for a large among of countries. The GIDD dataset is derived from household surveys harmonized by the World Bank.<sup>17</sup> It provides a cross section of surveys using 2011 as a base.<sup>18</sup> The sample covers 10.45 million individuals in 127 countries, constituting 83.4% of the global GDP and 86.3% of the global population<sup>19</sup> (see Table 1). The coverage of the data in GIDD is also large for most specific regions, both in terms of population and GDP.

Table 1: GIDD database coverage

|Region|GDP PPP<br>|$,B<br>|Populati<br>|on,M<br>|Microdata<br>|
|---|---|---|---|---|---|
||Total|%|Total|%|obs.|
|Low andmiddle-income countries|13,781.5|90.8|5,788.3|87.8|5,320,925|
|East Asia & Pacific|5,698.5|96.5|1,991.8|94.6|918,891|
|Europe & Central Asia|1,287.5|80.9|269.8|67.0|347,714|
|Latin America & Caribbean|3,379.2|98.2|585.6|98.0|1,472,436|
|Middle East & North Africa|843.6|19.5|344.1|19.4|70,402|
|South Asia|1,703.2|99.3|1,675.0|98.2|782,726|
|Sub-Saharan Africa|869.6|92.3|922.1|79.4|1,728,756|
|High-income countries|40,979.1|81.0|1,277.2|79.6|5,134,448|
|World|54,760.6|83.4|7,065.5|86.3|10,455,373|

Source: Authors’ elaboration using available data from GIDD-dataset.

From the household surveys, we extract information on individuals’ age, employment status, sector of activity, years of schooling and wage as the starting points to project the population growth by school attainment and the sectoral wage bill database (Cruz, Go and OsorioRodarte, 2017). These pieces of information feed into the LINKAGE model to establish consistency between the skill definition and volume of workers between the CGE model and the microsimulations.<sup>20</sup> Table 2 shows the share of workers by broad sectors (agriculture and nonagriculture) and skill level for 2012. The tabulation indicates that the share of skilled workers is much larger in high-income countries and the region of Europe & Central Asia (ECA). The three regions of East Asia & Pacific (EAP), South Asia (SAS), and Sub-Saharan Africa (SSA) together had approximately 96% of the people living below poverty line in 2015. In all of these regions, 35% or more of the paid workers were unskilled working in agriculture. An important channel through which changes in the composition of labor supply may affect income inequality and income distribution, in the long run, is the movement of workers across different categories delineated by the cells - agriculture, non-agriculture, skilled workers, and unskilled workers.

> 17 The data include household surveys harmonized by the Poverty Group Global Practice of the World Bank and the International Income Distribution Database (I2D2). The I2D2 is a World Bank project to collate, harmonize and make accessible comparable information from household surveys held by the World Bank, for poverty, inequality, education, demographics, and labor market analysis. For further details on I2D2, see Montenegro and Maximilian (2008).

> 18 For each country, the closest survey to 2011 has been chosen to be consistent with the database used in the LINKAGE model (Global Trade Analysis database v.8). From this dataset we derived the GIDD Sectoral Wage Bill database (Cruz, Go, and Osório-Rodarte, 2017).

> 19 If Japan and Switzerland are included with aggregated information generated from household surveys, using the Luxemburg Income Study data set, the GDP coverage increases to approximately 93%.

> 20 One issue is the comparability of school attainment to define skill-level because of differences in quality of education across countries. However, the differences of wages by skill, sector, and country indirectly account for the differences in respective productivity.

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