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Pobreza e o Sistema de Seguridade Social Rural no Brasil

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  • Marinho, Emerson
  • Araújo, Jair

Abstract

This work aims at measuring the impact of the monetary benefits from social security retirement on poverty using panel data for the rural regions of the Brazilian states in the 1995-2005 period. The analysis is performed by controlling for other poverty determinants, such as the per capita agricultural product, income distribution, measured by the GINI index, the average of school years and the number of unemployed people over 10 years of age. The method of analysis relies on a dynamic econometric model which is estimated by the Generalized Method of Moments system, developed by Arellano e Bond (1991) and Blundell e Bond (1998). The results suggest that the retirement benefits have no direct impact on rural poverty in Brazil, whereas the average of school years and the per capita agricultural product are relevant factors for reducing rural poverty. On the other hand, the number of unemployed people has a positive effect on the increase of poverty, while the effect of income concentration is statistically insignificant.

Suggested Citation

  • Marinho, Emerson & Araújo, Jair, 2010. "Pobreza e o Sistema de Seguridade Social Rural no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 64(2), June.
  • Handle: RePEc:fgv:epgrbe:v:64:y:2010:i:2:a:1476
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    1. Rafael Perez Ribas & Ana Flávia Machado & André Braz Golgher, 2006. "Fluctuations and persistence in poverty: a transient-chronic decomposition model for pseudo-panel data," Textos para Discussão Cedeplar-UFMG td290, Cedeplar, Universidade Federal de Minas Gerais.
    2. John P. Formby & Gary A. Hoover & Hoseong Kim, 2001. "Economic Growth and Poverty in the United States," Journal of Income Distribution, Ad libros publications inc., vol. 10(3-4), pages 1-1, September.
    3. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    4. Sonia Rocha, 2006. "Pobreza e indigência no Brasil: algumas evidências empíricas com base na PNAD 2004 [Poverty and indigence in Brazil: empirical evidence based on the 2004 PNAD]," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), vol. 16(2), pages 265-299, May-Augus.
    5. Ahn, Seung C. & Schmidt, Peter, 1995. "Efficient estimation of models for dynamic panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 5-27, July.
    6. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    7. Frederico Luiz Barbosa de Melo & Ana Flávia Machado, 2006. "Vulnerabilidade À Pobreza No Mercado De Trabalho Em Belo Horizonte: Uma Análise A Partir Da Ped," Anais do XII Semin·rio sobre a Economia Mineira [Proceedings of the 12th Seminar on the Economy of Minas Gerais], in: João Antonio de Paula & et alli (ed.),Anais do XII Seminário sobre a Economia Mineira [Proceedings of the 12th Seminar on the Economy of Minas Gerais], Cedeplar, Universidade Federal de Minas Gerais.
    8. 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.
    9. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    10. Windmeijer, Frank, 2005. "A finite sample correction for the variance of linear efficient two-step GMM estimators," Journal of Econometrics, Elsevier, vol. 126(1), pages 25-51, May.
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