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Determinantes Imediatos da Queda da Desigualdade de Renda Brasileira


  • Ricardo Paes de Barros
  • Mirela de Carvalho
  • Samuel Franco
  • Rosane Mendonça


Between 2001 e 2005, the degree of income inequality in Brazil declined sharply and continuously, reaching in 2005 the lowest level in the last 30 years. The Gini coefficient declined by almost 5%, and the ratio between the richest 20% and the poorest 20% declined more than 20%. This reduction on income inequality contributed to substantially reduce poverty and to improve the life?s conditions of the poorest, even in a period of relative per capita income stagnation. In spite of this decline, the degree of inequality in the country is steel extremely high. Therefore, it is essential that steps which are favorable to inequality reduction may be continued. In this way, it is essential to investigate the determinants of this recent decline in order to formulate more effective policies and interventions. In this paper, based on a series of counter factual simulations, we identify and quantify the contribution of proximately determinants responsible for this recent decline on inequality in Brazil. Between the findings we must highlight that around 50% of the decline on inequality resulted from the evolution of non labor income, although it represents less than 1/4 of the total income. Changes in the labor income explain around 1/3 of the observed decline on inequality, although it represents more than 3/4 of the total income. Finally, the reduction on the degree of association of these two sources of income also has an important role in the inequality decline.

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  • Ricardo Paes de Barros & Mirela de Carvalho & Samuel Franco & Rosane Mendonça, 2007. "Determinantes Imediatos da Queda da Desigualdade de Renda Brasileira," Discussion Papers 1253, Instituto de Pesquisa Econômica Aplicada - IPEA.
  • Handle: RePEc:ipe:ipetds:1253

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    1. V. V Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2002. "Can Sticky Price Models Generate Volatile and Persistent Real Exchange Rates?," Review of Economic Studies, Oxford University Press, vol. 69(3), pages 533-563.
    2. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    3. Rabanal, Pau & Rubio-Ramirez, Juan F., 2005. "Comparing New Keynesian models of the business cycle: A Bayesian approach," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1151-1166, September.
    4. Rodrigo Caputo & Felipe Liendo & Juan Pablo Medina, 2007. "New Keynesian Models for Chile in the Inflation-Targeting Period," Central Banking, Analysis, and Economic Policies Book Series,in: Frederic S. Miskin & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.), Monetary Policy under Inflation Targeting, edition 1, volume 11, chapter 13, pages 507-546 Central Bank of Chile.
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    Cited by:

    1. Marinho, Emerson & Araújo, Jair, 2010. "Pobreza e o Sistema de Seguridade Social Rural no Brasil," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 64(2), June.
    2. Marinho, Emerson & Linhares, Fabricio & Campelo, Guaracyane, 2011. "Os Programas de Transferência de Renda do Governo Impactam a Pobreza no Brasil?," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 65(3), September.
    3. Samir Cury & Allexandro Mori Coelh & Euclides Pedroso, "undated". "The Role of Income Transfer Programs in the Fall of Income Inequality in Brasil : a CGE Micro-Simulation Approach," EcoMod2007 23900017, EcoMod.

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