changes during the 1990s and 2000s.<sup>16</sup> This information has been provided by the Team for Statistical Development for Latin America at the World Bank.<sup>17</sup> This allows us to identify more accurate trends at the country level. Since the breaks in comparability are not synchronized in the timing or the direction of the impact in our indicator of interest (labor income distribution and the earnings structure), there is no expected important effect on the regional aggregate constructed on a yearly basis.

Second, we use the most recent population projections based on the most recent census to adjust surveys that have not been updated. This procedure is carried out by each NSO years after the release of the census. However, the timing of the adjustment is different for each country. We have applied the last census projections of the urban and rural populations to the surveys to guarantee comparability at this level.

Third, we exclude some country surveys for certain years in which the parameter of interest included outliers by a simple routine of using as a benchmark the observations for the same country during the period. The parameters used are the proportion of missing labor income among the employed population, average earnings, and the sociodemographic composition of certain groups by education, experience group, sex, and area. This leads to the exclusion of Brazil in 1992 and 2007 and Paraguay in 1990.

Finally, we control for changes in terms of coverage even if these have been minor (similar to previous studies). In addition, in terms of coverage, almost all the surveys are representative at the national level during the last two decades. In the cases where the coverage of the surveys changes during the period of analysis, the surveys were trimmed to the geographical areas that were covered in both decades. This substantially affects Argentina and Uruguay, which thus become representative of the main urban areas,<sup>18</sup> and excludes less well populated areas in Brazil and Colombia.<sup>19</sup> The latter rule reduces the share of each of these countries in population-weighted regional averages, but not in the unweighted averages.

The following analysis also offers benchmarking of Latin American countries using a set of middle- and high-income countries and data of the International Labour Organization (ILO) Global Wage Report Gini database (for more than 30 European and middle-income countries). We also conduct our analysis of the changes in returns using data from the World Bank International Income Distribution Dataset (I2D2), consisting of harmonized microdata available for a subset of countries, including the United States and Turkey. Finally, we also incorporate analysis from South Africa built from the Post Apartheid Labor Market Series– v2.0 and the Russian Federation based on the Russia Longitudinal Monitoring Survey. The trends in labor income inequality found in these countries are similar to those discussed in the literature.<sup>20</sup> These countries are used as reference points in the study rather than as points of interest. Thus, harmonization, the control of comparability, and the validation of trends over time have been limited to guarantee a rough estimate of differences with respect to relations and trends in the Latin America and Caribbean region (see annex A.2).

The variable of interest is the labor income after taxes associated with the main occupation of workers during the month previous to the survey. The survey question is asked of all employees and of the selfemployed. The objective is to use this variable to approximate the labor earnings structure. As Székely and Hilgert (2007) point out, the cross-country comparison of labor income inequality is meaningful and shows a

> 16 The countries in which the effect was present and in which it was feasible to control for the effect are those on which data exist on two years in the same period, one for the series before the change and the other for the series after the change.

> 17 This information has been constructed based on a knowledge of the SEDLAC Project and survey metadata and in close contact with the staff of each NSO.

> 18 This change limited the sample in Argentina to the urban areas covered since 1992, Gran Buenos Aires, and other major urban areas that include around 50 percent of the population. It also limited the sample in Uruguay to the urban population in the metropolitan area of Montevideo (about 70 percent of the population).

> 19 Among other trimming procedures, the north rural areas of Brazil were excluded because these were not covered in the 1990s (less than 2 percent of the population); also urban areas in new departments in the Amazon and Oriental regions in Colombia, only recently covered (less than 4 percent of the population).

> 20 See Bakis and Sezgin (2015) for the case of Turkey, with a fall between 2002 and 2004 and a slight increase in inequality since 2004. See Leibbrandt Arden, and Woolard (2013) for the case of South Africa, with a steady increase since the 1990s and a slight increase during the first decade of the 2000s. See Autor, Katz, and Kearney (2008) for the case of the United States, with a slight increase from the 1990s to the end of 2010. See Calvo, López-Calva, and Posadas (2015) for the case of the Russian Federation, with a slight increase at the end of the 1990s, but a steady fall during the first decade of the 2000s.

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