Acta Universitatis Danubius. Œconomica, Vol 14, No 5 (2018)

Labor Analysis for Developing

Countries and Regions of the World – Part One

Gina Ioan¹, Cătălin Angelo Ioan²

Abstract: The article analize the phenomenon of work for developing countries and regions of the World for each of the developing countries or regions of the World. A number of indicators are analyzed, such as: Labor force, Labor force with advanced education, Employment in agriculture, industry and services and also the phenomenon of unemployment.

Keywords: labor; agriculture; industry; services; unemployment

JEL Classification: J01

1. Main notions

In the following we will analyze the phenomeanon of work for developing countries and regions of the World for each of the developing countries or regions of the World.

The source of the statistical data present in the analysis is the World Bank, all the indicators and regression models being the contribution of the authors.

Before starting the analysis, we will briefly outline the significance of some (less usual) indicators.

Labor force includes people aged 15 or over who provide labor for the production of goods and services for a specified period, including employed persons, job-seekers and job-seekers for the first time.

Labor force with advanced education represents the working age population with an advanced level of education (short-term, undergraduate, masters, doctorate).

2. The Analysis

2.1. Aruba

The analysis of indicator: Population, total during - highlights an average of 74712.37. Also for Population, total the region ranks on the first 91% in the World.

2.2. Afghanistan

The analysis of indicator: Population, total during - highlights an average of 17040452.79. Also for Population, total the region ranks on the first 32% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 6419805.15. Also for Labor force, total the region ranks on the first 41% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 255744.925*Year-505837279.443. From this equation we can note that, every year, the indicator grow with 255744.925.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 14.37 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 98% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 66.21 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 12% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 85.13 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 4% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 62.83 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 12% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 9.95 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 86% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 5.66 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 81% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 10.73 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 89% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 23.85 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 9% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 9.21 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 99% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 26.43 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 89% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 23.14 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 84% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 23.23 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 93% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.00 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 65% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.68 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 73% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.50 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 63% in the World.

2.3. Angola

The analysis of indicator: Population, total during - highlights an average of 13292350.05. Also for Population, total the region ranks on the first 35% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 388190.100*Year-758429568.129. From this equation we can note that, every year, the indicator grow with 388190.100.

The analysis of: Labor force, total during 1990-2016 highlights an average of 7808647.11. Also for Labor force, total the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 263508.970*Year-519999819.970. From this equation we can note that, every year, the indicator grow with 263508.970.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 49.74 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 4% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.027*Year-4.004. From this equation we can note that, every year, the indicator grow with 0.027.

Employment in agriculture (% of total employment) during - highlights an average of 7.54 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.316*Year+641.470. From this equation we can note that, every year, the indicator decreases with 0.316.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 14.43 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 61% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.538*Year+1092.352. From this equation we can note that, every year, the indicator decreases with 0.538.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 1.72 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 99% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 38.61 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 2% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 21.42 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 11% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 52.95 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 1% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 53.84 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 64.15 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 44% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 45.33 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 56% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 27.90 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 76% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 48.36 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 64% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.28 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 41% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.79 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 44% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.83 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 42% in the World.

2.4. Albania

The analysis of indicator: Population, total during - highlights an average of 2700066.77. Also for Population, total the region ranks on the first 70% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 1325670.81. Also for Labor force, total the region ranks on the first 78% in the World. The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 42.11 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 58% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2011-2015 highlights an average of 73.96Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 69% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2011-2015 highlights an average of 74.16Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 89% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2011-2015 highlights an average of 74.06Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 84% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 51.21 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.895*Year+1843.402. From this equation we can note that, every year, the indicator decreases with 0.895.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 60.85 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 23% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.807*Year+1677.007. From this equation we can note that, every year, the indicator decreases with 0.807.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 44.35 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 28% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 16.50 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 60% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.02 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 45% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 20.35 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 61% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 32.27 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 4% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.640*Year-1250.857. From this equation we can note that, every year, the indicator grow with 0.640.The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 28.12 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 76% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.865*Year-1705.850. From this equation we can note that, every year, the indicator grow with 0.865.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 35.32 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 75% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 31.21 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 73% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 37.30 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 83% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 14.59 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 89% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 15.21 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 79% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 14.15 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 91% in the World.

2.5. Andorra

The analysis of indicator: Population, total during - highlights an average of 50205.37. Also for Population, total the region ranks on the first 93% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 1393.537*Year-2720147.111. From this equation we can note that, every year, the indicator grow with 1393.537.

2.6. Arab World

The analysis of indicator: Population, total during - highlights an average of 222496109.60. Also for Population, total the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 5641778.043*Year-10993358639.191. From this equation we can note that, every year, the indicator grow with 5641778.043.

The analysis of: Labor force, total during 1990-2016 highlights an average of 94210147.59. Also for Labor force, total the region ranks on the first 18% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 2788544.462*Year-5491244410.092. From this equation we can note that, every year, the indicator grow with 2788544.462.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 20.20 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 95% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 26.17 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.453*Year+933.632. From this equation we can note that, every year, the indicator decreases with 0.453.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 33.98 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 42% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.513*Year+1062.497. From this equation we can note that, every year, the indicator decreases with 0.513.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 24.36 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.446*Year+917.153. From this equation we can note that, every year, the indicator decreases with 0.446.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 22.28 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 25% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.35 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 34% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.14 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 43% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 51.55 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.298*Year-545.238. From this equation we can note that, every year, the indicator grow with 0.298.The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 51.68 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.687*Year-1324.404. From this equation we can note that, every year, the indicator grow with 0.687.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 51.49 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 39% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 55.06 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 52% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.640*Year-1226.925. From this equation we can note that, every year, the indicator grow with 0.640.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 64.07 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 40% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.19 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 77% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 20.95 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 87% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.87 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 71% in the World.

2.7. United Arab Emirates

The analysis of indicator: Population, total during - highlights an average of 2723790.95. Also for Population, total the region ranks on the first 53% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 3252644.22. Also for Labor force, total the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 254756.578*Year-507024780.578. From this equation we can note that, every year, the indicator grow with 254756.578.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 11.79 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 100% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 5.58 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 86% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.214*Year+434.707. From this equation we can note that, every year, the indicator decreases with 0.214.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 6.26 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.240*Year+486.207. From this equation we can note that, every year, the indicator decreases with 0.240.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 30.27 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 46% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 7.59 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 84% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 33.08 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 62% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 92.33 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 2% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 60.66 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 4% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 98.67 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 2% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 95.70 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 2% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.33 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 14% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.93 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 64% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 2.58 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 11% in the World.

2.8. Argentina

The analysis of indicator: Population, total during - highlights an average of 31852734.81. Also for Population, total the region ranks on the first 28% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 425710.846*Year-814460427.159. From this equation we can note that, every year, the indicator grow with 425710.846.

The analysis of: Labor force, total during 1990-2016 highlights an average of 16949910.89. Also for Labor force, total the region ranks on the first 32% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 234907.020*Year-453568850.465. From this equation we can note that, every year, the indicator grow with 234907.020.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 40.66 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 67% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2004-2014 highlights an average of 72.44Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 35% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2004-2014 highlights an average of 81.43Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 19% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2004-2014 highlights an average of 75.99Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 30% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 1.07 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 93% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.39 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 96% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 1.50 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 92% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 24.95 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 22% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.05 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 59% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 33.57 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 11% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 88.57 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 10% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 64.91 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 23% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 77.64 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 31% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 70.99 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 34% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 11.24 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 67% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 13.18 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 67% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 10.01 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 64% in the World.

2.9. Armenia

The analysis of indicator: Population, total during - highlights an average of 2909755.18. Also for Population, total the region ranks on the first 69% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 1349415.04. Also for Labor force, total the region ranks on the first 78% in the World. The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.97 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 27% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2011-2015 highlights an average of 65.02Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 79% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2011-2015 highlights an average of 83.60Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 32% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: 1.530*Year-2996.292. From this equation we can note that, every year, the indicator grow with 1.530.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2011-2015 highlights an average of 72.62Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 63% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 40.16 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 30% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 46.81 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 30% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 34.95 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 36% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 18.87 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 70% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.78 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 65% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 25.14 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 62% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 40.97 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 42.42 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 65% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 39.89 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 62% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 52.36 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 56% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 56.58 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 61% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 17.62 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 91% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 19.58 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 85% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 15.91 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 92% in the World.

2.10. American Samoa

The analysis of indicator: Population, total during - highlights an average of 42210.81. Also for Population, total the region ranks on the first 95% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 790.884*Year-1530066.668. From this equation we can note that, every year, the indicator grow with 790.884.

2.11. Antigua and Barbuda

The analysis of indicator: Population, total during - highlights an average of 75765.37. Also for Population, total the region ranks on the first 92% in the World.

2.12. Australia

The analysis of indicator: Population, total during - highlights an average of 16686639.46. Also for Population, total the region ranks on the first 37% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 234606.627*Year-449711334.716. From this equation we can note that, every year, the indicator grow with 234606.627.

The analysis of: Labor force, total during 1990-2016 highlights an average of 10348688.74. Also for Labor force, total the region ranks on the first 38% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 172948.469*Year-336067095.618. From this equation we can note that, every year, the indicator grow with 172948.469.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.99 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.179*Year-314.767. From this equation we can note that, every year, the indicator grow with 0.179.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2013 highlights an average of 81.48Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 35% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2013 highlights an average of 91.18Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 25% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2013 highlights an average of 85.82Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 29% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 4.05 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.126*Year+255.570. From this equation we can note that, every year, the indicator decreases with 0.126.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.81 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 85% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.100*Year+204.120. From this equation we can note that, every year, the indicator decreases with 0.100.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 5.02 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 90% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.139*Year+284.486. From this equation we can note that, every year, the indicator decreases with 0.139.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.78 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 44% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 9.93 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 59% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.160*Year+331.111. From this equation we can note that, every year, the indicator decreases with 0.160.The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 31.16 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 22% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 87.26 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.260*Year-433.854. From this equation we can note that, every year, the indicator grow with 0.260.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 63.81 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 18% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 85.88 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 22% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.141*Year-195.842. From this equation we can note that, every year, the indicator grow with 0.141.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 76.96 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 25% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.72 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 37% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.60 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 28% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.79 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 42% in the World.

2.13. Austria

The analysis of indicator: Population, total during - highlights an average of 7792513.28. Also for Population, total the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 24519.683*Year-40952617.384. From this equation we can note that, every year, the indicator grow with 24519.683.

The analysis of: Labor force, total during 1990-2016 highlights an average of 4029825.41. Also for Labor force, total the region ranks on the first 59% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 33383.073*Year-62836470.333. From this equation we can note that, every year, the indicator grow with 33383.073.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.45 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 25% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.222*Year-400.410. From this equation we can note that, every year, the indicator grow with 0.222.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1995-2016 highlights an average of 77.21Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 36% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1995-2016 highlights an average of 77.93Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 82% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1995-2016 highlights an average of 77.64Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 68% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 5.82 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 80% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 6.12 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 72% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: -0.176*Year+358.876. From this equation we can note that, every year, the indicator decreases with 0.176.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 5.62 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 83% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 28.75 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 19% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.16 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 35% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 40.39 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 8% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 79.71 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 29% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 53.97 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 30% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 87.67 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 15% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 84.41 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 11% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.84 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 40% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.88 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 27% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.84 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 54% in the World.

2.14. Azerbaijan

The analysis of indicator: Population, total during - highlights an average of 6904155.44. Also for Population, total the region ranks on the first 51% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 98848.709*Year-189607078.897. From this equation we can note that, every year, the indicator grow with 98848.709.

The analysis of: Labor force, total during 1990-2016 highlights an average of 3848248.22. Also for Labor force, total the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 80962.231*Year-158319101.231. From this equation we can note that, every year, the indicator grow with 80962.231.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 47.89 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 12% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 40.12 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 29% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 44.06 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 29% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 36.57 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 35% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 12.13 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 75% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.99 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 77% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 16.89 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 65% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 47.75 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 48.95 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 67% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 46.53 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 59% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 29.57 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 78% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 31.27 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 84% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.31 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 25% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.18 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 28% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.52 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 22% in the World.

2.15. Burundi

The analysis of indicator: Population, total during - highlights an average of 5507297.95. Also for Population, total the region ranks on the first 50% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 126738.567*Year-246448974.064. From this equation we can note that, every year, the indicator grow with 126738.567.

The analysis of: Labor force, total during 1990-2016 highlights an average of 3253599.48. Also for Labor force, total the region ranks on the first 58% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 81068.653*Year-159126912.950. From this equation we can note that, every year, the indicator grow with 81068.653.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 52.26 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 1% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 91.29 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 0% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 95.96 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 0% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 86.33 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 0% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 2.62 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 99% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 0.91 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 99% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 4.45 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 99% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 6.08 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 61% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 3.12 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 100% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 9.23 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 100% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 2.32 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 100% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 9.65 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 100% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 1.62 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 3% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 1.87 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 4% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 1.32 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 3% in the World.

2.16. Belgium

The analysis of indicator: Population, total during - highlights an average of 10079001.82. Also for Population, total the region ranks on the first 47% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 31169.567*Year-51886097.800. From this equation we can note that, every year, the indicator grow with 31169.567.

The analysis of: Labor force, total during 1990-2016 highlights an average of 4505231.85. Also for Labor force, total the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 42635.941*Year-80894558.756. From this equation we can note that, every year, the indicator grow with 42635.941.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.25 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 33% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.248*Year-454.154. From this equation we can note that, every year, the indicator grow with 0.248.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 highlights an average of 76.92Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 59% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 81.16Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.476*Year+1035.684. From this equation we can note that, every year, the indicator decreases with 0.476.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 79.01Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 75% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.322*Year+724.450. From this equation we can note that, every year, the indicator decreases with 0.322.

Employment in agriculture (% of total employment) during - highlights an average of 1.93 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 97% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 1.38 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 93% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 2.37 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 97% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 25.32 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 45% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.351*Year+729.387. From this equation we can note that, every year, the indicator decreases with 0.351.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.37 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 60% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.260*Year+531.453. From this equation we can note that, every year, the indicator decreases with 0.260.The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 35.83 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 19% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.277*Year+591.057. From this equation we can note that, every year, the indicator decreases with 0.277.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 87.27 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 11% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.318*Year-549.604. From this equation we can note that, every year, the indicator grow with 0.318.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 61.80 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.347*Year-634.391. From this equation we can note that, every year, the indicator grow with 0.347.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 86.94 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 17% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 81.95 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 19% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.96 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 60% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 9.16 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 52% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.12 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 66% in the World.

2.17. Benin

The analysis of indicator: Population, total during - highlights an average of 5404568.54. Also for Population, total the region ranks on the first 48% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 148548.651*Year-289910148.919. From this equation we can note that, every year, the indicator grow with 148548.651.

The analysis of: Labor force, total during 1990-2016 highlights an average of 3053640.85. Also for Labor force, total the region ranks on the first 59% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 92069.167*Year-181360901.204. From this equation we can note that, every year, the indicator grow with 92069.167.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.43 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.349*Year-651.920. From this equation we can note that, every year, the indicator grow with 0.349.

Employment in agriculture (% of total employment) during - highlights an average of 46.09 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 23% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 34.11 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 33% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 56.37 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.275*Year+607.832. From this equation we can note that, every year, the indicator decreases with 0.275.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 8.93 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 85% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.88 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 76% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 10.79 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.310*Year-610.738. From this equation we can note that, every year, the indicator grow with 0.310.

Employment in services (% of total employment) during 1991-2016 highlights an average of 44.98 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 59.01 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 55% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 32.84 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 85% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 4.16 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 99% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 14.26 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 98% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 0.99 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 2% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 0.92 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 1% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 1.05 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 2% in the World.

2.18. Burkina Faso

The analysis of indicator: Population, total during - highlights an average of 9504210.60. Also for Population, total the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 235256.934*Year-458186573.712. From this equation we can note that, every year, the indicator grow with 235256.934.

The analysis of: Labor force, total during 1990-2016 highlights an average of 5166462.26. Also for Labor force, total the region ranks on the first 48% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 107900.882*Year-210959004.734. From this equation we can note that, every year, the indicator grow with 107900.882.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.47 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 43% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 83.39 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 1% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 85.60 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 3% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 81.35 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 1% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 4.09 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 96% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 2.81 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 89% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 5.27 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 97% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 12.53 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 31% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 11.59 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 98% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 13.39 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 99% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.214*Year-415.391. From this equation we can note that, every year, the indicator grow with 0.214.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 3.07 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 99% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.134*Year-265.297. From this equation we can note that, every year, the indicator grow with 0.134.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 7.87 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 99% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.212*Year-417.691. From this equation we can note that, every year, the indicator grow with 0.212.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 2.94 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 10% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 2.07 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 6% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.72 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 20% in the World.

2.19. Bangladesh

The analysis of indicator: Population, total during - highlights an average of 103244602.63. Also for Population, total the region ranks on the first 19% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 2180762.362*Year-4232110973.162. From this equation we can note that, every year, the indicator grow with 2180762.362.

The analysis of: Labor force, total during 1990-2016 highlights an average of 50619446.33. Also for Labor force, total the region ranks on the first 22% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 1206702.270*Year-2366405201.382. From this equation we can note that, every year, the indicator grow with 1206702.270.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 23.77 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.348*Year-673.706. From this equation we can note that, every year, the indicator grow with 0.348.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2006-2016 highlights an average of 19.79Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 96% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2006-2016 highlights an average of 32.21Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 13% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2006-2016 highlights an average of 28.73Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 63% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 52.50 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.875*Year+1805.991. From this equation we can note that, every year, the indicator decreases with 0.875.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 67.74 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 19% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 43.98 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 34% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 14.03 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 58% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.06 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 29% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 15.08 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 68% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 33.49 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 5% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 20.20 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.352*Year-685.378. From this equation we can note that, every year, the indicator grow with 0.352.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 40.94 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 59% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 17.75 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 74% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 27.97 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 76% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.83 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 17% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.58 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 24% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.41 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 16% in the World.

2.20. Bulgaria

The analysis of indicator: Population, total during - highlights an average of 8249426.68. Also for Population, total the region ranks on the first 57% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 3555722.07. Also for Labor force, total the region ranks on the first 64% in the World. The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.84 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 30% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2000-2016 highlights an average of 73.29Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 73% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2000-2016 highlights an average of 74.59Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 85% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2000-2016 highlights an average of 73.82Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 86% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 10.13 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 75% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 7.90 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 74% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 12.10 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 73% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 33.37 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 8% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 27.52 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 7% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 38.52 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 12% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 64.57 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 43% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 49.38 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 35% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 87.42 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 11% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 83.21 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 10% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.92 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 58% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 12.37 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 48% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 13.40 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 66% in the World.

2.21. Bahrain

The analysis of indicator: Population, total during - highlights an average of 569312.30. Also for Population, total the region ranks on the first 76% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 458107.04. Also for Labor force, total the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 26087.392*Year-51794939.022. From this equation we can note that, every year, the indicator grow with 26087.392.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 20.41 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 93% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 1.54 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 98% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.056*Year+114.693. From this equation we can note that, every year, the indicator decreases with 0.056.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2009 highlights an average of 0.16 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 100% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 1.88 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 98% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.065*Year+131.334. From this equation we can note that, every year, the indicator decreases with 0.065.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 30.81 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 4% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 9.15 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 62% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 35.98 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 5% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 90.72 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 7% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 62.17 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 26% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 97.83 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 3% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 95.99 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 1% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 1.32 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 2% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.50 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 16% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 0.56 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 0% in the World.

2.22. Bahamas

The analysis of indicator: Population, total during - highlights an average of 249515.95. Also for Population, total the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 4818.042*Year-9328752.454. From this equation we can note that, every year, the indicator grow with 4818.042.

The analysis of: Labor force, total during 1990-2016 highlights an average of 177922.56. Also for Labor force, total the region ranks on the first 92% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 4414.952*Year-8665227.063. From this equation we can note that, every year, the indicator grow with 4414.952.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 47.39 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 19% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 3.90 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 84% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.98 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 91% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 6.53 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 78% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 15.33 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 76% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 4.69 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 87% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.99 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 60% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 94.33 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 2% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 68.47 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 8% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 84.52 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 34% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 78.56 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 18% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 11.23 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 83% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 12.17 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 78% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 10.37 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 82% in the World.

2.23. Bosnia and Herzegovina

The analysis of indicator: Population, total during - highlights an average of 3879438.93. Also for Population, total the region ranks on the first 68% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 1518555.85. Also for Labor force, total the region ranks on the first 77% in the World. The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.94 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 76% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.058*Year+155.813. From this equation we can note that, every year, the indicator decreases with 0.058.

Employment in agriculture (% of total employment) during - highlights an average of 27.43 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 55% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 31.14 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 51% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 25.43 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 56% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 29.37 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 6% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 18.27 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 12% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 35.53 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 7% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 43.20 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 50.60 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 52% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 39.04 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 68% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 64.43 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 35% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 59.15 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 33% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 23.75 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 97% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 24.87 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 91% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 23.10 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 99% in the World.

2.24. Belarus

The analysis of indicator: Population, total during - highlights an average of 9534427.65. Also for Population, total the region ranks on the first 52% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 4900360.04. Also for Labor force, total the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 20572.553*Year-36306462.627. From this equation we can note that, every year, the indicator grow with 20572.553.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 49.05 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 6% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.069*Year-88.820. From this equation we can note that, every year, the indicator grow with 0.069.

Employment in agriculture (% of total employment) during - highlights an average of 12.67 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 69% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.283*Year+580.434. From this equation we can note that, every year, the indicator decreases with 0.283.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 7.42 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 67% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.152*Year+311.536. From this equation we can note that, every year, the indicator decreases with 0.152.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 17.68 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 66% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.403*Year+824.283. From this equation we can note that, every year, the indicator decreases with 0.403.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 36.74 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 5% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: -0.413*Year+863.345. From this equation we can note that, every year, the indicator decreases with 0.413.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 38.58 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 3% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.724*Year+1489.316. From this equation we can note that, every year, the indicator decreases with 0.724.The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 35.01 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 17% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 50.58 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.696*Year-1344.810. From this equation we can note that, every year, the indicator grow with 0.696.The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 53.99 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.876*Year-1701.625. From this equation we can note that, every year, the indicator grow with 0.876.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 47.33 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.524*Year-1001.822. From this equation we can note that, every year, the indicator grow with 0.524.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 97.19 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 2% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 95.07 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 2% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 0.64 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 0% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 0.63 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 0% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 0.64 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 0% in the World.

2.25. Belize

The analysis of indicator: Population, total during - highlights an average of 198204.54. Also for Population, total the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 4787.560*Year-9319464.649. From this equation we can note that, every year, the indicator grow with 4787.560.

The analysis of: Labor force, total during 1990-2016 highlights an average of 106801.56. Also for Labor force, total the region ranks on the first 95% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 4347.816*Year-8601874.372. From this equation we can note that, every year, the indicator grow with 4347.816.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 34.81 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.481*Year-928.191. From this equation we can note that, every year, the indicator grow with 0.481.

Employment in agriculture (% of total employment) during - highlights an average of 21.55 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 59% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 4.33 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 70% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 29.72 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 47% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 17.65 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 69% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.39 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 62% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 21.26 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 68% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 85.26 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 20% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 49.01 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 33% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 72.31 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 38% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 64.61 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 42% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.84 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 75% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 16.52 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 82% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.64 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 59% in the World.

2.26. Bermuda

The analysis of indicator: Population, total during - highlights an average of 57715.63. Also for Population, total the region ranks on the first 94% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 333.277*Year-604839.359. From this equation we can note that, every year, the indicator grow with 333.277.

2.27. Bolivia

The analysis of indicator: Population, total during - highlights an average of 6840732.05. Also for Population, total the region ranks on the first 48% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 130992.198*Year-253571757.475. From this equation we can note that, every year, the indicator grow with 130992.198.

The analysis of: Labor force, total during 1990-2016 highlights an average of 3931589.37. Also for Labor force, total the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 92255.614*Year-180856404.577. From this equation we can note that, every year, the indicator grow with 92255.614.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 42.26 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 64% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2005-2015 highlights an average of 71.17Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 65% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2005-2015 highlights an average of 81.43Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 34% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2005-2015 highlights an average of 76.50Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 44% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 34.39 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 35% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.359*Year+753.388. From this equation we can note that, every year, the indicator decreases with 0.359.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 32.04 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 45% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 36.11 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 33% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.262*Year+560.374. From this equation we can note that, every year, the indicator decreases with 0.262.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.19 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 46% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.22 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 47% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 28.42 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 31% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 44.41 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.365*Year-686.095. From this equation we can note that, every year, the indicator grow with 0.365.The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 56.73 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 52% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.561*Year-1067.349. From this equation we can note that, every year, the indicator grow with 0.561.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 35.47 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 78% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 65.40 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 47% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 60.82 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 52% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.25 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 11% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 5.19 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 16% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.55 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 8% in the World.

2.28. Brazil

The analysis of indicator: Population, total during - highlights an average of 142325306.58. Also for Population, total the region ranks on the first 18% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 2535776.498*Year-4898798371.555. From this equation we can note that, every year, the indicator grow with 2535776.498.

The analysis of: Labor force, total during 1990-2016 highlights an average of 84224567.07. Also for Labor force, total the region ranks on the first 20% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 1746415.243*Year-3413845164.613. From this equation we can note that, every year, the indicator grow with 1746415.243.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 40.33 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 54% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2016 highlights an average of 69.84Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 38% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2016 highlights an average of 77.50Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 18% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2016 highlights an average of 73.05Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 28% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 20.33 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 61% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.563*Year+1147.706. From this equation we can note that, every year, the indicator decreases with 0.563.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 15.78 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 57% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 23.41 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 57% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.537*Year+1099.750. From this equation we can note that, every year, the indicator decreases with 0.537.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.13 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 41% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.42 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 43% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 27.71 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 33% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 72.81 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 37% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 48.88 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 41% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 67.91 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 38% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 62.54 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 49% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.84 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 78% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 13.16 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 75% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.19 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 78% in the World.

2.29. Barbados

The analysis of indicator: Population, total during - highlights an average of 258170.93. Also for Population, total the region ranks on the first 85% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 975.126*Year-1680379.696. From this equation we can note that, every year, the indicator grow with 975.126.

The analysis of: Labor force, total during 1990-2016 highlights an average of 146918.85. Also for Labor force, total the region ranks on the first 96% in the World. The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 48.57 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 5% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 3.76 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 89% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.63 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 87% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 4.78 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 86% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 18.23 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 55% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 9.13 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 53% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 26.58 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 33% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 88.21 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 15% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 68.62 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 12% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 89.41 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 20% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 80.68 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 26% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.84 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 77% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 14.51 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 69% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 11.29 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 84% in the World.

2.30. Brunei Darussalam

The analysis of indicator: Population, total during - highlights an average of 249001.86. Also for Population, total the region ranks on the first 83% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 6436.835*Year-12547427.102. From this equation we can note that, every year, the indicator grow with 6436.835.

The analysis of: Labor force, total during 1990-2016 highlights an average of 166422.56. Also for Labor force, total the region ranks on the first 93% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 4210.931*Year-8268072.264. From this equation we can note that, every year, the indicator grow with 4210.931.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.47 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 55% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 1.18 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 99% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.060*Year+122.277. From this equation we can note that, every year, the indicator decreases with 0.060.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.54 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 95% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 1.58 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 99% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.083*Year+167.200. From this equation we can note that, every year, the indicator decreases with 0.083.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.19 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 55% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.45 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 41% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 27.84 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 59% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 89.04 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 17% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 70.58 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 4% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 94.08 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 7% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 92.15 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 4% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.55 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 49% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.74 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 54% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.82 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 42% in the World.

2.31. Bhutan

The analysis of indicator: Population, total during - highlights an average of 487095.63. Also for Population, total the region ranks on the first 79% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 10160.868*Year-19712709.372. From this equation we can note that, every year, the indicator grow with 10160.868.

The analysis of: Labor force, total during 1990-2016 highlights an average of 272035.74. Also for Labor force, total the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 9224.685*Year-18205008.278. From this equation we can note that, every year, the indicator grow with 9224.685.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 41.00 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 70% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 58.16 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 14% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 72.85 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 14% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 49.05 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 16% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 12.44 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 86% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.78 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 54% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 15.90 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 91% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 29.39 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 7% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 20.38 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 88% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 35.04 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 78% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 14.46 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 90% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 40.14 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 85% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 2.66 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 6% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 3.37 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 10% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 2.18 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 5% in the World.

2.32. Botswana

The analysis of indicator: Population, total during - highlights an average of 1309982.39. Also for Population, total the region ranks on the first 72% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 32445.108*Year-63190891.387. From this equation we can note that, every year, the indicator grow with 32445.108.

The analysis of: Labor force, total during 1990-2016 highlights an average of 737041.52. Also for Labor force, total the region ranks on the first 81% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 22959.426*Year-45250689.019. From this equation we can note that, every year, the indicator grow with 22959.426.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.38 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.292*Year-542.159. From this equation we can note that, every year, the indicator grow with 0.292.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2010 highlights an average of 77.10Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 76% in the World. Time regression analysis reveals a correlation coefficient value: -1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: -15.000*Year+30219.600. From this equation we can note that, every year, the indicator decreases with 15.000.The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2010 highlights an average of 82.55Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: -1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: -14.900*Year+30024.103. From this equation we can note that, every year, the indicator decreases with 14.900.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2010 highlights an average of 80.00Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 83% in the World. Time regression analysis reveals a correlation coefficient value: -1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: -15.200*Year+30624.394. From this equation we can note that, every year, the indicator decreases with 15.200.

Employment in agriculture (% of total employment) during - highlights an average of 22.75 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 43% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 16.90 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 49% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 27.63 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 37% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 20.10 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 72% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.54 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 51% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.77 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 73% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 57.17 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 68.55 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 47% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 47.61 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 49% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 72.63 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 28% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 75.97 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 20% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 18.43 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 91% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 21.13 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 88% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 15.96 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 90% in the World.

2.33. Central African Republic

The analysis of indicator: Population, total during - highlights an average of 2945240.58. Also for Population, total the region ranks on the first 64% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 62046.933*Year-120404061.539. From this equation we can note that, every year, the indicator grow with 62046.933.

The analysis of: Labor force, total during 1990-2016 highlights an average of 1603432.56. Also for Labor force, total the region ranks on the first 75% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 26468.748*Year-51413470.637. From this equation we can note that, every year, the indicator grow with 26468.748.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.79 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 40% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 70.05 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 4% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 81.44 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 4% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 60.35 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 6% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 4.55 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 97% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 0.97 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 98% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 7.60 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 96% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 25.42 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 16% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 17.61 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 97% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 32.05 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 91% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 17.86 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 93% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 40.37 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 86% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.16 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 48% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.64 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 45% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.77 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 47% in the World.

2.34. Canada

The analysis of indicator: Population, total during - highlights an average of 27059815.63. Also for Population, total the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 318640.133*Year-606396768.396. From this equation we can note that, every year, the indicator grow with 318640.133.

The analysis of: Labor force, total during 1990-2016 highlights an average of 17163277.04. Also for Labor force, total the region ranks on the first 32% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 228450.460*Year-440422994.979. From this equation we can note that, every year, the indicator grow with 228450.460.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.03 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 22% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.127*Year-207.560. From this equation we can note that, every year, the indicator grow with 0.127.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1990-2016 highlights an average of 67.62Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 72% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1990-2016 highlights an average of 70.71Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 72% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1990-2016 highlights an average of 69.14Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 73% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 2.99 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 93% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.101*Year+204.982. From this equation we can note that, every year, the indicator decreases with 0.101.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 1.75 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.063*Year+127.440. From this equation we can note that, every year, the indicator decreases with 0.063.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 4.06 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 93% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.128*Year+260.574. From this equation we can note that, every year, the indicator decreases with 0.128.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.47 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 54% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.32 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 58% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 31.11 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 32% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 87.94 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 12% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 64.82 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 10% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 88.30 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 20% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 80.80 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 20% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.01 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 54% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.51 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 35% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.44 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 63% in the World.

2.35. Central Europe and the Baltics

The analysis of indicator: Population, total during - highlights an average of 104444580.39. Also for Population, total the region ranks on the first 21% in the World.

The analysis of: Labor force, total during 1990-2016 highlights an average of 50320375.41. Also for Labor force, total the region ranks on the first 24% in the World. The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.53 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 41% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1997-2016 highlights an average of 77.69Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 48% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1997-2016 highlights an average of 80.63Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 55% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1997-2016 highlights an average of 79.03Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 53% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 17.18 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 67% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.517*Year+1052.219. From this equation we can note that, every year, the indicator decreases with 0.517.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 16.74 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 58% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.571*Year+1160.048. From this equation we can note that, every year, the indicator decreases with 0.571.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 17.54 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 67% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.473*Year+964.637. From this equation we can note that, every year, the indicator decreases with 0.473.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 32.51 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 7% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 22.34 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 14% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 40.95 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 5% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 50.31 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.715*Year-1382.834. From this equation we can note that, every year, the indicator grow with 0.715.The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 60.92 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 44% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.971*Year-1884.848. From this equation we can note that, every year, the indicator grow with 0.971.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 41.51 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 56% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.508*Year-976.563. From this equation we can note that, every year, the indicator grow with 0.508.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 78.17 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.498*Year-918.717. From this equation we can note that, every year, the indicator grow with 0.498.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 74.59 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 26% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.23 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 50% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.52 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 40% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.98 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 55% in the World.

2.36. Switzerland

The analysis of indicator: Population, total during - highlights an average of 6772169.44. Also for Population, total the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 44456.219*Year-81606793.453. From this equation we can note that, every year, the indicator grow with 44456.219.

The analysis of: Labor force, total during 1990-2016 highlights an average of 4214331.93. Also for Labor force, total the region ranks on the first 56% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 39974.808*Year-75855209.105. From this equation we can note that, every year, the indicator grow with 39974.808.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.92 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.155*Year-265.080. From this equation we can note that, every year, the indicator grow with 0.155.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1996-2016 highlights an average of 79.54Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 26% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1996-2016 highlights an average of 84.80Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 53% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1996-2016 highlights an average of 83.10Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 33% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 3.85 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 86% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.95 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 78% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 4.59 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 85% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 22.83 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 50% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.178*Year+379.355. From this equation we can note that, every year, the indicator decreases with 0.178.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.57 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 46% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 31.94 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 33% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 85.48 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 21% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.145*Year-205.421. From this equation we can note that, every year, the indicator grow with 0.145.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 63.47 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 12% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 85.27 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 21% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 81.56 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 13% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.73 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 22% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.19 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 19% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.37 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 23% in the World.

2.37. Channel Islands

The analysis of indicator: Population, total during - highlights an average of 137615.16. Also for Population, total the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 974.439*Year-1799570.103. From this equation we can note that, every year, the indicator grow with 974.439.

The analysis of: Labor force, total during 1990-2016 highlights an average of 74754.00. Also for Labor force, total the region ranks on the first 98% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 546.094*Year-1019072.316. From this equation we can note that, every year, the indicator grow with 546.094.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 42.74 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 49% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 5.48 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 78% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.97 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 91% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 8.95 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 74% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 25.00 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 23% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 17.79 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 16% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 30.62 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 26% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 81.22 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 30% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 60.41 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 22% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 89.62 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 13% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 81.65 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 16% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.19 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 52% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.44 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 55% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.24 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 46% in the World.

2.38. Chile

The analysis of indicator: Population, total during - highlights an average of 12884621.11. Also for Population, total the region ranks on the first 41% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 186756.498*Year-358387296.900. From this equation we can note that, every year, the indicator grow with 186756.498.

The analysis of: Labor force, total during 1990-2016 highlights an average of 6760745.44. Also for Labor force, total the region ranks on the first 44% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 152497.449*Year-298691644.338. From this equation we can note that, every year, the indicator grow with 152497.449.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 35.49 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 64% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.440*Year-845.563. From this equation we can note that, every year, the indicator grow with 0.440.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2010-2016 highlights an average of 77.66Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 46% in the World. The analysis of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2010-2016 highlights an average of 89.79Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 12% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2010-2016 highlights an average of 83.90Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 23% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 13.05 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 69% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.320*Year+653.554. From this equation we can note that, every year, the indicator decreases with 0.320.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 5.08 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 70% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 17.21 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 66% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.395*Year+809.502. From this equation we can note that, every year, the indicator decreases with 0.395.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 24.07 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 32% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.38 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 42% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 30.50 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 24% in the World.

The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 82.52 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 27% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 52.28 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 33% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 73.93 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 41% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 69.23 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 36% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.11 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 51% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.25 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 51% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.49 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 51% in the World.

2.39. China

The analysis of indicator: Population, total during - highlights an average of 1071848070.18. Also for Population, total the region ranks on the first 6% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 13552779.038*Year-25871076657.592. From this equation we can note that, every year, the indicator grow with 13552779.038.

The analysis of: Labor force, total during 1990-2016 highlights an average of 738319219.41. Also for Labor force, total the region ranks on the first 6% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 5803686.051*Year-10886463941.311. From this equation we can note that, every year, the indicator grow with 5803686.051.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.61 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.061*Year+167.660. From this equation we can note that, every year, the indicator decreases with 0.061.

Employment in agriculture (% of total employment) during - highlights an average of 42.78 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 42% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -1.136*Year+2318.205. From this equation we can note that, every year, the indicator decreases with 1.136.The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 46.27 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 36% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 39.96 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 46% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -1.275*Year+2594.506. From this equation we can note that, every year, the indicator decreases with 1.275.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.76 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 28% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 17.77 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 21% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.96 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 30% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 35.46 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.944*Year-1855.157. From this equation we can note that, every year, the indicator grow with 0.944.The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 35.95 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 68% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 1.086*Year-2139.881. From this equation we can note that, every year, the indicator grow with 1.086.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 35.08 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.832*Year-1632.383. From this equation we can note that, every year, the indicator grow with 0.832.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 47.54 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 52% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 1.424*Year-2806.404. From this equation we can note that, every year, the indicator grow with 1.424.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 51.56 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 47% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 1.412*Year-2777.586. From this equation we can note that, every year, the indicator grow with 1.412.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.42 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 22% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 3.82 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 14% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.90 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 33% in the World.

2.40. Cote d'Ivoire

The analysis of indicator: Population, total during - highlights an average of 12059651.37. Also for Population, total the region ranks on the first 38% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 370145.547*Year-723789696.826. From this equation we can note that, every year, the indicator grow with 370145.547.

The analysis of: Labor force, total during 1990-2016 highlights an average of 6281145.33. Also for Labor force, total the region ranks on the first 46% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 112426.313*Year-218908759.980. From this equation we can note that, every year, the indicator grow with 112426.313.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 36.38 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 66% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.300*Year-565.077. From this equation we can note that, every year, the indicator grow with 0.300.

Employment in agriculture (% of total employment) during - highlights an average of 60.45 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 15% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 78.50 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 8% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 50.92 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 21% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 5.11 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 95% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 0.77 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 99% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 7.40 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 95% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 34.43 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 5% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 20.72 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 89% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 41.66 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 62% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 10.45 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 94% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 26.30 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 91% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 9.19 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 69% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 11.45 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 70% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.94 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 65% in the World.

2.41. Cameroon

The analysis of indicator: Population, total during - highlights an average of 12067520.70. Also for Population, total the region ranks on the first 38% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 320687.258*Year-625458748.534. From this equation we can note that, every year, the indicator grow with 320687.258.

The analysis of: Labor force, total during 1990-2016 highlights an average of 7197361.04. Also for Labor force, total the region ranks on the first 42% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 202223.527*Year-397856363.268. From this equation we can note that, every year, the indicator grow with 202223.527.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.73 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 24% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 64.49 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 11% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 70.59 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.269*Year+610.129. From this equation we can note that, every year, the indicator decreases with 0.269.The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 59.49 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 12% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 8.67 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 88% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 7.00 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 73% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 10.08 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 90% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 26.82 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.158*Year-290.175. From this equation we can note that, every year, the indicator grow with 0.158.The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 22.43 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 87% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.280*Year-537.800. From this equation we can note that, every year, the indicator grow with 0.280.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 30.43 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 88% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 9.57 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 92% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.313*Year-617.094. From this equation we can note that, every year, the indicator grow with 0.313.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 27.98 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 90% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.18 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 19% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.17 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 24% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.36 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 17% in the World.

2.42. Congo, Dem. Rep.

The analysis of indicator: Population, total during - highlights an average of 37618326.00. Also for Population, total the region ranks on the first 23% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1063356.616*Year-2076334626.525. From this equation we can note that, every year, the indicator grow with 1063356.616.

The analysis of: Labor force, total during 1990-2016 highlights an average of 20983493.78. Also for Labor force, total the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 627178.651*Year-1235255343.762. From this equation we can note that, every year, the indicator grow with 627178.651.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 50.29 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 5% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 69.58 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 9% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 79.65 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 7% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 59.63 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 13% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 5.42 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 94% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 1.72 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 93% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 9.08 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 92% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 24.99 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 9% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 18.65 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 91% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 31.29 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 82% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 14.98 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 89% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 24.62 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 94% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.65 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 13% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.37 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 18% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 2.92 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 9% in the World.

2.43. Congo, Rep.

The analysis of indicator: Population, total during - highlights an average of 2568563.84. Also for Population, total the region ranks on the first 63% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 70741.657*Year-138065850.506. From this equation we can note that, every year, the indicator grow with 70741.657.

The analysis of: Labor force, total during 1990-2016 highlights an average of 1447140.93. Also for Labor force, total the region ranks on the first 73% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 44203.173*Year-87091815.359. From this equation we can note that, every year, the indicator grow with 44203.173.The analysis of indicator: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 48.76 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 13% in the World.

Employment in agriculture (% of total employment) during - highlights an average of 43.20 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 27% in the World. The analysis of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 49.39 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 24% in the World. The analysis of indicator: Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 37.87 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 30% in the World.

Employment in industry (% of total employment) during 1991-2016 highlights an average of 25.98 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 18% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 27.72 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 4% in the World. The analysis of indicator: Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.50 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 54% in the World.

Employment in services (% of total employment) during 1991-2016 highlights an average of 30.81 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 7% in the World. The analysis of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 22.89 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 88% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.64 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 75% in the World.

The analysis of indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 9.15 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 96% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 38.33 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 81% in the World.

Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.20 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 73% in the World. The analysis of indicator: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 14.48 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 73% in the World. The analysis of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 10.13 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 69% in the World.

2.44. Colombia

The study of indicator: Population, total during - highlights an average of 32860933.39. Also for Population, total the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 596749.567*Year-1153477206.625. From this equation we can note that, every year, the indicator grow with 596749.567.

The indicator: Labor force, total during 1990-2016 highlights an average of 18820380.33. Also for Labor force, total the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 599027.059*Year-1181030818.059. From this equation we can note that, every year, the indicator grow with 599027.059.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 36.77 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 54% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.626*Year-1216.726. From this equation we can note that, every year, the indicator grow with 0.626.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2016 reveals an average of 75.76Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 60% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2016 highlights an average of 82.93Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 50% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2016 highlights an average of 79.05Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 52% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 16.98 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 62% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 3.95 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 74% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 24.35 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 51% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 16.00 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 68% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.23 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 45% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 18.80 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 68% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 84.82 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 25% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 56.84 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 28% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 51.61 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 66% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 48.04 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 73% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 11.92 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 65% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 16.07 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 71% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.36 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 54% in the World.

2.45. Comoros

The study of indicator: Population, total during - highlights an average of 423053.81. Also for Population, total the region ranks on the first 80% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 10960.577*Year-21366573.146. From this equation we can note that, every year, the indicator grow with 10960.577.

The indicator: Labor force, total during 1990-2016 highlights an average of 143339.70. Also for Labor force, total the region ranks on the first 94% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 4158.032*Year-8185197.884. From this equation we can note that, every year, the indicator grow with 4158.032.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.17 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.205*Year-371.490. From this equation we can note that, every year, the indicator grow with 0.205.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 61.81 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 11% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 77.83 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 7% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 55.83 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 12% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 5.36 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 96% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 0.52 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 100% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 7.16 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 97% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 32.83 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 7% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 21.67 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 90% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.00 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 79% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 28.39 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 82% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 44.15 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 80% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 20.15 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 94% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 24.07 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 92% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 18.59 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 94% in the World.

2.46. Cabo Verde

The study of indicator: Population, total during - highlights an average of 356703.46. Also for Population, total the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 6093.114*Year-11756406.301. From this equation we can note that, every year, the indicator grow with 6093.114.

The indicator: Labor force, total during 1990-2016 highlights an average of 166400.15. Also for Labor force, total the region ranks on the first 92% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 4307.772*Year-8462067.735. From this equation we can note that, every year, the indicator grow with 4307.772.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.60 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: 0.148*Year-257.605. From this equation we can note that, every year, the indicator grow with 0.148.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 38.94 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 42% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -1.241*Year+2524.858. From this equation we can note that, every year, the indicator decreases with 1.241.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 53.78 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -1.322*Year+2702.853. From this equation we can note that, every year, the indicator decreases with 1.322.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 29.96 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 52% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -1.223*Year+2481.077. From this equation we can note that, every year, the indicator decreases with 1.223.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 9.57 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 81% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: 0.196*Year-382.911. From this equation we can note that, every year, the indicator grow with 0.196.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 1.20 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 96% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 14.67 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 75% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.334*Year-655.082. From this equation we can note that, every year, the indicator grow with 0.334.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 45.02 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 56% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 1.322*Year-2603.577. From this equation we can note that, every year, the indicator grow with 1.322.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 55.37 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 20% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 42.18 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 63% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1.335*Year-2631.889. From this equation we can note that, every year, the indicator grow with 1.335.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 51.94 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 59% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.97 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 72% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 13.74 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 75% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.25 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 72% in the World.

2.47. Costa Rica

The study of indicator: Population, total during - highlights an average of 3038258.32. Also for Population, total the region ranks on the first 63% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 66728.203*Year-129617409.005. From this equation we can note that, every year, the indicator grow with 66728.203.

The indicator: Labor force, total during 1990-2016 highlights an average of 1775060.70. Also for Labor force, total the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 47109.341*Year-92584948.637. From this equation we can note that, every year, the indicator grow with 47109.341.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 34.18 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 79% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.433*Year-832.501. From this equation we can note that, every year, the indicator grow with 0.433.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2010-2016 reveals an average of 71.80Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 85% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2010-2016 highlights an average of 81.54Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 65% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2010-2016 highlights an average of 76.37Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 79% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 16.80 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 65% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 4.43 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 76% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 22.72 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 61% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 22.18 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 57% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.265*Year+552.471. From this equation we can note that, every year, the indicator decreases with 0.265.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.87 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.494*Year+1005.180. From this equation we can note that, every year, the indicator decreases with 0.494.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 25.92 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 56% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 80.68 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 20% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.561*Year-1042.718. From this equation we can note that, every year, the indicator grow with 0.561.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 51.34 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.695*Year-1341.244. From this equation we can note that, every year, the indicator grow with 0.695.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 76.64 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 28% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 70.66 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 31% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.62 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 68% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.65 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 72% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.54 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 60% in the World.

2.48. Caribbean Small States

The study of indicator: Population, total during - highlights an average of 5868926.16. Also for Population, total the region ranks on the first 56% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 53325.522*Year-100142211.911. From this equation we can note that, every year, the indicator grow with 53325.522.

The indicator: Labor force, total during 1990-2016 highlights an average of 2881395.37. Also for Labor force, total the region ranks on the first 63% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 39599.051*Year-76435504.348. From this equation we can note that, every year, the indicator grow with 39599.051.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 41.49 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 56% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 15.32 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 65% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 7.03 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 69% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 20.87 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 59% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.40 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 49% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 8.94 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 69% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 29.83 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 28% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 84.04 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 19% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 49.31 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 42% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 71.68 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 43% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 62.33 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 58% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.45 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 75% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 16.60 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 78% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.40 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 69% in the World.

2.49. Cuba

The study of indicator: Population, total during - highlights an average of 10068954.32. Also for Population, total the region ranks on the first 46% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 73735.906*Year-136518026.198. From this equation we can note that, every year, the indicator grow with 73735.906.

The indicator: Labor force, total during 1990-2016 highlights an average of 4726093.30. Also for Labor force, total the region ranks on the first 51% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 50722.725*Year-96871525.429. From this equation we can note that, every year, the indicator grow with 50722.725.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 35.96 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 78% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2010 reveals an average of 83.95Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 12% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 0.500*Year-920.800. From this equation we can note that, every year, the indicator grow with 0.500.The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2010 highlights an average of 89.10Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 20% in the World. Time regression analysis reveals a correlation coefficient value: -1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: -0.800*Year+1696.706. From this equation we can note that, every year, the indicator decreases with 0.800.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2010 highlights an average of 86.30Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: -1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: -0.200*Year+488.209. From this equation we can note that, every year, the indicator decreases with 0.200.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 20.02 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 64% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 9.74 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 69% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 25.65 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 58% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 18.19 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 79% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 13.06 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 71% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 21.02 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 81% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 77.20 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 18% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 53.33 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 11% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 83.18 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 32% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 70.47 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 62% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.80 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 6% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.45 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 7% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.47 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 5% in the World.

2.50. Curacao

The study of indicator: Population, total during - highlights an average of 144151.81. Also for Population, total the region ranks on the first 89% in the World.

2.51. Cayman Islands

The study of indicator: Population, total during - highlights an average of 28099.11. Also for Population, total the region ranks on the first 94% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 1057.941*Year-2075087.893. From this equation we can note that, every year, the indicator grow with 1057.941.

The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2011-2015 reveals an average of 69.06Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 8% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2011-2015 highlights an average of 72.98Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 12% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2011-2015 highlights an average of 70.78Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 4% in the World.

2.52. Cyprus

The study of indicator: Population, total during - highlights an average of 808045.11. Also for Population, total the region ranks on the first 78% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 11567.469*Year-22188083.172. From this equation we can note that, every year, the indicator grow with 11567.469.

The indicator: Labor force, total during 1990-2016 highlights an average of 486969.93. Also for Labor force, total the region ranks on the first 86% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 11416.383*Year-22380046.013. From this equation we can note that, every year, the indicator grow with 11416.383.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 42.20 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.329*Year-616.281. From this equation we can note that, every year, the indicator grow with 0.329.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2000-2016 reveals an average of 83.96Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 10% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2000-2016 highlights an average of 89.02Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 33% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2000-2016 highlights an average of 86.36Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 16% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 4.95 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 83% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 4.02 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.243*Year+491.576. From this equation we can note that, every year, the indicator decreases with 0.243.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 5.65 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 81% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 22.87 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 68% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.415*Year+854.133. From this equation we can note that, every year, the indicator decreases with 0.415.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.48 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 73% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.447*Year+906.861. From this equation we can note that, every year, the indicator decreases with 0.447.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 30.81 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 57% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 84.50 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.693*Year-1303.223. From this equation we can note that, every year, the indicator grow with 0.693.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 63.52 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 8% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 83.68 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.547*Year-1012.118. From this equation we can note that, every year, the indicator grow with 0.547.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 72.48 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.554*Year-1037.904. From this equation we can note that, every year, the indicator grow with 0.554.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.12 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 83% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.57 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 76% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.82 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 87% in the World.

2.53. Czech Republic

The study of indicator: Population, total during - highlights an average of 10184891.79. Also for Population, total the region ranks on the first 50% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 5175580.37. Also for Labor force, total the region ranks on the first 51% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.14 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 46% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1998-2016 reveals an average of 72.48Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 83% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1998-2016 highlights an average of 81.19Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 58% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1998-2016 highlights an average of 77.17Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 72% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 4.30 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 91% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.146*Year+297.462. From this equation we can note that, every year, the indicator decreases with 0.146.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 3.05 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 87% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 5.27 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 91% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.166*Year+338.569. From this equation we can note that, every year, the indicator decreases with 0.166.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 40.50 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 3% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 27.76 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 7% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 50.30 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 1% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 69.19 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.632*Year-1196.133. From this equation we can note that, every year, the indicator grow with 0.632.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 44.45 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.332*Year-621.461. From this equation we can note that, every year, the indicator grow with 0.332.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 89.32 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 23% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 80.43 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 24% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.95 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 17% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.14 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 18% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.01 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 14% in the World.

2.54. Germany

The study of indicator: Population, total during - highlights an average of 79381016.42. Also for Population, total the region ranks on the first 22% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 40951859.19. Also for Labor force, total the region ranks on the first 25% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 138511.185*Year-236486044.333. From this equation we can note that, every year, the indicator grow with 138511.185.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.27 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.193*Year-341.422. From this equation we can note that, every year, the indicator grow with 0.193.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 72.04Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 65% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 73.40Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 90% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 72.93Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 86% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 2.47 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 96% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.107*Year+216.104. From this equation we can note that, every year, the indicator decreases with 0.107.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.04 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 89% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 2.81 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 96% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.092*Year+187.472. From this equation we can note that, every year, the indicator decreases with 0.092.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 32.49 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 11% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 17.74 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 31% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 44.10 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 6% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 80.22 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 25% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 53.08 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.632*Year-1212.241. From this equation we can note that, every year, the indicator grow with 0.632.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 91.63 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 8% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 86.61 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 9% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.72 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 17% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.96 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 12% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.56 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 23% in the World.

2.55. Djibouti

The study of indicator: Population, total during - highlights an average of 495348.63. Also for Population, total the region ranks on the first 79% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 16855.530*Year-33013445.931. From this equation we can note that, every year, the indicator grow with 16855.530.

The indicator: Labor force, total during 1990-2016 highlights an average of 283451.74. Also for Labor force, total the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 6796.225*Year-13329386.262. From this equation we can note that, every year, the indicator grow with 6796.225.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.51 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 59% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.226*Year-414.260. From this equation we can note that, every year, the indicator grow with 0.226.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 25.69 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 46% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 18.80 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 51% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 28.95 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 43% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.75 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 26% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 31.41 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 4% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 17.21 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 69% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 52.56 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 49.77 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 66% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 53.84 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 41% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 29.22 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 77% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 72.50 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 31% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.25 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.020*Year+46.457. From this equation we can note that, every year, the indicator decreases with 0.020.The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.56 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 48% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: -0.060*Year+127.840. From this equation we can note that, every year, the indicator decreases with 0.060.The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.63 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 40% in the World.

2.56. Dominica

The study of indicator: Population, total during - highlights an average of 70709.35. Also for Population, total the region ranks on the first 93% in the World.

2.57. Denmark

The study of indicator: Population, total during - highlights an average of 5172882.46. Also for Population, total the region ranks on the first 60% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 16481.149*Year-27591641.270. From this equation we can note that, every year, the indicator grow with 16481.149.

The indicator: Labor force, total during 1990-2016 highlights an average of 2892318.26. Also for Labor force, total the region ranks on the first 65% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.63 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 20% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 80.79Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 56% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.398*Year+877.767. From this equation we can note that, every year, the indicator decreases with 0.398.The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 83.36Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.511*Year+1106.946. From this equation we can note that, every year, the indicator decreases with 0.511.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 82.04Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 66% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.462*Year+1007.888. From this equation we can note that, every year, the indicator decreases with 0.462.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 3.36 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 91% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 1.64 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 91% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 4.88 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 88% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 23.52 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 56% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.375*Year+775.743. From this equation we can note that, every year, the indicator decreases with 0.375.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.46 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 54% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.310*Year+633.508. From this equation we can note that, every year, the indicator decreases with 0.310.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 33.12 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 37% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 85.92 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.387*Year-688.764. From this equation we can note that, every year, the indicator grow with 0.387.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 62.01 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.537*Year-1014.471. From this equation we can note that, every year, the indicator grow with 0.537.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 94.16 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 5% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 87.60 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 6% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.16 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 43% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.64 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 42% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.76 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 45% in the World.

2.58. Dominican Republic

The study of indicator: Population, total during - highlights an average of 6931871.11. Also for Population, total the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 133977.312*Year-259415025.211. From this equation we can note that, every year, the indicator grow with 133977.312.

The indicator: Labor force, total during 1990-2016 highlights an average of 3846032.15. Also for Labor force, total the region ranks on the first 54% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 82560.660*Year-161522969.734. From this equation we can note that, every year, the indicator grow with 82560.660.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 37.51 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 63% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.267*Year-496.430. From this equation we can note that, every year, the indicator grow with 0.267.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2005-2016 reveals an average of 69.78Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 78% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2005-2016 highlights an average of 82.25Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 69% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2005-2016 highlights an average of 75.03Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 80% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 16.41 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 63% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.67 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 80% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 23.20 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 52% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.87 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 67% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 15.40 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 57% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.609*Year+1234.826. From this equation we can note that, every year, the indicator decreases with 0.609.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 25.22 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 67% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 81.94 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 16% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.665*Year-1250.505. From this equation we can note that, every year, the indicator grow with 0.665.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 51.60 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.571*Year-1092.214. From this equation we can note that, every year, the indicator grow with 0.571.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 67.30 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 42% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 47.72 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 74% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 13.66 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 86% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 21.23 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 90% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.09 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 73% in the World.

2.59. Algeria

The study of indicator: Population, total during - highlights an average of 24537494.05. Also for Population, total the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 538183.145*Year-1045370598.844. From this equation we can note that, every year, the indicator grow with 538183.145.

The indicator: Labor force, total during 1990-2016 highlights an average of 9529918.11. Also for Labor force, total the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 216595.547*Year-424310962.547. From this equation we can note that, every year, the indicator grow with 216595.547.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 15.08 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 97% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 17.57 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 68% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 9.00 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 71% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 18.68 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 68% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 28.14 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 4% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 32.33 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 2% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 27.75 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 13% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 54.29 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 58.67 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 53% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 53.56 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 40% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 61.09 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 50% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 58.27 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 66% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 18.72 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 78% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 35.77 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 84% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 15.92 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 78% in the World.

2.60. East Asia & Pacific (Excluding High Income)

The study of indicator: Population, total during - highlights an average of 1519966807.35. Also for Population, total the region ranks on the first 4% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 21749401.480*Year-41717843335.734. From this equation we can note that, every year, the indicator grow with 21749401.480.

The indicator: Labor force, total during 1990-2016 highlights an average of 1014425985.11. Also for Labor force, total the region ranks on the first 5% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 11044154.810*Year-21107016098.365. From this equation we can note that, every year, the indicator grow with 11044154.810.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.87 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 51% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.049*Year+141.615. From this equation we can note that, every year, the indicator decreases with 0.049.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 43.66 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 35% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -1.046*Year+2138.621. From this equation we can note that, every year, the indicator decreases with 1.046.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 46.30 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 34% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.938*Year+1925.346. From this equation we can note that, every year, the indicator decreases with 0.938.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 41.58 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 41% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -1.128*Year+2301.078. From this equation we can note that, every year, the indicator decreases with 1.128.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 20.52 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 33% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 16.96 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 21% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 23.31 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 39% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 35.82 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.851*Year-1669.813. From this equation we can note that, every year, the indicator grow with 0.851.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 36.73 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 69% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 1.011*Year-1989.442. From this equation we can note that, every year, the indicator grow with 1.011.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 35.11 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 66% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.729*Year-1424.562. From this equation we can note that, every year, the indicator grow with 0.729.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 43.62 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 60% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 1.212*Year-2384.499. From this equation we can note that, every year, the indicator grow with 1.212.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 47.76 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 58% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1.197*Year-2349.759. From this equation we can note that, every year, the indicator grow with 1.197.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.48 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 20% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.08 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 15% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.79 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 26% in the World.

2.61. Early-demographic Dividend

The study of indicator: Population, total during - highlights an average of 1982604820.94. Also for Population, total the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 40616830.973*Year-78763655153.012. From this equation we can note that, every year, the indicator grow with 40616830.973.

The indicator: Labor force, total during 1990-2016 highlights an average of 1015198087.96. Also for Labor force, total the region ranks on the first 3% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 21110769.626*Year-41269673473.663. From this equation we can note that, every year, the indicator grow with 21110769.626.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 31.03 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 87% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2010-2012 reveals an average of 34.14Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 97% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2010-2012 highlights an average of 57.43Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 34% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2010-2012 highlights an average of 47.33Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 88% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 45.26 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.607*Year+1260.414. From this equation we can note that, every year, the indicator decreases with 0.607.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 51.84 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.659*Year+1372.989. From this equation we can note that, every year, the indicator decreases with 0.659.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 42.24 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.582*Year+1208.640. From this equation we can note that, every year, the indicator decreases with 0.582.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 18.90 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 39% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.250*Year-482.749. From this equation we can note that, every year, the indicator grow with 0.250.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 13.37 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 30% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 21.43 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.311*Year-602.238. From this equation we can note that, every year, the indicator grow with 0.311.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 35.84 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 4% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.357*Year-678.497. From this equation we can note that, every year, the indicator grow with 0.357.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 34.80 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 75% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.548*Year-1063.166. From this equation we can note that, every year, the indicator grow with 0.548.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 36.33 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 74% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.271*Year-506.428. From this equation we can note that, every year, the indicator grow with 0.271.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 27.10 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 75% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.685*Year-1345.142. From this equation we can note that, every year, the indicator grow with 0.685.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 32.98 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 82% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.97 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 35% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.39 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 50% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.31 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 29% in the World.

2.62. East Asia & Pacific

The study of indicator: Population, total during - highlights an average of 1727211318.02. Also for Population, total the region ranks on the first 4% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 23511036.952*Year-45012730143.531. From this equation we can note that, every year, the indicator grow with 23511036.952.

The indicator: Labor force, total during 1990-2016 highlights an average of 1133971863.59. Also for Labor force, total the region ranks on the first 4% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 11815251.410*Year-22531976711.151. From this equation we can note that, every year, the indicator grow with 11815251.410.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.60 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 51% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 39.64 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 42% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.934*Year+1910.796. From this equation we can note that, every year, the indicator decreases with 0.934.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 42.27 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.863*Year+1771.101. From this equation we can note that, every year, the indicator decreases with 0.863.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 37.59 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 45% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.988*Year+2016.420. From this equation we can note that, every year, the indicator decreases with 0.988.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.44 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 31% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 17.19 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 23% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.77 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 35% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 38.91 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.805*Year-1574.547. From this equation we can note that, every year, the indicator grow with 0.805.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 40.54 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.982*Year-1926.096. From this equation we can note that, every year, the indicator grow with 0.982.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.64 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 60% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.670*Year-1305.659. From this equation we can note that, every year, the indicator grow with 0.670.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 47.24 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 1.143*Year-2242.371. From this equation we can note that, every year, the indicator grow with 1.143.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 51.09 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 54% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1.063*Year-2079.132. From this equation we can note that, every year, the indicator grow with 1.063.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.44 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 19% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.06 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 13% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.74 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 25% in the World.

2.63. Europe & Central Asia (Excluding High Income)

The study of indicator: Population, total during - highlights an average of 365566552.53. Also for Population, total the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 2336748.650*Year-4279889763.261. From this equation we can note that, every year, the indicator grow with 2336748.650.

The indicator: Labor force, total during 1990-2016 highlights an average of 183416559.78. Also for Labor force, total the region ranks on the first 15% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.92 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 45% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2011-2015 reveals an average of 67.87Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 87% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2011-2015 highlights an average of 77.41Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.576*Year-1081.136. From this equation we can note that, every year, the indicator grow with 0.576.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2011-2015 highlights an average of 73.26Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 79% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 21.93 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 58% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 21.79 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 53% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 22.04 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 61% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 26.90 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 19% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 20.86 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.337*Year+695.704. From this equation we can note that, every year, the indicator decreases with 0.337.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 31.81 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 20% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 51.18 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.539*Year-1029.628. From this equation we can note that, every year, the indicator grow with 0.539.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 57.34 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.736*Year-1416.680. From this equation we can note that, every year, the indicator grow with 0.736.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 46.15 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.379*Year-712.862. From this equation we can note that, every year, the indicator grow with 0.379.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 77.34 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 31% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 75.54 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 27% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.75 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 59% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.49 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 52% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.96 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 65% in the World.

2.64. Europe & Central Asia

The study of indicator: Population, total during - highlights an average of 813548708.54. Also for Population, total the region ranks on the first 10% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 4038345.971*Year-7214683080.826. From this equation we can note that, every year, the indicator grow with 4038345.971.

The indicator: Labor force, total during 1990-2016 highlights an average of 407710357.04. Also for Labor force, total the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 2111228.643*Year-3821080615.829. From this equation we can note that, every year, the indicator grow with 2111228.643.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.39 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 39% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.083*Year-122.219. From this equation we can note that, every year, the indicator grow with 0.083.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2016 reveals an average of 74.56Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 49% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2016 highlights an average of 79.45Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 63% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2016 highlights an average of 77.06Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 56% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 12.78 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.290*Year+594.749. From this equation we can note that, every year, the indicator decreases with 0.290.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 12.33 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.310*Year+633.678. From this equation we can note that, every year, the indicator decreases with 0.310.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 13.15 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.272*Year+558.337. From this equation we can note that, every year, the indicator decreases with 0.272.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 27.51 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 24% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.282*Year+593.121. From this equation we can note that, every year, the indicator decreases with 0.282.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 17.73 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.374*Year+767.856. From this equation we can note that, every year, the indicator decreases with 0.374.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 35.28 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 17% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 69.94 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 38% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.685*Year-1302.177. From this equation we can note that, every year, the indicator grow with 0.685.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 51.57 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 0.445*Year-840.915. From this equation we can note that, every year, the indicator grow with 0.445.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 82.73 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 26% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 78.07 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 24% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 9.07 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 62% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 9.40 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 57% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.82 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 67% in the World.

2.65. Ecuador

The study of indicator: Population, total during - highlights an average of 9994361.07. Also for Population, total the region ranks on the first 43% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 217306.259*Year-422010482.356. From this equation we can note that, every year, the indicator grow with 217306.259.

The indicator: Labor force, total during 1990-2016 highlights an average of 5932980.11. Also for Labor force, total the region ranks on the first 46% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 141247.802*Year-276986366.468. From this equation we can note that, every year, the indicator grow with 141247.802.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.71 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 65% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2016 reveals an average of 74.31Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 40% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2016 highlights an average of 84.51Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 36% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2016 highlights an average of 79.07Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 40% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 14.87 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 44% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 9.96 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 49% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 17.70 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 40% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.32 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 56% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.92 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 47% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 26.15 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 57% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 63.82 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 77.11 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 48% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 56.15 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 57% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 47.57 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 71% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 58.78 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 60% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.59 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 23% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.64 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 32% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.73 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 20% in the World.

2.66. Egypt, Arab Rep.

The study of indicator: Population, total during - highlights an average of 56355838.07. Also for Population, total the region ranks on the first 22% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 1214341.299*Year-2357754664.990. From this equation we can note that, every year, the indicator grow with 1214341.299.

The indicator: Labor force, total during 1990-2016 highlights an average of 22907131.00. Also for Labor force, total the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 625799.799*Year-1230569865.465. From this equation we can note that, every year, the indicator grow with 625799.799.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 22.52 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 92% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2008-2016 reveals an average of 55.39Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 90% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2008-2016 highlights an average of 77.54Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 20% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2008-2016 highlights an average of 68.03Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 60% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 30.53 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 43% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 40.52 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 29% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 28.14 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 48% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 22.78 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 21% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 7.21 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 81% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 26.50 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 29% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 46.69 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 52.28 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 63% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 45.37 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 52% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 53.80 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 65% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 61.08 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 45% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.32 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 82% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 23.33 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 93% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.54 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 68% in the World.

2.67. Euro area

The study of indicator: Population, total during - highlights an average of 308458890.60. Also for Population, total the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 1234833.625*Year-2146390356.870. From this equation we can note that, every year, the indicator grow with 1234833.625.

The indicator: Labor force, total during 1990-2016 highlights an average of 152333629.56. Also for Labor force, total the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 1071021.018*Year-1992921470.129. From this equation we can note that, every year, the indicator grow with 1071021.018.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.22 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 34% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.229*Year-415.236. From this equation we can note that, every year, the indicator grow with 0.229.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 76.94Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 50% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 80.73Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 73% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.344*Year+770.121. From this equation we can note that, every year, the indicator decreases with 0.344.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 78.95Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 69% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.232*Year+544.371. From this equation we can note that, every year, the indicator decreases with 0.232.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 4.88 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.169*Year+342.819. From this equation we can note that, every year, the indicator decreases with 0.169.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 3.94 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.186*Year+377.190. From this equation we can note that, every year, the indicator decreases with 0.186.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 5.62 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 86% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.147*Year+300.045. From this equation we can note that, every year, the indicator decreases with 0.147.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 28.54 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.437*Year+903.836. From this equation we can note that, every year, the indicator decreases with 0.437.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 15.37 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.404*Year+825.279. From this equation we can note that, every year, the indicator decreases with 0.404.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 38.39 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.347*Year+734.456. From this equation we can note that, every year, the indicator decreases with 0.347.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 80.70 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 22% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.591*Year-1104.065. From this equation we can note that, every year, the indicator grow with 0.591.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 55.99 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 21% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.495*Year-934.746. From this equation we can note that, every year, the indicator grow with 0.495.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 87.05 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 19% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.185*Year-283.964. From this equation we can note that, every year, the indicator grow with 0.185.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 80.12 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 20% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.00 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 71% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 11.31 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 67% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.04 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 77% in the World.

2.68. Eritrea

The study of indicator: Population, total during - highlights an average of 2743227.94. Also for Population, total the region ranks on the first 64% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 58324.653*Year-113060370.744. From this equation we can note that, every year, the indicator grow with 58324.653.

The indicator: Labor force, total during 1990-2011 highlights an average of 1640308.59. Also for Labor force, total the region ranks on the first 71% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2011 highlights an average of 46.24 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 24% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 60.15 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 14% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 73.08 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 12% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 49.04 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 20% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 6.35 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 90% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 0.95 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 98% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 11.00 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 86% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 33.51 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 6% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 25.99 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 84% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 39.97 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 72% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 76.06 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 35% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 80.66 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 22% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.67 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 49% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.28 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 48% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.15 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 47% in the World.

2.69. Spain

The study of indicator: Population, total during - highlights an average of 38823879.77. Also for Population, total the region ranks on the first 28% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 284882.136*Year-527521806.569. From this equation we can note that, every year, the indicator grow with 284882.136.

The indicator: Labor force, total during 1990-2016 highlights an average of 19880755.67. Also for Labor force, total the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 371374.548*Year-723982464.437. From this equation we can note that, every year, the indicator grow with 371374.548.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 40.80 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.452*Year-864.055. From this equation we can note that, every year, the indicator grow with 0.452.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 79.18Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 16% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 83.86Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 60% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 81.58Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 39% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 6.28 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 83% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.272*Year+551.648. From this equation we can note that, every year, the indicator decreases with 0.272.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 4.37 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 83% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.270*Year+544.664. From this equation we can note that, every year, the indicator decreases with 0.270.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 7.54 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 81% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 27.58 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 54% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.27 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 59% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.335*Year+684.349. From this equation we can note that, every year, the indicator decreases with 0.335.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 37.31 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 36% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 83.38 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 14% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.605*Year-1129.264. From this equation we can note that, every year, the indicator grow with 0.605.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 55.15 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 14% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 83.28 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 22% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 77.47 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 25% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 17.33 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 94% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 21.38 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 90% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 14.75 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 93% in the World.

2.70. Estonia

The study of indicator: Population, total during - highlights an average of 1399332.96. Also for Population, total the region ranks on the first 77% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 695950.67. Also for Labor force, total the region ranks on the first 84% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 48.42 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 15% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1997-2016 reveals an average of 77.20Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 35% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1997-2016 highlights an average of 86.35Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 28% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1997-2016 highlights an average of 80.56Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 30% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 7.48 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 84% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 5.11 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 81% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 9.74 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 82% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 32.85 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 10% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 22.80 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 15% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 42.52 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 4% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 72.07 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 32% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 47.73 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 39% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 94.62 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 7% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 88.93 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 7% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 9.00 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 52% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.15 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 32% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.78 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 61% in the World.

2.71. Ethiopia

The study of indicator: Population, total during - highlights an average of 51869601.09. Also for Population, total the region ranks on the first 21% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 1416337.725*Year-2763809796.947. From this equation we can note that, every year, the indicator grow with 1416337.725.

The indicator: Labor force, total during 1990-2016 highlights an average of 33184559.15. Also for Labor force, total the region ranks on the first 23% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 1139833.137*Year-2249901213.766. From this equation we can note that, every year, the indicator grow with 1139833.137.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.57 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 21% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2012 reveals an average of 89.20Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 0% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2012 highlights an average of 94.28Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 2% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2012 highlights an average of 92.55Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 0% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 55.61 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 5% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 50.38 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 17% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 59.87 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 1% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 11.72 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 90% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.95 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 56% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 12.32 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 96% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 32.68 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 19% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 38.67 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 84% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 27.80 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 100% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 11.22 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 68% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 14.85 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 68% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.64 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 29% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.62 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 54% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.12 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 9% in the World.

2.72. European Union

The study of indicator: Population, total during - highlights an average of 470535188.72. Also for Population, total the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 1630945.777*Year-2771785015.112. From this equation we can note that, every year, the indicator grow with 1630945.777.

The indicator: Labor force, total during 1990-2016 highlights an average of 233675223.11. Also for Labor force, total the region ranks on the first 14% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 1169928.426*Year-2109691414.426. From this equation we can note that, every year, the indicator grow with 1169928.426.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.02 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 34% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.153*Year-263.121. From this equation we can note that, every year, the indicator grow with 0.153.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1997-2016 reveals an average of 78.03Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 39% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1997-2016 highlights an average of 81.26Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 66% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1997-2016 highlights an average of 79.57Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 58% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 6.86 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 80% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.234*Year+476.144. From this equation we can note that, every year, the indicator decreases with 0.234.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 6.16 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 77% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.268*Year+543.342. From this equation we can note that, every year, the indicator decreases with 0.268.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 7.42 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.203*Year+414.799. From this equation we can note that, every year, the indicator decreases with 0.203.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 28.36 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.402*Year+833.305. From this equation we can note that, every year, the indicator decreases with 0.402.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 15.85 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 38% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.403*Year+823.590. From this equation we can note that, every year, the indicator decreases with 0.403.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 38.09 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.326*Year+690.892. From this equation we can note that, every year, the indicator decreases with 0.326.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 77.99 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.672*Year-1267.604. From this equation we can note that, every year, the indicator grow with 0.672.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 54.49 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 24% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.529*Year-1006.084. From this equation we can note that, every year, the indicator grow with 0.529.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 85.85 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 21% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.231*Year-376.648. From this equation we can note that, every year, the indicator grow with 0.231.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 79.32 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 21% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 9.46 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 65% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.22 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 61% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.88 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 67% in the World.

2.73. Fragile and Conflict Affected Situations

The study of indicator: Population, total during - highlights an average of 272629039.70. Also for Population, total the region ranks on the first 14% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 6757769.148*Year-13161816026.349. From this equation we can note that, every year, the indicator grow with 6757769.148.

The indicator: Labor force, total during 1990-2016 highlights an average of 133714051.96. Also for Labor force, total the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 3376223.188*Year-6628860993.670. From this equation we can note that, every year, the indicator grow with 3376223.188.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.00 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 73% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 55.18 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 20% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.395*Year+845.845. From this equation we can note that, every year, the indicator decreases with 0.395.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 66.25 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 18% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.407*Year+881.102. From this equation we can note that, every year, the indicator decreases with 0.407.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 47.74 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 24% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.388*Year+824.214. From this equation we can note that, every year, the indicator decreases with 0.388.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 10.50 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 81% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.102*Year-193.174. From this equation we can note that, every year, the indicator grow with 0.102.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.53 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 75% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 13.15 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 81% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.154*Year-296.381. From this equation we can note that, every year, the indicator grow with 0.154.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 34.32 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 5% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.293*Year-553.181. From this equation we can note that, every year, the indicator grow with 0.293.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 27.22 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.383*Year-740.229. From this equation we can note that, every year, the indicator grow with 0.383.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 39.11 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 69% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.233*Year-427.400. From this equation we can note that, every year, the indicator grow with 0.233.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 18.04 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 85% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 33.02 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 82% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.15 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 66% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 9.33 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 66% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.31 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 64% in the World.

2.74. Finland

The study of indicator: Population, total during - highlights an average of 4957158.44. Also for Population, total the region ranks on the first 61% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 18404.357*Year-31630702.917. From this equation we can note that, every year, the indicator grow with 18404.357.

The indicator: Labor force, total during 1990-2016 highlights an average of 2612571.48. Also for Labor force, total the region ranks on the first 68% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 47.75 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 17% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1995-2016 reveals an average of 78.49Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 69% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1995-2016 highlights an average of 79.97Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 88% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1995-2016 highlights an average of 79.15Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 83% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.438*Year+957.905. From this equation we can note that, every year, the indicator decreases with 0.438.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 5.84 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 82% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 3.78 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 81% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: -0.181*Year+365.434. From this equation we can note that, every year, the indicator decreases with 0.181.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 7.73 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 80% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 25.59 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 38% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.22 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.301*Year+614.776. From this equation we can note that, every year, the indicator decreases with 0.301.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 37.85 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 13% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 84.00 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 16% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.484*Year-885.214. From this equation we can note that, every year, the indicator grow with 0.484.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 54.43 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.409*Year-765.463. From this equation we can note that, every year, the indicator grow with 0.409.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 90.30 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 13% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 81.06 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 19% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.48 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 67% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.02 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 58% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 10.88 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 73% in the World.

2.75. Fiji

The study of indicator: Population, total during - highlights an average of 689373.23. Also for Population, total the region ranks on the first 79% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 8820.168*Year-16845120.897. From this equation we can note that, every year, the indicator grow with 8820.168.

The indicator: Labor force, total during 1990-2016 highlights an average of 318696.52. Also for Labor force, total the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 3909.973*Year-7512979.677. From this equation we can note that, every year, the indicator grow with 3909.973.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 33.48 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.068*Year-103.618. From this equation we can note that, every year, the indicator grow with 0.068.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 24.65 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 48% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.242*Year+508.846. From this equation we can note that, every year, the indicator decreases with 0.242.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 25.22 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 47% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 24.38 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.296*Year+617.759. From this equation we can note that, every year, the indicator decreases with 0.296.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 3.03 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 99% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 1.80 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 94% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 3.60 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 99% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 72.98 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 40% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 72.01 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 3% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.306*Year-540.409. From this equation we can note that, every year, the indicator grow with 0.306.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 56.10 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 56% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 59.63 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 56% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.45 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 64% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.41 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 72% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.00 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 56% in the World.

2.76. France

The study of indicator: Population, total during - highlights an average of 57638192.00. Also for Population, total the region ranks on the first 24% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 328301.665*Year-595025518.713. From this equation we can note that, every year, the indicator grow with 328301.665.

The indicator: Labor force, total during 1990-2016 highlights an average of 28249883.70. Also for Labor force, total the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 195343.627*Year-363023401.146. From this equation we can note that, every year, the indicator grow with 195343.627.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.39 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 24% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.148*Year-251.996. From this equation we can note that, every year, the indicator grow with 0.148.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1998-2016 reveals an average of 76.05Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 52% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1998-2016 highlights an average of 80.02Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 69% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1998-2016 highlights an average of 77.91Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 65% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 3.93 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 90% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.123*Year+250.999. From this equation we can note that, every year, the indicator decreases with 0.123.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.71 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 86% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.120*Year+243.950. From this equation we can note that, every year, the indicator decreases with 0.120.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 4.98 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.116*Year+237.040. From this equation we can note that, every year, the indicator decreases with 0.116.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 24.47 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 47% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.322*Year+669.771. From this equation we can note that, every year, the indicator decreases with 0.322.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.56 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 50% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.271*Year+555.797. From this equation we can note that, every year, the indicator decreases with 0.271.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 34.36 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.268*Year+570.820. From this equation we can note that, every year, the indicator decreases with 0.268.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 84.75 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.392*Year-701.311. From this equation we can note that, every year, the indicator grow with 0.392.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 60.67 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.381*Year-702.301. From this equation we can note that, every year, the indicator grow with 0.381.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 91.20 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 10% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 85.06 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 10% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.21 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 71% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 11.30 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 63% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.33 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 79% in the World.

2.77. Faroe Islands

The study of indicator: Population, total during - highlights an average of 44239.67. Also for Population, total the region ranks on the first 96% in the World.

2.78. Micronesia, Fed. Sts.

The study of indicator: Population, total during - highlights an average of 84855.93. Also for Population, total the region ranks on the first 91% in the World.

2.79. Gabon

The study of indicator: Population, total during - highlights an average of 1006928.44. Also for Population, total the region ranks on the first 74% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 25070.025*Year-48832281.687. From this equation we can note that, every year, the indicator grow with 25070.025.

The indicator: Labor force, total during 1990-2016 highlights an average of 410115.04. Also for Labor force, total the region ranks on the first 86% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 14791.535*Year-29217329.164. From this equation we can note that, every year, the indicator grow with 14791.535.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.77 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 69% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 26.38 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 57% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -1.059*Year+2148.036. From this equation we can note that, every year, the indicator decreases with 1.059.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 40.08 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 44% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -1.359*Year+2762.242. From this equation we can note that, every year, the indicator decreases with 1.359.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 15.75 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 72% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.660*Year+1337.512. From this equation we can note that, every year, the indicator decreases with 0.660.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 14.55 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 57% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.415*Year-816.033. From this equation we can note that, every year, the indicator grow with 0.415.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 4.02 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 81% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 22.36 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 41% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.473*Year-925.829. From this equation we can note that, every year, the indicator grow with 0.473.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 55.90 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1.215*Year-2377.818. From this equation we can note that, every year, the indicator grow with 1.215.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 61.90 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 20% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 45.50 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 55% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 61.34 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 39% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 18.38 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 93% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 20.91 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 92% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 16.67 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 92% in the World.

2.80. United Kingdom

The study of indicator: Population, total during - highlights an average of 57894885.40. Also for Population, total the region ranks on the first 25% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 30424224.26. Also for Labor force, total the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 212750.499*Year-395715026.018. From this equation we can note that, every year, the indicator grow with 212750.499.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.25 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 28% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.116*Year-186.932. From this equation we can note that, every year, the indicator grow with 0.116.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 81.34Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 22% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 86.98Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 19% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 84.24Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 15% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 1.51 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 97% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.82 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 94% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 2.09 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 96% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 23.52 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 58% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.499*Year+1024.036. From this equation we can note that, every year, the indicator decreases with 0.499.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.85 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 64% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.381*Year+773.824. From this equation we can note that, every year, the indicator decreases with 0.381.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 34.21 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 39% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: -0.570*Year+1175.621. From this equation we can note that, every year, the indicator decreases with 0.570.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 88.34 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 8% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.402*Year-716.623. From this equation we can note that, every year, the indicator grow with 0.402.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 63.69 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 7% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.626*Year-1191.423. From this equation we can note that, every year, the indicator grow with 0.626.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 91.50 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 18% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 82.20 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 23% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.74 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 24% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 5.81 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 18% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.49 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 30% in the World.

2.81. Georgia

The study of indicator: Population, total during - highlights an average of 4278878.95. Also for Population, total the region ranks on the first 67% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 2214451.78. Also for Labor force, total the region ranks on the first 73% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.74 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 36% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 50.95 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 23% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 53.41 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 25% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 48.73 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 24% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 10.20 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 82% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 4.63 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 87% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 15.15 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 74% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 38.87 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 41.94 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 69% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 36.12 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 77% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 40.08 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 73% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 39.82 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 79% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 13.25 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 80% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 12.00 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 66% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 14.32 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 88% in the World.

2.82. Ghana

The study of indicator: Population, total during - highlights an average of 15092693.46. Also for Population, total the region ranks on the first 36% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 379324.388*Year-739004190.008. From this equation we can note that, every year, the indicator grow with 379324.388.

The indicator: Labor force, total during 1990-2016 highlights an average of 9342164.78. Also for Labor force, total the region ranks on the first 37% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 274727.221*Year-540936458.888. From this equation we can note that, every year, the indicator grow with 274727.221.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 48.87 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 7% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.101*Year-152.438. From this equation we can note that, every year, the indicator grow with 0.101.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 55.65 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 24% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 51.74 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 31% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 59.38 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 20% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 13.29 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 76% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.48 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 45% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 14.11 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 75% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 31.08 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 35.78 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 70% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 26.53 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 81% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 11.06 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 91% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 30.42 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 88% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.48 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 32% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.03 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 29% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.96 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 34% in the World.

2.83. Gibraltar

The study of indicator: Population, total during - highlights an average of 29995.02. Also for Population, total the region ranks on the first 98% in the World.

2.84. Guinea

The study of indicator: Population, total during - highlights an average of 6757750.93. Also for Population, total the region ranks on the first 45% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 161934.423*Year-315167881.731. From this equation we can note that, every year, the indicator grow with 161934.423.

The indicator: Labor force, total during 1990-2016 highlights an average of 3421962.30. Also for Labor force, total the region ranks on the first 58% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 81469.187*Year-159760818.891. From this equation we can note that, every year, the indicator grow with 81469.187.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 48.68 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 10% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 73.47 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 6% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 79.28 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 5% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 68.83 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 7% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 5.93 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 91% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 1.38 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 96% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 9.53 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 87% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 20.60 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 17% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 19.35 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 94% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 21.64 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 94% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 23.65 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 84% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 33.66 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 86% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.27 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 46% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.93 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 46% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.76 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 45% in the World.

2.85. Gambia, The

The study of indicator: Population, total during - highlights an average of 951912.42. Also for Population, total the region ranks on the first 74% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 29377.984*Year-57451520.525. From this equation we can note that, every year, the indicator grow with 29377.984.

The indicator: Labor force, total during 1990-2016 highlights an average of 440807.56. Also for Labor force, total the region ranks on the first 85% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 14363.230*Year-28328741.230. From this equation we can note that, every year, the indicator grow with 14363.230.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 41.72 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 46% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.234*Year-427.778. From this equation we can note that, every year, the indicator grow with 0.234.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 40.91 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 34% in the World. Time regression analysis reveals a correlation coefficient value: -1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: -0.992*Year+2027.695. From this equation we can note that, every year, the indicator decreases with 0.992.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 53.66 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 28% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.893*Year+1843.729. From this equation we can note that, every year, the indicator decreases with 0.893.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 32.09 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -1.106*Year+2248.953. From this equation we can note that, every year, the indicator decreases with 1.106.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 9.06 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 77% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.414*Year-820.696. From this equation we can note that, every year, the indicator grow with 0.414.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 1.78 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.091*Year-179.866. From this equation we can note that, every year, the indicator grow with 0.091.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 14.17 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 65% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.666*Year-1320.200. From this equation we can note that, every year, the indicator grow with 0.666.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 50.01 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.575*Year-1101.953. From this equation we can note that, every year, the indicator grow with 0.575.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 44.55 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 61% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.801*Year-1560.712. From this equation we can note that, every year, the indicator grow with 0.801.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 53.74 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 32% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 13.20 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 92% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 28.88 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 92% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 29.64 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 99% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 38.71 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 100% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 21.67 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 96% in the World.

2.86. Guinea-Bissau

The study of indicator: Population, total during - highlights an average of 1048490.68. Also for Population, total the region ranks on the first 75% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 20425.605*Year-39557612.708. From this equation we can note that, every year, the indicator grow with 20425.605.

The indicator: Labor force, total during 1990-2016 highlights an average of 549601.85. Also for Labor force, total the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 13365.919*Year-26222334.734. From this equation we can note that, every year, the indicator grow with 13365.919.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.60 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 23% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 63.63 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 13% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 76.28 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 9% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 52.90 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 18% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 5.25 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 94% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 0.92 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 97% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 8.91 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 92% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 31.13 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 7% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 22.82 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 87% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 38.18 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 73% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 27.22 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 82% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 48.05 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 74% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.17 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 41% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.68 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 42% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.72 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 41% in the World.

2.87. Equatorial Guinea

The study of indicator: Population, total during - highlights an average of 508606.19. Also for Population, total the region ranks on the first 78% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 264994.63. Also for Labor force, total the region ranks on the first 87% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 11605.002*Year-22979825.262. From this equation we can note that, every year, the indicator grow with 11605.002.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 41.10 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 72% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 34.12 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 54% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 51.67 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 32% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 21.90 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 84% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 14.03 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 59% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 3.90 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 83% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 21.10 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 38% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 44.45 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 56% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 57.00 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 11% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 60.45 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 33% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 63.33 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 33% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.48 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 43% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.78 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 44% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.30 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 47% in the World.

2.88. Greece

The study of indicator: Population, total during - highlights an average of 9947039.07. Also for Population, total the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 54959.325*Year-99312098.630. From this equation we can note that, every year, the indicator grow with 54959.325.

The indicator: Labor force, total during 1990-2016 highlights an average of 4797745.33. Also for Labor force, total the region ranks on the first 56% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.48 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 47% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.351*Year-662.811. From this equation we can note that, every year, the indicator grow with 0.351.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 78.60Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 43% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 81.22Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 83% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 80.07Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 70% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 15.70 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 64% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 17.33 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 57% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 14.84 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 65% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.25 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 71% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.98 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 65% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.374*Year+761.214. From this equation we can note that, every year, the indicator decreases with 0.374.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 27.49 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 71% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 71.70 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 33% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 1.032*Year-1996.049. From this equation we can note that, every year, the indicator grow with 1.032.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 57.67 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.621*Year-1186.552. From this equation we can note that, every year, the indicator grow with 0.621.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 63.87 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 43% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 57.86 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 52% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.99 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 96% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 17.78 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 96% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.86 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 95% in the World.

2.89. Grenada

The study of indicator: Population, total during - highlights an average of 97899.23. Also for Population, total the region ranks on the first 90% in the World.

2.90. Greenland

The study of indicator: Population, total during - highlights an average of 51225.14. Also for Population, total the region ranks on the first 94% in the World.

2.91. Guatemala

The study of indicator: Population, total during - highlights an average of 9386883.19. Also for Population, total the region ranks on the first 43% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 217630.067*Year-423261689.272. From this equation we can note that, every year, the indicator grow with 217630.067.

The indicator: Labor force, total during 1990-2016 highlights an average of 4663059.00. Also for Labor force, total the region ranks on the first 49% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 137737.053*Year-271224257.164. From this equation we can note that, every year, the indicator grow with 137737.053.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 34.24 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 85% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2011-2016 reveals an average of 75.30Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 62% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2011-2016 highlights an average of 88.55Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 10% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2011-2016 highlights an average of 82.45Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 26% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 32.91 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 33% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 11.62 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 59% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 43.54 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 23% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 23.62 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 59% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 22.68 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 19% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.524*Year+1071.556. From this equation we can note that, every year, the indicator decreases with 0.524.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 23.95 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 71% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 43.49 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 65.71 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 42% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 32.52 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 81% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 44.14 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 65% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 55.92 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 44% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 2.75 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 8% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 3.58 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 12% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 2.35 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 5% in the World.

2.92. Guam

The study of indicator: Population, total during - highlights an average of 122086.00. Also for Population, total the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 1966.326*Year-3786970.793. From this equation we can note that, every year, the indicator grow with 1966.326.

The indicator: Labor force, total during 1990-2016 highlights an average of 74617.19. Also for Labor force, total the region ranks on the first 98% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.94 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 68% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 0.40 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 100% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.015*Year+31.014. From this equation we can note that, every year, the indicator decreases with 0.015.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.48 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 97% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.020*Year+39.801. From this equation we can note that, every year, the indicator decreases with 0.020.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 0.32 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 100% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 12.64 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 77% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.128*Year-243.737. From this equation we can note that, every year, the indicator grow with 0.128.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.47 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 72% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.044*Year-81.133. From this equation we can note that, every year, the indicator grow with 0.044.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 17.02 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 72% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.234*Year-452.173. From this equation we can note that, every year, the indicator grow with 0.234.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 93.05 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 6% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 82.65 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.223*Year+529.931. From this equation we can note that, every year, the indicator decreases with 0.223.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 51.50 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 59% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 51.50 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 62% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.92 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 30% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 9.62 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 29% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.41 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 32% in the World.

2.93. Guyana

The study of indicator: Population, total during - highlights an average of 734438.33. Also for Population, total the region ranks on the first 80% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 283803.37. Also for Labor force, total the region ranks on the first 90% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 32.74 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 84% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 24.60 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.607*Year+1239.924. From this equation we can note that, every year, the indicator decreases with 0.607.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 11.99 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 65% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 30.45 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 46% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.588*Year+1208.371. From this equation we can note that, every year, the indicator decreases with 0.588.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 24.54 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 20% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 15.93 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 45% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 28.62 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 18% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 50.87 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 72.05 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 30% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 40.95 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 69% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 70.13 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 44% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 63.09 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 49% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 11.27 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 79% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 15.26 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 80% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.24 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 76% in the World.

2.94. High Income

The study of indicator: Population, total during - highlights an average of 981846555.33. Also for Population, total the region ranks on the first 7% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 7563285.325*Year-14053964671.398. From this equation we can note that, every year, the indicator grow with 7563285.325.

The indicator: Labor force, total during 1990-2016 highlights an average of 537338816.22. Also for Labor force, total the region ranks on the first 8% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 4808624.165*Year-9094335385.943. From this equation we can note that, every year, the indicator grow with 4808624.165.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 42.97 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 47% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.100*Year-158.208. From this equation we can note that, every year, the indicator grow with 0.100.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 4.49 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.146*Year+297.541. From this equation we can note that, every year, the indicator decreases with 0.146.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 3.52 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.146*Year+296.275. From this equation we can note that, every year, the indicator decreases with 0.146.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 5.22 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 88% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.143*Year+291.778. From this equation we can note that, every year, the indicator decreases with 0.143.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 25.97 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 37% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.364*Year+754.887. From this equation we can note that, every year, the indicator decreases with 0.364.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.31 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 46% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.399*Year+814.446. From this equation we can note that, every year, the indicator decreases with 0.399.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 34.72 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 23% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: -0.298*Year+632.282. From this equation we can note that, every year, the indicator decreases with 0.298.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 82.17 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 20% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.546*Year-1011.246. From this equation we can note that, every year, the indicator grow with 0.546.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 60.06 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.442*Year-825.208. From this equation we can note that, every year, the indicator grow with 0.442.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 86.96 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.219*Year-351.827. From this equation we can note that, every year, the indicator grow with 0.219.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 81.49 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.174*Year-267.576. From this equation we can note that, every year, the indicator grow with 0.174.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.11 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 45% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.50 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 39% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.83 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 48% in the World.

2.95. Hong Kong SAR, China

The study of indicator: Population, total during - highlights an average of 5491928.16. Also for Population, total the region ranks on the first 56% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 78418.230*Year-150403514.056. From this equation we can note that, every year, the indicator grow with 78418.230.

The indicator: Labor force, total during 1990-2016 highlights an average of 3456675.81. Also for Labor force, total the region ranks on the first 61% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 41638.491*Year-79945222.566. From this equation we can note that, every year, the indicator grow with 41638.491.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.16 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 11% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.517*Year-992.255. From this equation we can note that, every year, the indicator grow with 0.517.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2015 reveals an average of 72.77Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 68% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2015 highlights an average of 79.69Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 63% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2015 highlights an average of 76.27Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 65% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 0.32 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 100% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.27 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 100% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 0.40 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 100% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 23.08 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.889*Year+1805.062. From this equation we can note that, every year, the indicator decreases with 0.889.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.08 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 77% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 30.20 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 63% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.686*Year+1404.772. From this equation we can note that, every year, the indicator decreases with 0.686.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 85.65 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 3% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 69.42 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 3% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.709*Year-1351.114. From this equation we can note that, every year, the indicator grow with 0.709.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 94.25 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 4% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 84.90 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 7% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.09 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 11% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 3.43 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 9% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.59 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 18% in the World.

2.96. Honduras

The study of indicator: Population, total during - highlights an average of 5027773.93. Also for Population, total the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 131118.395*Year-255635594.420. From this equation we can note that, every year, the indicator grow with 131118.395.

The indicator: Labor force, total during 1990-2016 highlights an average of 2740556.70. Also for Labor force, total the region ranks on the first 59% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 85379.341*Year-168274262.637. From this equation we can note that, every year, the indicator grow with 85379.341.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 34.34 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 81% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2012-2016 reveals an average of 82.30Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 19% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2012-2016 highlights an average of 88.08Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 8% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2012-2016 highlights an average of 84.90Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 8% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 34.69 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 36% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 7.86 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 65% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 47.39 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 25% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.07 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 40% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 23.07 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 9% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 20.18 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 66% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 44.23 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 69.07 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 46% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 32.43 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 79% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 46.88 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 71% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 47.74 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 71% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.19 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 46% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 5.68 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 63% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.41 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 22% in the World.

2.97. Heavily Indebted Poor Countries (HIPC)

The study of indicator: Population, total during - highlights an average of 377834671.54. Also for Population, total the region ranks on the first 11% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 10050257.756*Year-19602077747.826. From this equation we can note that, every year, the indicator grow with 10050257.756.

The indicator: Labor force, total during 1990-2016 highlights an average of 209657254.22. Also for Labor force, total the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 6224565.457*Year-12258147355.457. From this equation we can note that, every year, the indicator grow with 6224565.457.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.76 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 38% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.052*Year-58.452. From this equation we can note that, every year, the indicator grow with 0.052.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 64.02 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 9% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 67.76 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 13% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 61.04 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 9% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 8.81 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 88% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.14 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 78% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 10.92 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 89% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 27.18 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 10% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 26.10 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 85% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 28.03 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 92% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 13.80 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 87% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 25.26 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 88% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.48 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 43% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.68 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 50% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.50 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 35% in the World.

2.98. Croatia

The study of indicator: Population, total during - highlights an average of 4466205.14. Also for Population, total the region ranks on the first 66% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 1990985.33. Also for Labor force, total the region ranks on the first 75% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.64 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.151*Year-258.257. From this equation we can note that, every year, the indicator grow with 0.151.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2002-2016 reveals an average of 76.39Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 66% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2002-2016 highlights an average of 70.70Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 96% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2002-2016 highlights an average of 73.65Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 89% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 15.12 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 69% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 15.67 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 63% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 14.72 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 70% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 30.01 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 15% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 19.96 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 28% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 38.08 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 9% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 64.38 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 39% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 1.019*Year-1976.385. From this equation we can note that, every year, the indicator grow with 1.019.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 47.22 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 43% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 75.44 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 20% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 75.25 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.490*Year-905.887. From this equation we can note that, every year, the indicator grow with 0.490.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.60 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 84% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 13.70 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 77% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 11.74 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 86% in the World.

2.99. Haiti

The study of indicator: Population, total during - highlights an average of 7001419.65. Also for Population, total the region ranks on the first 48% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 129229.839*Year-249907499.884. From this equation we can note that, every year, the indicator grow with 129229.839.

The indicator: Labor force, total during 1990-2016 highlights an average of 3627435.52. Also for Labor force, total the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 85730.677*Year-168091110.603. From this equation we can note that, every year, the indicator grow with 85730.677.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.67 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 17% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 49.92 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 21% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 35.84 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 33% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 61.68 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 11% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 10.81 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 79% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.68 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 63% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 14.26 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 78% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 39.28 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 4% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 57.48 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 58% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 24.07 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 93% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 10.35 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 97% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 13.89 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 99% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 12.99 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 86% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 15.03 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 80% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 11.20 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 85% in the World.

2.100. Hungary

The study of indicator: Population, total during - highlights an average of 10292310.33. Also for Population, total the region ranks on the first 51% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 4301749.70. Also for Labor force, total the region ranks on the first 57% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 45.17 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 35% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1997-2016 reveals an average of 73.62Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 82% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1997-2016 highlights an average of 78.77Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 78% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1997-2016 highlights an average of 75.96Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 88% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 6.49 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 81% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 3.74 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 80% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 8.78 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 80% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 32.50 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 7% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 22.73 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.387*Year+798.312. From this equation we can note that, every year, the indicator decreases with 0.387.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 40.60 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 6% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 73.53 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 36% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 50.62 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 38% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 89.24 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 9% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 81.87 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.493*Year-906.661. From this equation we can note that, every year, the indicator grow with 0.493.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.47 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 28% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.96 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 24% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.90 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 33% in the World.

2.101. IBRD only

The study of indicator: Population, total during - highlights an average of 3322329675.28. Also for Population, total the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 51634228.727*Year-99326517034.698. From this equation we can note that, every year, the indicator grow with 51634228.727.

The indicator: Labor force, total during 1990-2016 highlights an average of 1914255149.56. Also for Labor force, total the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 25515523.012*Year-49193337442.678. From this equation we can note that, every year, the indicator grow with 25515523.012.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.62 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 81% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 39.78 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 38% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.818*Year+1679.479. From this equation we can note that, every year, the indicator decreases with 0.818.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 42.01 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 39% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.811*Year+1667.073. From this equation we can note that, every year, the indicator decreases with 0.811.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 38.38 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 40% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.821*Year+1683.586. From this equation we can note that, every year, the indicator decreases with 0.821.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.58 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 27% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 16.70 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 22% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.61 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 35% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 38.64 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.631*Year-1226.496. From this equation we can note that, every year, the indicator grow with 0.631.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 41.30 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 65% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.871*Year-1703.058. From this equation we can note that, every year, the indicator grow with 0.871.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.01 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 68% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 0.490*Year-943.906. From this equation we can note that, every year, the indicator grow with 0.490.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 45.37 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.900*Year-1756.916. From this equation we can note that, every year, the indicator grow with 0.900.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 44.79 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.623*Year-1203.491. From this equation we can note that, every year, the indicator grow with 0.623.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.92 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 35% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.18 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 30% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.76 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 38% in the World.

2.102. IDA & IBRD total

The study of indicator: Population, total during - highlights an average of 4182359748.07. Also for Population, total the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 72835783.743*Year-140615178333.221. From this equation we can note that, every year, the indicator grow with 72835783.743.

The indicator: Labor force, total during 1990-2016 highlights an average of 2358134632.30. Also for Labor force, total the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 37450152.921*Year-72654521667.736. From this equation we can note that, every year, the indicator grow with 37450152.921.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.71 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 78% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 43.08 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.698*Year+1440.774. From this equation we can note that, every year, the indicator decreases with 0.698.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 46.39 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 32% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.669*Year+1386.412. From this equation we can note that, every year, the indicator decreases with 0.669.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 40.98 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 35% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: -0.714*Year+1471.785. From this equation we can note that, every year, the indicator decreases with 0.714.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 19.68 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 42% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 15.10 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 30% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 22.57 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 50% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 37.24 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.546*Year-1056.610. From this equation we can note that, every year, the indicator grow with 0.546.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 38.51 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.731*Year-1425.432. From this equation we can note that, every year, the indicator grow with 0.731.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 36.44 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 0.432*Year-829.784. From this equation we can note that, every year, the indicator grow with 0.432.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 40.40 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 67% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.767*Year-1496.637. From this equation we can note that, every year, the indicator grow with 0.767.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 42.63 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 72% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.589*Year-1138.037. From this equation we can note that, every year, the indicator grow with 0.589.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.94 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 36% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.39 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 34% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.65 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 37% in the World.

2.103. IDA total

The study of indicator: Population, total during - highlights an average of 860030072.79. Also for Population, total the region ranks on the first 6% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 21201555.016*Year-41288661298.523. From this equation we can note that, every year, the indicator grow with 21201555.016.

The indicator: Labor force, total during 1990-2016 highlights an average of 443879482.70. Also for Labor force, total the region ranks on the first 7% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 11934629.905*Year-23461184217.757. From this equation we can note that, every year, the indicator grow with 11934629.905.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.97 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 68% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.109*Year-179.574. From this equation we can note that, every year, the indicator grow with 0.109.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 56.81 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 19% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.373*Year+804.020. From this equation we can note that, every year, the indicator decreases with 0.373.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 63.89 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 20% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.392*Year+848.552. From this equation we can note that, every year, the indicator decreases with 0.392.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 52.08 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 19% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.374*Year+801.013. From this equation we can note that, every year, the indicator decreases with 0.374.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 11.70 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 78% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.109*Year-206.688. From this equation we can note that, every year, the indicator grow with 0.109.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 8.56 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 56% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 13.80 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 78% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.162*Year-311.731. From this equation we can note that, every year, the indicator grow with 0.162.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 31.49 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 6% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.264*Year-497.810. From this equation we can note that, every year, the indicator grow with 0.264.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 27.55 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.354*Year-681.798. From this equation we can note that, every year, the indicator grow with 0.354.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 34.12 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 78% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.211*Year-388.873. From this equation we can note that, every year, the indicator grow with 0.211.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 20.40 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 79% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 33.28 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 79% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.00 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 38% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 7.32 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 47% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.13 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 31% in the World.

2.104. IDA Blend

The study of indicator: Population, total during - highlights an average of 283980529.79. Also for Population, total the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 7102715.118*Year-13836217124.987. From this equation we can note that, every year, the indicator grow with 7102715.118.

The indicator: Labor force, total during 1990-2016 highlights an average of 132950642.96. Also for Labor force, total the region ranks on the first 16% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 3618408.985*Year-7114722554.689. From this equation we can note that, every year, the indicator grow with 3618408.985.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 35.16 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.156*Year-277.541. From this equation we can note that, every year, the indicator grow with 0.156.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 48.42 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 26% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 53.26 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 26% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 46.02 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 26% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 15.17 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 69% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.66 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 39% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 16.96 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 74% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 36.39 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 35.08 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 75% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.03 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.387*Year-738.316. From this equation we can note that, every year, the indicator grow with 0.387.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 38.30 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 72% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 48.21 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 66% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.81 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 46% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.89 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 56% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 5.71 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 35% in the World.

2.105. Indonesia

The study of indicator: Population, total during - highlights an average of 173426701.14. Also for Population, total the region ranks on the first 17% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 3164476.102*Year-6117551788.907. From this equation we can note that, every year, the indicator grow with 3164476.102.

The indicator: Labor force, total during 1990-2016 highlights an average of 102312896.93. Also for Labor force, total the region ranks on the first 19% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 1998286.411*Year-3900254785.263. From this equation we can note that, every year, the indicator grow with 1998286.411.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 37.44 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 79% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2000-2016 reveals an average of 75.50Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 28% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2000-2016 highlights an average of 91.58Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 5% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2000-2016 highlights an average of 84.07Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 5% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 42.15 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 33% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 42.40 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 38% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 42.00 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 33% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 18.40 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 36% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.90 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 24% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 20.48 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 48% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 39.45 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.504*Year-971.068. From this equation we can note that, every year, the indicator grow with 0.504.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 42.70 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 64% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.53 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 72% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 30.48 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 75% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 35.74 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 80% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 6.77 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 34% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.01 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 37% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.03 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 34% in the World.

2.106. IDA only

The study of indicator: Population, total during - highlights an average of 576049543.00. Also for Population, total the region ranks on the first 8% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 14098839.898*Year-27452444173.535. From this equation we can note that, every year, the indicator grow with 14098839.898.

The indicator: Labor force, total during 1990-2016 highlights an average of 310928839.85. Also for Labor force, total the region ranks on the first 10% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 8316220.932*Year-16346461686.191. From this equation we can note that, every year, the indicator grow with 8316220.932.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 40.60 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 57% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.090*Year-138.719. From this equation we can note that, every year, the indicator grow with 0.090.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 60.22 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 16% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 67.24 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 15% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: -0.329*Year+726.220. From this equation we can note that, every year, the indicator decreases with 0.329.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 54.94 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 17% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 10.30 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 80% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.132*Year-254.387. From this equation we can note that, every year, the indicator grow with 0.132.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 7.60 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 63% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 12.31 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.189*Year-367.258. From this equation we can note that, every year, the indicator grow with 0.189.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 29.49 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 7% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 25.15 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.274*Year-523.178. From this equation we can note that, every year, the indicator grow with 0.274.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 32.74 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 83% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 14.82 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 83% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 26.22 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 84% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.66 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 35% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.73 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 42% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.85 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 29% in the World.

2.107. Isle of Man

The study of indicator: Population, total during - highlights an average of 66130.79. Also for Population, total the region ranks on the first 92% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 621.696*Year-1169801.260. From this equation we can note that, every year, the indicator grow with 621.696.

2.108. India

The study of indicator: Population, total during - highlights an average of 853265287.81. Also for Population, total the region ranks on the first 7% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 16427322.466*Year-31804251774.801. From this equation we can note that, every year, the indicator grow with 16427322.466.

The indicator: Labor force, total during 1990-2016 highlights an average of 427318472.63. Also for Labor force, total the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 7020415.175*Year-13634573122.101. From this equation we can note that, every year, the indicator grow with 7020415.175.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 27.19 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 91% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1994-2012 reveals an average of 8.71Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 100% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1994-2012 highlights an average of 22.42Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 52% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1994-2012 highlights an average of 17.71Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 98% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 55.73 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 23% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.770*Year+1598.456. From this equation we can note that, every year, the indicator decreases with 0.770.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 70.19 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 18% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 50.39 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 26% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.761*Year+1574.422. From this equation we can note that, every year, the indicator decreases with 0.761.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 19.11 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 25% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 14.58 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 13% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 20.77 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 48% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: 0.465*Year-910.837. From this equation we can note that, every year, the indicator grow with 0.465.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 25.15 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.330*Year-635.016. From this equation we can note that, every year, the indicator grow with 0.330.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 15.24 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 94% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 28.84 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 86% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 0.296*Year-563.303. From this equation we can note that, every year, the indicator grow with 0.296.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 11.12 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 90% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 18.03 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 96% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.94 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 12% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.24 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 16% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.83 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 12% in the World.

2.109. Not classified

2.110. Ireland

The study of indicator: Population, total during - highlights an average of 3604802.77. Also for Population, total the region ranks on the first 63% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 33786.034*Year-63561833.264. From this equation we can note that, every year, the indicator grow with 33786.034.

The indicator: Labor force, total during 1990-2016 highlights an average of 1874932.70. Also for Labor force, total the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 40632.274*Year-79511511.125. From this equation we can note that, every year, the indicator grow with 40632.274.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 40.97 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 43% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.393*Year-747.008. From this equation we can note that, every year, the indicator grow with 0.393.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 74.79Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 45% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 84.26Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 43% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 79.33Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 43% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 7.76 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 79% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.02 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 88% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 11.68 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 76% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 25.17 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 60% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.98 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 67% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.466*Year+946.170. From this equation we can note that, every year, the indicator decreases with 0.466.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 33.95 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 45% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 84.99 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 10% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.574*Year-1064.640. From this equation we can note that, every year, the indicator grow with 0.574.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 54.37 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 16% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 91.45 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 10% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 73.71 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 30% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 9.47 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 61% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 8.47 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 41% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 10.26 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 72% in the World.

2.111. Iran, Islamic Rep.

The study of indicator: Population, total during - highlights an average of 50596659.39. Also for Population, total the region ranks on the first 23% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 1144466.001*Year-2224601749.774. From this equation we can note that, every year, the indicator grow with 1144466.001.

The indicator: Labor force, total during 1990-2016 highlights an average of 20787765.37. Also for Labor force, total the region ranks on the first 28% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 541683.915*Year-1064205115.433. From this equation we can note that, every year, the indicator grow with 541683.915.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 15.76 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 97% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 22.38 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 56% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 23.97 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 49% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 21.85 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 62% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 31.54 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 5% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 30.35 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 6% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 31.91 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 14% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 46.08 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 45.70 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 62% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 46.23 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 52% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 42.19 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 59% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 51.88 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 64% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 11.68 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 77% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 19.01 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 86% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 10.30 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 76% in the World.

2.112. Iraq

The study of indicator: Population, total during - highlights an average of 18538447.23. Also for Population, total the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 506091.403*Year-987571262.518. From this equation we can note that, every year, the indicator grow with 506091.403.

The indicator: Labor force, total during 1990-2016 highlights an average of 6635860.33. Also for Labor force, total the region ranks on the first 42% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 243092.737*Year-480278892.849. From this equation we can note that, every year, the indicator grow with 243092.737.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 14.97 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 96% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.510*Year-1005.854. From this equation we can note that, every year, the indicator grow with 0.510.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 20.51 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 52% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 42.40 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 28% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 16.96 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 64% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 19.04 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 46% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.66 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 85% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 21.08 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 60% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 60.47 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 50.95 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 64% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 61.97 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 25% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 46.52 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 58% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 57.19 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 48% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 17.45 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 88% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 28.90 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 93% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 15.29 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 88% in the World.

2.113. Iceland

The study of indicator: Population, total during - highlights an average of 252305.28. Also for Population, total the region ranks on the first 85% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 2751.775*Year-5218223.329. From this equation we can note that, every year, the indicator grow with 2751.775.

The indicator: Labor force, total during 1990-2016 highlights an average of 172730.15. Also for Labor force, total the region ranks on the first 94% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 2404.918*Year-4644320.992. From this equation we can note that, every year, the indicator grow with 2404.918.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.74 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 22% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1999-2016 reveals an average of 89.87Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 0% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1999-2016 highlights an average of 93.89Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 0% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1999-2016 highlights an average of 91.72Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 0% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 7.03 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 82% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.257*Year+521.498. From this equation we can note that, every year, the indicator decreases with 0.257.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 3.30 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 84% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 10.30 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 78% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.367*Year+745.468. From this equation we can note that, every year, the indicator decreases with 0.367.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.99 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.345*Year+713.727. From this equation we can note that, every year, the indicator decreases with 0.345.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.15 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 65% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.381*Year+775.083. From this equation we can note that, every year, the indicator decreases with 0.381.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 31.59 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 42% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 85.56 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 12% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.501*Year-918.384. From this equation we can note that, every year, the indicator grow with 0.501.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 58.10 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.651*Year-1246.196. From this equation we can note that, every year, the indicator grow with 0.651.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 90.29 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 8% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 78.22 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 12% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.06 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 9% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 3.99 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 9% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.11 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 9% in the World.

2.114. Israel

The study of indicator: Population, total during - highlights an average of 4926216.14. Also for Population, total the region ranks on the first 54% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 113793.268*Year-221294800.811. From this equation we can note that, every year, the indicator grow with 113793.268.

The indicator: Labor force, total during 1990-2016 highlights an average of 2963927.19. Also for Labor force, total the region ranks on the first 60% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 75147.488*Year-147556490.858. From this equation we can note that, every year, the indicator grow with 75147.488.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 44.62 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 21% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2013 reveals an average of 74.22Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 56% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2013 highlights an average of 80.34Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 52% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1.780*Year-3499.241. From this equation we can note that, every year, the indicator grow with 1.780.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2013 highlights an average of 76.90Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 54% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 2.09 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 98% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.091*Year+185.113. From this equation we can note that, every year, the indicator decreases with 0.091.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.96 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 94% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 3.02 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 97% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.119*Year+240.840. From this equation we can note that, every year, the indicator decreases with 0.119.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 23.16 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 61% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.496*Year+1016.761. From this equation we can note that, every year, the indicator decreases with 0.496.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.28 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.299*Year+610.348. From this equation we can note that, every year, the indicator decreases with 0.299.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 32.62 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 44% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.536*Year+1105.670. From this equation we can note that, every year, the indicator decreases with 0.536.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 87.76 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 10% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.343*Year-599.662. From this equation we can note that, every year, the indicator grow with 0.343.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 64.35 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 6% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.657*Year-1251.038. From this equation we can note that, every year, the indicator grow with 0.657.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 92.88 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 10% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 83.84 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 11% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 9.80 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 24% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.46 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 21% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.31 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 27% in the World.

2.115. Italy

The study of indicator: Population, total during - highlights an average of 56204448.95. Also for Population, total the region ranks on the first 25% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 24064020.96. Also for Labor force, total the region ranks on the first 29% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 39.20 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 58% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.253*Year-466.578. From this equation we can note that, every year, the indicator grow with 0.253.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 1992-2016 reveals an average of 74.93Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 70% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 1992-2016 highlights an average of 81.58Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 75% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.511*Year+1106.553. From this equation we can note that, every year, the indicator decreases with 0.511.The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 1992-2016 highlights an average of 78.31Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 78% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: -0.427*Year+933.399. From this equation we can note that, every year, the indicator decreases with 0.427.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 5.00 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 85% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 4.24 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 81% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 5.51 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 85% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 30.85 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: -0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: -0.315*Year+661.353. From this equation we can note that, every year, the indicator decreases with 0.315.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 18.39 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 32% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.470*Year+959.999. From this equation we can note that, every year, the indicator decreases with 0.470.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 38.64 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 10% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 77.38 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.705*Year-1334.594. From this equation we can note that, every year, the indicator grow with 0.705.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 55.84 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 28% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.251*Year-446.985. From this equation we can note that, every year, the indicator grow with 0.251.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 78.89 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.296*Year-514.764. From this equation we can note that, every year, the indicator grow with 0.296.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 69.39 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 36% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 9.90 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 80% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 12.73 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 74% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.13 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 81% in the World.

2.116. Jamaica

The study of indicator: Population, total during - highlights an average of 2335293.07. Also for Population, total the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 23583.027*Year-44547765.050. From this equation we can note that, every year, the indicator grow with 23583.027.

The indicator: Labor force, total during 1990-2016 highlights an average of 1265795.74. Also for Labor force, total the region ranks on the first 76% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 14538.584*Year-27854987.287. From this equation we can note that, every year, the indicator grow with 14538.584.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.57 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 53% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 20.60 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 55% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 9.97 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 63% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 28.37 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 44% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 17.64 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 71% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 7.87 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 79% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.76 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 65% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 82.17 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 23% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 46.88 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 43% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.488*Year-931.581. From this equation we can note that, every year, the indicator grow with 0.488.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 66.12 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 46% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 55.07 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 68% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 13.72 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 85% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 19.02 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 83% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 9.38 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 77% in the World.

2.117. Jordan

The study of indicator: Population, total during - highlights an average of 3876501.82. Also for Population, total the region ranks on the first 52% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 136588.859*Year-267662150.428. From this equation we can note that, every year, the indicator grow with 136588.859.

The indicator: Labor force, total during 1990-2016 highlights an average of 1498727.11. Also for Labor force, total the region ranks on the first 70% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 55696.023*Year-110060407.357. From this equation we can note that, every year, the indicator grow with 55696.023.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 15.22 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 97% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 3.87 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 93% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.213*Year+429.848. From this equation we can note that, every year, the indicator decreases with 0.213.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 2.50 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 91% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.170*Year+343.262. From this equation we can note that, every year, the indicator decreases with 0.170.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 4.08 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 94% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.214*Year+433.819. From this equation we can note that, every year, the indicator decreases with 0.214.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 20.49 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 62% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.53 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 59% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 21.99 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 72% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 86.98 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 12% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 73.94 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 2% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 93.88 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 3% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 80.52 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 17% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 14.20 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 89% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 25.38 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 94% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 12.21 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 87% in the World.

2.118. Japan

The study of indicator: Population, total during - highlights an average of 117703334.79. Also for Population, total the region ranks on the first 20% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 66667082.78. Also for Labor force, total the region ranks on the first 21% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 41.09 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 52% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2012-2016 reveals an average of 54.58Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 86% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2012-2016 highlights an average of 68.98Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 39% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2012-2016 highlights an average of 61.94Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 62% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 4.83 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.107*Year+219.150. From this equation we can note that, every year, the indicator decreases with 0.107.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 5.05 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 77% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.161*Year+326.976. From this equation we can note that, every year, the indicator decreases with 0.161.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 4.69 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 88% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 30.11 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 16% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.379*Year+788.839. From this equation we can note that, every year, the indicator decreases with 0.379.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 20.01 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.541*Year+1103.062. From this equation we can note that, every year, the indicator decreases with 0.541.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 37.30 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 12% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 74.94 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 32% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.703*Year-1333.745. From this equation we can note that, every year, the indicator grow with 0.703.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 58.03 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 23% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 83.39 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 12% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 0.656*Year-1230.291. From this equation we can note that, every year, the indicator grow with 0.656.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 83.29 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 5% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.97 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 10% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 3.80 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 6% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.09 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 12% in the World.

2.119. Kazakhstan

The study of indicator: Population, total during - highlights an average of 14605426.56. Also for Population, total the region ranks on the first 41% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 8211326.04. Also for Labor force, total the region ranks on the first 42% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 48.67 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 14% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 31.54 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 56% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 30.02 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 52% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 32.95 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 56% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 17.59 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 49% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 10.46 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 41% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 24.18 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 33% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 59.52 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 46% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 42.86 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 44% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 61.37 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 39% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 64.57 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 37% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.08 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 25% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 9.52 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 28% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.71 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 21% in the World.

2.120. Kenya

The study of indicator: Population, total during - highlights an average of 23883480.61. Also for Population, total the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 719923.530*Year-1407324497.562. From this equation we can note that, every year, the indicator grow with 719923.530.

The indicator: Labor force, total during 1990-2016 highlights an average of 13207208.04. Also for Labor force, total the region ranks on the first 33% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 355067.698*Year-697993391.884. From this equation we can note that, every year, the indicator grow with 355067.698.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 48.28 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 14% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 66.18 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 10% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.238*Year+542.158. From this equation we can note that, every year, the indicator decreases with 0.238.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 77.91 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 8% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.174*Year+426.212. From this equation we can note that, every year, the indicator decreases with 0.174.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 56.33 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 16% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 7.41 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.083*Year-159.787. From this equation we can note that, every year, the indicator grow with 0.083.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 2.69 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 91% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 11.38 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 86% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.130*Year-248.423. From this equation we can note that, every year, the indicator grow with 0.130.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 26.40 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 9% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: 0.155*Year-285.119. From this equation we can note that, every year, the indicator grow with 0.155.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 19.38 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 92% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.159*Year-299.258. From this equation we can note that, every year, the indicator grow with 0.159.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 32.28 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 83% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 20.51 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 80% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 47.50 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 60% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 10.67 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 77% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 12.58 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 77% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 8.97 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 75% in the World.

2.121. Kyrgyz Republic

The study of indicator: Population, total during - highlights an average of 4120177.19. Also for Population, total the region ranks on the first 60% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 65166.502*Year-125430829.704. From this equation we can note that, every year, the indicator grow with 65166.502.

The indicator: Labor force, total during 1990-2016 highlights an average of 2168119.00. Also for Labor force, total the region ranks on the first 68% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 36669.891*Year-71281673.336. From this equation we can note that, every year, the indicator grow with 36669.891.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 42.76 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 68% in the World. The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2011-2013 reveals an average of 70.10Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 86% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2011-2013 highlights an average of 89.33Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 40% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2011-2013 highlights an average of 78.63Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 75% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 39.07 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 37% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 39.28 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 37% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 38.90 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 42% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 18.26 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 46% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.64 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 43% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 23.11 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 41% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 42.66 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 49.08 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 57% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.98 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 64% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 50.15 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 50% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 49.05 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 65% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.72 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 58% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 9.94 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 61% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.80 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 56% in the World.

2.122. Cambodia

The study of indicator: Population, total during - highlights an average of 9702197.23. Also for Population, total the region ranks on the first 44% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 183077.011*Year-354254900.291. From this equation we can note that, every year, the indicator grow with 183077.011.

The indicator: Labor force, total during 1990-2016 highlights an average of 6458431.85. Also for Labor force, total the region ranks on the first 43% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 214729.335*Year-423644426.483. From this equation we can note that, every year, the indicator grow with 214729.335.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 50.60 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 4% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 63.92 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 24% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -1.718*Year+3505.213. From this equation we can note that, every year, the indicator decreases with 1.718.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 64.61 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 30% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -1.931*Year+3933.109. From this equation we can note that, every year, the indicator decreases with 1.931.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 63.16 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 22% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -1.501*Year+3070.672. From this equation we can note that, every year, the indicator decreases with 1.501.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 11.91 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 53% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.762*Year-1514.177. From this equation we can note that, every year, the indicator grow with 0.762.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 11.81 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 13% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 12.00 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 69% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 0.750*Year-1490.450. From this equation we can note that, every year, the indicator grow with 0.750.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 24.18 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 6% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.956*Year-1890.964. From this equation we can note that, every year, the indicator grow with 0.956.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 23.58 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 77% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 1.158*Year-2297.332. From this equation we can note that, every year, the indicator grow with 1.158.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 24.84 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.750*Year-1478.369. From this equation we can note that, every year, the indicator grow with 0.750.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 17.78 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1.859*Year-3705.852. From this equation we can note that, every year, the indicator grow with 1.859.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 24.47 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 69% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: 2.370*Year-4724.001. From this equation we can note that, every year, the indicator grow with 2.370.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 0.88 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 0% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 0.74 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 0% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 1.03 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 0% in the World.

2.123 Kiribati

The study of indicator: Population, total during - highlights an average of 71959.35. Also for Population, total the region ranks on the first 89% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 1252.248*Year-2417508.753. From this equation we can note that, every year, the indicator grow with 1252.248.

2.124. St. Kitts and Nevis

The study of indicator: Population, total during - highlights an average of 46213.35. Also for Population, total the region ranks on the first 96% in the World.

2.125. Korea, Rep.

The study of indicator: Population, total during - highlights an average of 40706806.49. Also for Population, total the region ranks on the first 27% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.97. The equation of linear regression is therefore: 460836.245*Year-875435648.458. From this equation we can note that, every year, the indicator grow with 460836.245.

The indicator: Labor force, total during 1990-2016 highlights an average of 23577046.89. Also for Labor force, total the region ranks on the first 28% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 300788.984*Year-578903287.095. From this equation we can note that, every year, the indicator grow with 300788.984.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 40.50 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 59% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 9.44 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 78% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: -0.424*Year+858.237. From this equation we can note that, every year, the indicator decreases with 0.424.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 10.62 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 68% in the World. Time regression analysis reveals a correlation coefficient value: -0.98 and a value of R Square: 0.96. The equation of linear regression is therefore: -0.531*Year+1075.321. From this equation we can note that, every year, the indicator decreases with 0.531.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 8.62 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 83% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.353*Year+716.523. From this equation we can note that, every year, the indicator decreases with 0.353.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 28.03 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 22% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 18.30 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 33% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 34.80 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 18% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 71.08 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 31% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 1.102*Year-2137.290. From this equation we can note that, every year, the indicator grow with 1.102.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 56.59 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 21% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 64.93 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 34% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.791*Year-1519.311. From this equation we can note that, every year, the indicator grow with 0.791.The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 63.58 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 35% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 3.49 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 13% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 2.93 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 12% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 3.87 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 19% in the World.

2.126. Kuwait

The study of indicator: Population, total during - highlights an average of 1632611.07. Also for Population, total the region ranks on the first 66% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 1162454.41. Also for Labor force, total the region ranks on the first 72% in the World. The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 23.49 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 88% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 2.78 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 90% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.17 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 100% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 3.73 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 89% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 24.25 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 13% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 4.46 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 76% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 31.44 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 10% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 95.38 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 4% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 64.84 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 25% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 99.44 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 1% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 96.52 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 1% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 1.68 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 8% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 1.50 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 6% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 1.75 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 9% in the World.

2.127. Latin America & Caribbean (Excluding High Income)

The study of indicator: Population, total during - highlights an average of 406952620.23. Also for Population, total the region ranks on the first 12% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 7432557.330*Year-14368971351.008. From this equation we can note that, every year, the indicator grow with 7432557.330.

The indicator: Labor force, total during 1990-2016 highlights an average of 229430632.63. Also for Labor force, total the region ranks on the first 13% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 5209771.322*Year-10205741326.026. From this equation we can note that, every year, the indicator grow with 5209771.322.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.43 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 66% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.286*Year-534.992. From this equation we can note that, every year, the indicator grow with 0.286.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2016 reveals an average of 67.59Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 58% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2016 highlights an average of 76.71Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 25% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2016 highlights an average of 71.73Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 38% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 18.15 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 59% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 10.93 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 59% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 22.54 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 50% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: -0.253*Year+529.513. From this equation we can note that, every year, the indicator decreases with 0.253.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.83 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 44% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.95 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 39% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 27.27 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 40% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 76.12 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 35% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.90. The equation of linear regression is therefore: 0.246*Year-417.612. From this equation we can note that, every year, the indicator grow with 0.246.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 50.19 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 46% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 62.00 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 49% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 59.97 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 53% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.78 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 63% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.96 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 64% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.40 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 58% in the World.

2.128. Lao PDR

The study of indicator: Population, total during - highlights an average of 4220550.21. Also for Population, total the region ranks on the first 58% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 87019.463*Year-168774142.470. From this equation we can note that, every year, the indicator grow with 87019.463.

The indicator: Labor force, total during 1990-2016 highlights an average of 2655180.93. Also for Labor force, total the region ranks on the first 62% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 61892.464*Year-121315424.427. From this equation we can note that, every year, the indicator grow with 61892.464.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 50.15 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 6% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 83.35 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 1% in the World. Time regression analysis reveals a correlation coefficient value: -0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: -0.256*Year+596.451. From this equation we can note that, every year, the indicator decreases with 0.256.The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 87.28 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 2% in the World. Time regression analysis reveals a correlation coefficient value: -0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: -0.211*Year+509.766. From this equation we can note that, every year, the indicator decreases with 0.211.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 79.27 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 2% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 3.54 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 98% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 2.55 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 91% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 4.58 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 98% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 13.11 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 29% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.245*Year-477.322. From this equation we can note that, every year, the indicator grow with 0.245.The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 10.19 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 99% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 0.237*Year-464.483. From this equation we can note that, every year, the indicator grow with 0.237.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 16.16 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 99% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.259*Year-503.245. From this equation we can note that, every year, the indicator grow with 0.259.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 8.09 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 93% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 15.82 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 95% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 1.77 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 3% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 1.51 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 2% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 2.05 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 3% in the World.

2.129. Lebanon

The study of indicator: Population, total during - highlights an average of 3094882.26. Also for Population, total the region ranks on the first 60% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 1278690.48. Also for Labor force, total the region ranks on the first 72% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 50218.696*Year-99309357.548. From this equation we can note that, every year, the indicator grow with 50218.696.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 23.03 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 92% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 8.92 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 73% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 0.20 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 98% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 11.36 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 70% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 18.37 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 38% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 4.59 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 74% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 22.26 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 43% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 95.22 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 5% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 66.38 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 20% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 81.90 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 32% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 56.13 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 64% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 7.54 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 49% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.87 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 69% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 6.53 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 32% in the World.

2.130. Liberia

The study of indicator: Population, total during - highlights an average of 2359616.75. Also for Population, total the region ranks on the first 64% in the World.

The indicator: Labor force, total during 1990-2016 highlights an average of 1000248.93. Also for Labor force, total the region ranks on the first 76% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.98. The equation of linear regression is therefore: 35459.305*Year-70024739.490. From this equation we can note that, every year, the indicator grow with 35459.305.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 47.53 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 15% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 49.57 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 21% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 47.83 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 24% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 51.20 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 23% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 7.82 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 81% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 4.31 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 81% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 11.10 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 76% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 42.60 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 2% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 47.85 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 71% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 37.71 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 77% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 7.69 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 95% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 24.81 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 90% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 4.30 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 14% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 4.02 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 14% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.59 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 19% in the World.

2.131. Libya

The study of indicator: Population, total during - highlights an average of 4050731.86. Also for Population, total the region ranks on the first 59% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 97533.350*Year-189845567.966. From this equation we can note that, every year, the indicator grow with 97533.350.

The indicator: Labor force, total during 1990-2016 highlights an average of 1928939.70. Also for Labor force, total the region ranks on the first 71% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 47697.179*Year-93608509.586. From this equation we can note that, every year, the indicator grow with 47697.179.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 23.51 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 91% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 15.23 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 50% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 25.28 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 40% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 12.62 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 58% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 24.75 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 20% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 22.50 bigger than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 4% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 25.34 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 55% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 60.01 bigger than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 1% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 52.24 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 73% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 62.05 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 31% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 66.13 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 54% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 68.02 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 50% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 17.86 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 92% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 27.79 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 94% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 14.73 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 91% in the World.

2.132. St. Lucia

The study of indicator: Population, total during - highlights an average of 134123.91. Also for Population, total the region ranks on the first 87% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 1695.606*Year-3236740.768. From this equation we can note that, every year, the indicator grow with 1695.606.

The indicator: Labor force, total during 1990-2016 highlights an average of 75187.81. Also for Labor force, total the region ranks on the first 97% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 1781.916*Year-3493989.434. From this equation we can note that, every year, the indicator grow with 1781.916.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 43.24 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 33% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.94. The equation of linear regression is therefore: 0.281*Year-520.418. From this equation we can note that, every year, the indicator grow with 0.281.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 18.18 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 62% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 12.01 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 59% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 22.91 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 55% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 20.01 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 63% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.80 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 65% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 25.68 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 52% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 75.20 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 29% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 51.42 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 35% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 72.07 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 42% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 60.12 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 55% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 19.19 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 95% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 23.81 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 96% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 15.27 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 94% in the World.

2.133. Latin America & Caribbean

The study of indicator: Population, total during - highlights an average of 428382503.95. Also for Population, total the region ranks on the first 12% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 7682302.083*Year-14844034036.731. From this equation we can note that, every year, the indicator grow with 7682302.083.

The indicator: Labor force, total during 1990-2016 highlights an average of 240072225.30. Also for Labor force, total the region ranks on the first 12% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 1.00. The equation of linear regression is therefore: 5390872.838*Year-10557846068.430. From this equation we can note that, every year, the indicator grow with 5390872.838.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 38.41 smaller than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 65% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.289*Year-539.867. From this equation we can note that, every year, the indicator grow with 0.289.The analysis of indicator: Labor force with advanced education (% of total working-age population with advanced education) during 2009-2016 reveals an average of 67.63Also for Labor force with advanced education (% of total working-age population with advanced education) the region ranks on the first 55% in the World. The study of indicator: Labor force with advanced education, female (% of female working-age population with advanced education) during 2009-2016 highlights an average of 76.77Also for Labor force with advanced education, female (% of female working-age population with advanced education) the region ranks on the first 23% in the World. The analysis of indicator: Labor force with advanced education, male (% of male working-age population with advanced education) during 2009-2016 highlights an average of 71.79Also for Labor force with advanced education, male (% of male working-age population with advanced education) the region ranks on the first 36% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 17.82 smaller than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 61% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 10.63 smaller than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 60% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 22.19 smaller than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 51% in the World. Time regression analysis reveals a correlation coefficient value: -0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: -0.253*Year+528.583. From this equation we can note that, every year, the indicator decreases with 0.253.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 21.92 bigger than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 42% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 12.90 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 40% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 27.44 bigger than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 39% in the World.

The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 76.47 bigger than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 33% in the World. Time regression analysis reveals a correlation coefficient value: 0.95 and a value of R Square: 0.91. The equation of linear regression is therefore: 0.245*Year-413.545. From this equation we can note that, every year, the indicator grow with 0.245.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 50.37 bigger than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 44% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 62.63 bigger than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 48% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 60.39 bigger than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 53% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 8.78 bigger than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 63% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 10.92 bigger than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 63% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 7.42 bigger than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 58% in the World.

2.134. Least developed countries: UN classification

The study of indicator: Population, total during - highlights an average of 529739708.04. Also for Population, total the region ranks on the first 10% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.97. The equation of linear regression is therefore: 13009092.050*Year-25332335287.700. From this equation we can note that, every year, the indicator grow with 13009092.050.

The indicator: Labor force, total during 1990-2016 highlights an average of 288701262.41. Also for Labor force, total the region ranks on the first 11% in the World. Time regression analysis reveals a correlation coefficient value: 1.00 and a value of R Square: 0.99. The equation of linear regression is therefore: 7866824.444*Year-15468548098.592. From this equation we can note that, every year, the indicator grow with 7866824.444.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 41.15 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 55% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.95. The equation of linear regression is therefore: 0.086*Year-131.092. From this equation we can note that, every year, the indicator grow with 0.086.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 60.40 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 16% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 67.34 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 15% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 55.05 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 17% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 10.36 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 80% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.140*Year-270.695. From this equation we can note that, every year, the indicator grow with 0.140.The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 7.70 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 62% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 12.39 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 81% in the World. Time regression analysis reveals a correlation coefficient value: 0.96 and a value of R Square: 0.92. The equation of linear regression is therefore: 0.201*Year-390.615. From this equation we can note that, every year, the indicator grow with 0.201.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 29.25 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 7% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 24.96 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 84% in the World. Time regression analysis reveals a correlation coefficient value: 0.97 and a value of R Square: 0.93. The equation of linear regression is therefore: 0.256*Year-487.614. From this equation we can note that, every year, the indicator grow with 0.256.The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 32.55 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 85% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 14.07 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 83% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 25.06 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 84% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.40 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 32% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.43 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 38% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.60 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 25% in the World.

2.135. Low Income

The study of indicator: Population, total during - highlights an average of 341833101.88. Also for Population, total the region ranks on the first 11% in the World. Time regression analysis reveals a correlation coefficient value: 0.98 and a value of R Square: 0.95. The equation of linear regression is therefore: 8684376.305*Year-16922706992.393. From this equation we can note that, every year, the indicator grow with 8684376.305.

The indicator: Labor force, total during 1990-2016 highlights an average of 198529425.59. Also for Labor force, total the region ranks on the first 14% in the World. Time regression analysis reveals a correlation coefficient value: 0.99 and a value of R Square: 0.99. The equation of linear regression is therefore: 5686785.675*Year-11192102280.638. From this equation we can note that, every year, the indicator grow with 5686785.675.The analysis of: Labor force, female (% of total labor force) during 1990-2016 highlights an average of 46.57 bigger than the World average: 39.49. Also for Labor force, female (% of total labor force) the region ranks on the first 23% in the World.

An overview of the indicator: Employment in agriculture (% of total employment) during - highlights an average of 67.40 bigger than the World average: 36.26. Also for Employment in agriculture (% of total employment) the region ranks on the first 7% in the World. The study of indicator: Employment in agriculture, female (% of female employment) during 1991-2016 highlights an average of 70.92 bigger than the World average: 38.19. Also for Employment in agriculture, female (% of female employment) the region ranks on the first 10% in the World.Employment in agriculture, male (% of male employment) during 1991-2016 highlights an average of 64.39 bigger than the World average: 34.99. Also for Employment in agriculture, male (% of male employment) the region ranks on the first 4% in the World.

The indicator: Employment in industry (% of total employment) during 1991-2016 highlights an average of 8.56 smaller than the World average: 20.78. Also for Employment in industry (% of total employment) the region ranks on the first 89% in the World. The analysis of indicator: Employment in industry, female (% of female employment) during 1991-2016 highlights an average of 6.24 smaller than the World average: 14.98. Also for Employment in industry, female (% of female employment) the region ranks on the first 78% in the World.Employment in industry, male (% of male employment) during 1991-2016 highlights an average of 10.54 smaller than the World average: 24.57. Also for Employment in industry, male (% of male employment) the region ranks on the first 90% in the World.

The analysis of: Employment in services (% of total employment) during 1991-2016 highlights an average of 24.04 smaller than the World average: 42.96. Also for Employment in services (% of total employment) the region ranks on the first 16% in the World. The study of indicator: Employment in services, female (% of female employment) during 1991-2016 highlights an average of 22.84 smaller than the World average: 46.83. Also for Employment in services, female (% of female employment) the region ranks on the first 91% in the World. The analysis of indicator: Employment in services, male (% of male employment) during 1991-2016 highlights an average of 25.07 smaller than the World average: 40.44. Also for Employment in services, male (% of male employment) the region ranks on the first 97% in the World.

An overview of the indicator: Wage and salaried workers, female (% of female employment) during 1991-2016 highlights an average of 15.60 smaller than the World average: 49.50. Also for Wage and salaried workers, female (% of female employment) the region ranks on the first 86% in the World. The analysis of indicator: Wage and salaried workers, male (% of male employment) during 1991-2016 highlights an average of 24.82 smaller than the World average: 49.30. Also for Wage and salaried workers, male (% of male employment) the region ranks on the first 89% in the World.

The indicator: Unemployment, total (% of total labor force) during 1991-2016 highlights an average of 5.54 smaller than the World average: 6.11. Also for Unemployment, total (% of total labor force) the region ranks on the first 34% in the World. The analysis of: Unemployment, female (% of female labor force) during 1991-2016 highlights an average of 6.48 smaller than the World average: 6.54. Also for Unemployment, female (% of female labor force) the region ranks on the first 40% in the World. The study of indicator: Unemployment, male (% of male labor force) during 1991-2016 highlights an average of 4.71 smaller than the World average: 5.82. Also for Unemployment, male (% of male labor force) the region ranks on the first 28% in the World.

3. References

Ioan, C.A. & Ioan, G. (2010). Applied Mathematics in Micro and Macroeconomics. Galati, Romania: Sinteze Publishers.

Ioan, C.A. & Ioan, G. (2012). Mathconomics. Galați: Zigotto Publishers.

Ioan, G. & Ioan, C.A. (2017). Macroeconomics. Galați: Zigotto Publishers.

Ioan C.A. (2017). Chance - Between Finite and Infinite. Galati, Romania: Zigotto Publishers.

*** World Bank national accounts data.

*** International Monetary Fund.

Refbacks

• There are currently no refbacks.

This work is licensed under a Creative Commons Attribution 4.0 International License.