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Ageing Poorly? Accounting for the Decline in Earnings Inequality in Brazil, 1995-2012 Francisco Ferreira, PhD1; Sergio Firpo, PhD2; Julián Messina, PhD3.

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Presentation on theme: "Ageing Poorly? Accounting for the Decline in Earnings Inequality in Brazil, 1995-2012 Francisco Ferreira, PhD1; Sergio Firpo, PhD2; Julián Messina, PhD3."— Presentation transcript:

1 Ageing Poorly? Accounting for the Decline in Earnings Inequality in Brazil, Francisco Ferreira, PhD1; Sergio Firpo, PhD2; Julián Messina, PhD3 1World Bank and Institute for the Study of Labor (IZA), 2Insper Institute of Education and Research and Institute for the Study of Labor (IZA), 2IInter-American Development Bank and Institute for the Study of Labor (IZA) What accounts for the substantial decline of earnings inequality between 1995 and 2012 in Brazil? Methodology Introduction Figure 1. The Evolution of Inequality in Brazil Sharp household income inequality decline in Brazil, by an large driven by labor market dynamics The Gini coefficient of labor earnings fell by nearly 9 Gini points (almost 20%) between 1995 and 2012. Two distinct subperiods is low growth with slow inequality decline is high growth with stronger inequality reduction Objective Use recent decomposition methods based on re-centered influence function (RIF) regressions to estimate the quantitative impact of five groups of candidate explanatory factors on changes in the Brazilian earnings distribution. For each group of factors, what part of the decline in inequality can be attributed to: Composition effects. Changes in the distribution of observable worker characteristics. Pay structure effects. Changes in the remuneration of observable worker characteristics. Analyze differences in the roles played by each factor across subperiods (1995/2002/2012). Results Table 1. Decompositions results: Changes in Inequality, Gini, Composition Structure Total Education 4.11** -0.16 3.95** Potential Experience -0.39** -3.12** -3.52** Minimum Wage 1.13** 0.07** 1.20** Formality Status -0.32** -1.14** -1.46** Race and Gender -0.27** -1.59** -1.86** Region and Urban -0.03** -1.27** -1.29** Economic Sector -0.22** 2.16 1.94 Constant -7.91** N 484,054 Note:. **, * and + denote statistical significance at the 1% ,5% and 10% levels, respectively. The Gini coefficient is expressed in percentage points and goes from 0 (perfect equality) to 100 (perfect inequality). Standard errors are calculated with the delta method. Data Overall Post 40.82** Pre 49.77** Difference -8.95** Composition 4.01** Structure -12.96** Pesquisa Nacional por Amostra de Domicílios (PNAD). Annual household survey carried out by the Instituto Brasileiro de Geografía e Estatística (IBGE). Period: Wage measure: total gross monthly individual labor earnings. Sample for analysis: Working age population: Men and women. Rural and urban areas. Employees and self employed. Formal and informal employees. Falling Inequality and its Five Potential Drivers Composition effects Figure 3. Decomposition results: Changes in Earnings by Percentile, Human Capital Education: Rising levels of education attainment (population with at least 10 years of schooling doubled from 25% to 50%) Experience: Ageing of the labor force (population aged 30 or over increased from 64% to 69%) Demographics Rising female participation (from 38% to 42% as share of total labor force) Proportion of non-white workers in labor force increased by 8 p.p. Institutions Massive real minimum wage increase (by 103% over the full period) Increase of employees with formal contracts (almost a fifth) Geography Urbanization of labor force  rural share of the working-age population decreased by 38%, from 16% to 10% of the total. Sectoral distribution Reduction in the proportion of workers in agriculture - Expansion of the construction sector. Structure effects A more level playing field? Reduction of wage gaps: Men-Women: fell from 35% to 26%. Black-White: fell from 13% to 8%. Formal-Informal sector employees: fell from 13% to 2%. Declining Human Capital premiums Returns to both education and experience fell over the period: Figure 2. Education and Experience Premium by Year. Conclusions Decline in earnings inequality between 1995 and 2012 was driven primarily by changes in the structure of remuneration in the Brazilian labor market. Educational upgrade was roughly neutral for inequality dynamics. The composition effect was inequality enhancing, but the decline of the education premium pulled inequality down. Important driver of the observed dynamics  Reduction in the experience premium. Other changes in pay structure that contributed to declining inequality  Reductions in: Gender – Racial – Urban-rural wage gaps Formal and informal wage gap. The minimum wage reduced inequality during , but increased inequality in the slow growth period because of increasing non-compliance and self-employment Contact References Julián Messina Inter-American Development bank Website: Phone: Blinder, Alan S (1973) “Wage Discrimination: Reduced Form and Structural Estimates”, Journal of Human Resources, 8: Firpo, Sergio, Nicole M. Fortin and Thomas Lemieux (2009), “Unconditional Quantile Regressions”, Econometrica, 77 (3): Oaxaca, Ronald (1973) “Male-Female Wage Differentials in Urban Labor Markets”, International Economic Review 14 (3): World Bank (2016): Taking on Inequality: Poverty and Shared Prosperity Report Washington, DC: World Bank Publications.


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