SOCIAL POLICY AS REGIONAL POLICY: MARKET AND NONMARKET FACTORS DETERMINING REGIONAL INEQUALITY

We decompose the recent changes in regional inequality in Brazil into its components, highlighting the role of spatially blind social programs. We aggregate personal income micro data to the state level, differentiating nine income sources, and assess the role of these components in the observed changes in regional inequality indicators. The main results indicate that the largest part of the recent reduction in regional inequality is related to the dynamics of the market-related labor income, with manufacturing and services favoring deconcentration. Labor income in agriculture, retirement and pensions, and property rents and other sources favored concentration. The social programs Bolsa Familia and Beneficios de Prestacao Continuada are responsible for more than 24 percent of the reduction in inequality, although they account for less than 1.7 percent of the disposable household income. Such positive impact on regional concentration is impressive, since the goals of the programs are clearly nonspatial.

Infant mortality in Brazil, 1980-2000: A spatial panel data analysis

Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.