Este trabalho investiga o impacto da escolaridade sobre a distribuição de renda do trabalho de Estados/ regiões do Brasil, usando um método semiparamétrico, seguindo DiNardo, Fortin e Lemieux (1996) e informações da PNAD de 1999. Foram construídas densidades contrafactuais, reponderando a distribuição da região/Estado mais pobre (Nordeste/Ceará) pelo perfil de escolaridade da mais rica (Sudeste/São Paulo). Resultados: entre 12% e 36% do diferencial de renda é explicado pelo diferencial de escolaridade; a reponderação pela escolaridade aumentou em cerca de 55% a renda média nos contrafactuais; a renda do contrafactual do Nordeste equivale a 93% da renda média brasileira; quanto mais elevado for o percentil de renda considerado, maior é a contribuição da diferença de escolaridade para a diferença de renda; a dispersão de renda das regiões mais pobres aumenta quando fornecemos a elas o nível de escolaridade das regiões mais ricas, mantendo-se o perfil salarial da região. Palavras-Chave distribuição de renda, educação, método semiparamétrico AbstractThis paper investigates the impact of education on income distribution of Brazilian states and regions, using a semi parametric method, following Dinardo, Fortin and Lemieux (1996) and dataset from the PNAD 1999. Contrafactual densities were constructed weighting the distribution of the poorest region/state (Northeast / Ceará) by the profile of education in the richer one (Southeast / São Paulo). Results: between 12% and 36% of the difference in income is explained by the educational differences; the weighting by education increased by about 55% the average income in counterfactuals; the counterfactual income of the Northeast amounts to 93% of the average Brazilian income; the higher the percentile considered income, the greater the contribution of the difference in schooling for the difference in income; and the income dispersion of the poorest regions increases when they provide the level of schooling of the richest regions, while the wage profile of the region is kept constant.

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In this paper, a derived-demand approach is proposed to explain the positive correlation and the synchronicity between the growth rates of commodity prices and of economic activity at the global level. The focus is on important traded commodities, whose supply function is very price inelastic in the short run, such as oil and major metal commodities. The paper contributions are as follows. First, the synchronicity of oil-price and global activity cycles is presented using the tools of the common-feature literature. Second, it is shown how to improve forecasts of global activity using commodity prices, noting that one observes the latter at an almost continuous-time basis, but the former at a much lower frequency and with considerable delay. Third, the usefulness of optimal forecast combinations for oil prices is discussed employing a wide array of macroeconomic and …nancial variables. The out-of-sample R 2 statistic for model combinations can reach up to about 14%, a major improvement over the previous literature.

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