Marcos Aurélio Brambilla

The objective of this thesis was to evaluate poverty, inequality in income distribution and its impacts on migratory flows. The first essay aimed to analyze the spatial distribution of multidimensional poverty and to verify its convergence. The second essay aimed to analyze the spatial distribution of income inequality and the impact of education and the labor market on inequality in income distribution. Finally, the third essay aimed to evaluate the spatial distribution of migratory flows and the impact of poverty and inequality on the net migration rate. This work was based on information from the Demographic Censuses of 1991, 2000 and 2010. In order to meet the objectives, the exploratory analysis of spatial data was carried out and the spatial econometric approach was used. The results indicated that housing conditions and demography were the dimensions that contributed most to multidimensional poverty. In addition, it was identified that throughout the period, there was a higher incidence of multidimensional poverty in the North and Northeast regions and lower incidence in the South and Southeast regions. In turn, there was a higher incidence of income inequality in the North, Northeast and Central-West regions and lower incidence in the South and Southeast regions. In addition, it was observed a higher concentration of migratory flows in the state of São Paulo and in the Center-West region and lower incidence in the state of Minas Gerais and in the Northeast region. The study also indicated that Brazil presented absolute convergence of multidimensional poverty, mainly in the sub-period 2000/2010 and throughout the analyzed period (1991/2000) and indicated convergence in multidimensional poverty clubs in Brazil. It was possible to observe that the three clubs, North and Northeast, South and Southeast and Center-West, presented the negative and significant "β" coefficient, that is, for all clubs it was confirmed that the reduction of multidimensional poverty in poorer municipalities presented a pace faster than reducing poverty in richer counties. Moreover, the dimensions of work and housing conditions have contributed most to the convergence of multidimensional poverty. In addition, the second test confirmed the non-linear relationship between education and the labor market and inequality in income distribution. For the control variables, the results showed that the percentage control variable of male heads of household and the spatial spillovers of the labor supply rate and the percentage of male heads of household had a positive impact on the index of inequality in the distribution income and labor supply and employment rate and spatial spillovers of employment rate and age of heads of household had a negative impact on the inequality index in income distribution. Moreover, the study suggests that multidimensional poverty, income inequality, multidimensional poverty of neighboring municipalities, and inequality in the income distribution of neighboring municipalities had a negative impact on the migration rate. Since multidimensional poverty had a greater influence on the individual's decision to migrate.