Suchergebnisse

This study aimed to identify the major factors underlying the large discrepancy in poverty levels between two Brazilian racial groups: whites and Afro-Brazilians. We performed an Oaxaca-Blinder-type decomposition for nonlinear regressions in order to quantify the extent to which differences in observed geographic, sociodemographic, and labor characteristics (characteristics effect) account for this difference. The remaining unexplained part (coefficients effect) provides evidence on how these characteristics differentially impact on the risk of poverty in each group. A detailed decomposition of both effects allows the individual contribution of each characteristic to be determined. Our results show that the characteristics effect explains a large part of the discrepancy in poverty levels, with education and labor variables of household members explaining at least one half of the effect, and geographic and demographic variables accounting for the remainder. However, the unexplained part that remains significant has increased in importance in recent last years, and probably results from unequal access to high-quality education and the persistence of discrimination against colored workers in the labor market.

This paper compares the extent and the nature of the higher prevalence of poverty among disadvantaged ethnic groups in six Asian countries using demographic surveys. We first estimate a composite wealth index as a proxy for economic status, and analyze the magnitude of the ethnic gap in absolute and relative poverty levels across six countries and different ethnicities in those countries. Then, we use regression-based counterfactual analysis for explaining these ethnic differentials in poverty. We compare the actual differential in poverty with the gap that remains after disadvantaged ethnic groups are given the distribution of characteristics of the advantaged ones (by reweighting their densities using propensity scores). Our results show that there is a substantial cross-country variability in the extension, evolution, and nature of the ethnic poverty gap, which is as high as 50 percentage points or more in some specific cases in Nepal, Pakistan, or India. The gap in the latter country increased over the analyzed period, while it was reduced in the Philippines. Our analyses indicate that factors that contribute to ethnic disadvantaged groups being poorer are the strongly persistent high inequalities in education (e.g., India, Nepal, and Pakistan), in regional development (e.g., the Philippines) and the large urban-rural gap (e.g., Pakistan).