EFFECTS OF RURAL CREDIT ON MULTIDIMENSIONAL POVERTY IN RURAL BRAZIL
Rural Credit, Multidimensional Poverty, Alkire-Foster Method, Unconditional Quantile Regression, Spatial Econometrics.
Despite the agricultural sector presents a high performance in the Brazilian economy, the rural environment coexists with a high incidence of poverty and high concentration of income. Much of the literature on the subject has shown that rural credit can act as a mechanism to reduce these problems. In this sense, the objective of this work was to analyze the importance of the rural credit policy not only in its economic aspect, but also in the social one. In addition, the study sought to measure multidimensional poverty in rural areas, since, according to recent approaches to the phenomenon, it does not only mean lack of income, but also lack of education, basic sanitation, health, housing and employment. In order to achieve the proposed objectives, multidimensional poverty was measured based on the Alkire-Foster methodology, which allows verifying which are the dimensions of greatest need in rural areas of the country. Then, the effect of rural credit on differentiated levels of multidimensional poverty was analyzed using the unconditional quantile regression methodology and the distortion of poverty differentials. The survey data refer to microdata from the 2014 PNAD by IBGE. The results found that education is the dimension with the greatest contribution to multidimensional rural poverty in Brazil. In the regional analysis, the highest rates of multidimensional rural poverty were found in the Northeast and North of the country. In addition, it is tolerated that the rural credit policy needs to be applied in conjunction with other measures such as technical assistance and the promotion of human capital so that it has a potentiating effect on the reduction of multidimensional poverty.