Wage Inequality in Latin America: Learning from Matched Employer-Employee Data
Inequality in Latin America fell substantially in the early 2000s. In this paper, we take advantage of administrative matched employee-employed data in Brazil, Chile and Ecuador to examine whether these inequality trends held in the formal sector, as well. We document a significant decrease in the log variance of earnings in Brazil and Ecuador in the early 2000s, whereas inequality in Chile between 2008 and 2015 remained largely flat. In this context, we find that inequality among salaried workers is largely a between-firm phenomenon across these three countries. We expand on our descriptive analysis and estimate an additive worker and firm fixed effects model to understand the driving factors behind inequality in the region. We find a significant decline in between-firm inequality in Brazil and a modest one in Chile. We last focus our attention on the commodities and manufacturing sectors, which were directly exposed to two large external shocks, the commodity-boom and the ''China Shock". We find an increase in inequality in the former sector accompanied by an reduction in inequality in the latter across the region.
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Language: | English |
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Inter-American Development Bank
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Subjects: | Income Equality, Workforce and Employment, Wage, E24 - Employment • Unemployment • Wages • Intergenerational Income Distribution • Aggregate Human Capital • Aggregate Labor Productivity, D22 - Firm Behavior: Empirical Analysis, J08 - Labor Economics Policies, J31 - Wage Level and Structure • Wage Differentials, Wage inequality; Matched Employer-Employee Data; Firms, |
Online Access: | http://dx.doi.org/10.18235/0001727 https://publications.iadb.org/en/wage-inequality-latin-america-learning-matched-employer-employee-data |
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dig-bid-node-190762020-07-01T19:40:10ZWage Inequality in Latin America: Learning from Matched Employer-Employee Data 2018-08-29T00:00:00+0000 http://dx.doi.org/10.18235/0001727 https://publications.iadb.org/en/wage-inequality-latin-america-learning-matched-employer-employee-data Inter-American Development Bank Income Equality Workforce and Employment Wage E24 - Employment • Unemployment • Wages • Intergenerational Income Distribution • Aggregate Human Capital • Aggregate Labor Productivity D22 - Firm Behavior: Empirical Analysis J08 - Labor Economics Policies J31 - Wage Level and Structure • Wage Differentials Wage inequality; Matched Employer-Employee Data; Firms Inequality in Latin America fell substantially in the early 2000s. In this paper, we take advantage of administrative matched employee-employed data in Brazil, Chile and Ecuador to examine whether these inequality trends held in the formal sector, as well. We document a significant decrease in the log variance of earnings in Brazil and Ecuador in the early 2000s, whereas inequality in Chile between 2008 and 2015 remained largely flat. In this context, we find that inequality among salaried workers is largely a between-firm phenomenon across these three countries. We expand on our descriptive analysis and estimate an additive worker and firm fixed effects model to understand the driving factors behind inequality in the region. We find a significant decline in between-firm inequality in Brazil and a modest one in Chile. We last focus our attention on the commodities and manufacturing sectors, which were directly exposed to two large external shocks, the commodity-boom and the ''China Shock". We find an increase in inequality in the former sector accompanied by an reduction in inequality in the latter across the region. Inter-American Development Bank Ercio Muñoz Graciana Rucci Fernando Saltiel Sergio Urzúa application/pdf IDB Publications Brazil Chile Ecuador Latin America en |
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Income Equality Workforce and Employment Wage E24 - Employment • Unemployment • Wages • Intergenerational Income Distribution • Aggregate Human Capital • Aggregate Labor Productivity D22 - Firm Behavior: Empirical Analysis J08 - Labor Economics Policies J31 - Wage Level and Structure • Wage Differentials Wage inequality; Matched Employer-Employee Data; Firms Income Equality Workforce and Employment Wage E24 - Employment • Unemployment • Wages • Intergenerational Income Distribution • Aggregate Human Capital • Aggregate Labor Productivity D22 - Firm Behavior: Empirical Analysis J08 - Labor Economics Policies J31 - Wage Level and Structure • Wage Differentials Wage inequality; Matched Employer-Employee Data; Firms |
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Income Equality Workforce and Employment Wage E24 - Employment • Unemployment • Wages • Intergenerational Income Distribution • Aggregate Human Capital • Aggregate Labor Productivity D22 - Firm Behavior: Empirical Analysis J08 - Labor Economics Policies J31 - Wage Level and Structure • Wage Differentials Wage inequality; Matched Employer-Employee Data; Firms Income Equality Workforce and Employment Wage E24 - Employment • Unemployment • Wages • Intergenerational Income Distribution • Aggregate Human Capital • Aggregate Labor Productivity D22 - Firm Behavior: Empirical Analysis J08 - Labor Economics Policies J31 - Wage Level and Structure • Wage Differentials Wage inequality; Matched Employer-Employee Data; Firms Inter-American Development Bank Wage Inequality in Latin America: Learning from Matched Employer-Employee Data |
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Inequality in Latin America fell substantially in the early 2000s. In this paper, we take advantage of administrative matched employee-employed data in Brazil, Chile and Ecuador to examine whether these inequality trends held in the formal sector, as well. We document a significant decrease in the log variance of earnings in Brazil and Ecuador in the early 2000s, whereas inequality in Chile between 2008 and 2015 remained largely flat. In this context, we find that inequality among salaried workers is largely a between-firm phenomenon across these three countries. We expand on our descriptive analysis and estimate an additive worker and firm fixed effects model to understand the driving factors behind inequality in the region. We find a significant decline in between-firm inequality in Brazil and a modest one in Chile. We last focus our attention on the commodities and manufacturing sectors, which were directly exposed to two large external shocks, the commodity-boom and the ''China Shock". We find an increase in inequality in the former sector accompanied by an reduction in inequality in the latter across the region. |
author2 |
Ercio Muñoz |
author_facet |
Ercio Muñoz Inter-American Development Bank |
topic_facet |
Income Equality Workforce and Employment Wage E24 - Employment • Unemployment • Wages • Intergenerational Income Distribution • Aggregate Human Capital • Aggregate Labor Productivity D22 - Firm Behavior: Empirical Analysis J08 - Labor Economics Policies J31 - Wage Level and Structure • Wage Differentials Wage inequality; Matched Employer-Employee Data; Firms |
author |
Inter-American Development Bank |
author_sort |
Inter-American Development Bank |
title |
Wage Inequality in Latin America: Learning from Matched Employer-Employee Data |
title_short |
Wage Inequality in Latin America: Learning from Matched Employer-Employee Data |
title_full |
Wage Inequality in Latin America: Learning from Matched Employer-Employee Data |
title_fullStr |
Wage Inequality in Latin America: Learning from Matched Employer-Employee Data |
title_full_unstemmed |
Wage Inequality in Latin America: Learning from Matched Employer-Employee Data |
title_sort |
wage inequality in latin america: learning from matched employer-employee data |
publisher |
Inter-American Development Bank |
url |
http://dx.doi.org/10.18235/0001727 https://publications.iadb.org/en/wage-inequality-latin-america-learning-matched-employer-employee-data |
work_keys_str_mv |
AT interamericandevelopmentbank wageinequalityinlatinamericalearningfrommatchedemployeremployeedata |
_version_ |
1806237562753253376 |