Table 1: Total and Within-Skill-Groups Wage Variance in Latin America, 1995–2015

||Contribution<br>level|of the comp<br> of wage ineq|onent to the<br>uality|Contribution of t<br>component to the<br>inequ|he change in the<br> change in wage<br>ality|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(2)-(1)|(3)-(2)|
||1995|2002|2015|1995-2002|2002–15|
|Between-skill-groups component|29 (0.155)|28 (0.212)|25 (0.146)|24 (0.056)|34 (-0.066)|
|Within-skill-groups component|71 (0.379)|72 (0.557)|75 (0.429)|76 (0.178)|66 (-0.127)|
|Total wage variance|100 (0.534)|100 (0.768)|100 (0.575)|100 (0.234)|100 (-0.193)|

_Source_ : Authors’ calculations based on data from the Socioeconomic Database for Latin America and the Caribbean, World Bank and Center for Distributive, Labor and Social Studies of the Universidad Nacional de La Plata (CEDLAS) (http://sedlac.econo.unlp.edu.ar/eng). _Note:_ Total wage variance is the variance of the log hourly wage in the household surveys data set. Within-skill-groups variance is the variance of the residuals from a regression of log hourly wage on a vector of workers’ socio-demographic characteristics, including all possible interactions between education (five categories), experience (five-year bins), and gender. Cells contain the contribution of each component to the level or change in variance (shown in parentheses) and the corresponding share their represent. When a given year was not available for a particular country, the closest year available was used. See supplementary online appendix S1.1 for details on this “circa” concept where _S_ ( _i, t_ ) denotes the sector and occupation of worker _i_ in year _t_ . Following equation (2), this paper decomposes the variance of hourly wages each year into the variance across sector-occupation cells, the variance across education-gender-experience cells, the covariance between these two terms, and a residual. As before, the differences over time are simply the differences of each component. To proceed with the decomposition, the occupations and sector classifications were harmonized into seventeen industries and nine occupations.<sup>13</sup> The results are summarized in table 2, panel a, for Latin America, and table S2.8 in supplementary online appendix S2 for each country individually. In table 2, columns 1, 2, and 3 report the results for each year individually, and columns 4 and 5 decompose the changes in inequality over time. The within-component (the residual) accounts for most of the total wage variance. Specifically, it accounts for 58, 61, and 66 percent of the inequality levels in 1995, 2002, and 2015, respectively. However, changes in the variance across sector-occupation cells play a large role during the expansion of inequality in 1995-2002, explaining 53 percent of the increase. Instead, during 2002-2015, the role of sector-occupations is more muted, accounting for 31 percent of the decline in dispersion. The within component continues to dominate the observed changes during 2002-2015, contributing to 45 percent of the decline in the variance.

> 13The 17 industries considered were agriculture, hunting, and forestry; fishing; mining and quarrying; manufacturing; electricity, gas, and water supply; construction; wholesale and retail trade; hotels and restaurants; transport, storage, and communication; financial intermediation; real estate, renting, and business activities; public administration and defense; education; health and social work; other community, social and personal service activities; activities of private households as employers; and extraterritorial organizations. The nine occupations considered were professionals or technicians; directors and managers; administrative employees and employees in middle-level jobs; merchants or sellers; employees in the service sector; agricultural employees; laborers in non-agricultural jobs and drivers; armed forces; and other.

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