摘要: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.
其他摘要: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.