A robust poverty profile for Brazil using multiple data sources

This paper presents a poverty profile for Brazil, based on three different sources of household data for 1996. We use PPV consumption data to estimate poverty and indigence lines. “Contagem” data is used to allow for an unprecedented refinement of the country’s poverty map. Poverty measures and shares are also presented for a wide range of population subgroups, based on the PNAD 1996, with new adjustments for imputed rents and spatial differences in cost of living. Robustness of the profile is verified with respect to different poverty lines, spatial price deflators, and equivalence scales. Overall poverty incidence ranges from 23% with respect to an indigence line to 45% with respect to a more generous poverty line. More importantly, however, poverty is found to vary significantly across regions and city sizes, with rural areas, small and medium towns and the metropolitan peripheries of the North and Northeast regions being poorest.

Robust statistical modeling of portfolios

Atypical points in the data may result in meaningless e±cient frontiers. This follows since portfolios constructed using classical estimates may re°ect neither the usual nor the unusual days patterns. On the other hand, portfolios constructed using robust approaches are able to capture just the dynamics of the usual days, which constitute the majority of the business days. In this paper we propose an statistical model and a robust estimation procedure to obtain an e±cient frontier which would take into account the behavior of both the usual and most of the atypical days. We show, using real data and simulations, that portfolios constructed in this way require less frequent rebalancing, and may yield higher expected returns for any risk level.

Country factors and the dynamic modeling of capital structure : an empirical study of latin american firms

Desenvolvemos modelos de ajuste parcial e de duration para testar a relevância de fatores específicos de países na determinação da estrutura de capital de empresas listadas nas bolsas de valores brasileira, chilena e mexicana. Utilizamos dados em painel, em um período que se estende do quarto trimestre de 1996 ao segundo trimestre de 2010, abrangendo 4403 observações relacionadas a 139 empresas diferentes. Os resultados obtidos sugerem que a dinâmica da estrutura de capital varia por país e que idiossincrasias locais são determinantes-chave dos níveis de alavancagem das empresas. Não detectamos comportamento explicado pela Teoria de Trade Off entre as empresas brasileiras, chilenas e mexicanas, o que indica que teorias alternativas possam comandar os processos de decisão de financiamento dos gestores latino americanos.

Factors affecting the technical efficiency of production of the Brazilian banking system : a comparison of four statistical models in the context of data envelopment analysis

This paper uses an output oriented Data Envelopment Analysis (DEA) measure of technical efficiency to assess the technical efficiencies of the Brazilian banking system. Four approaches to estimation are compared in order to assess the significance of factors affecting inefficiency. These are nonparametric Analysis of Covariance, maximum likelihood using a family of exponential distributions, maximum likelihood using a family of truncated normal distributions, and the normal Tobit model. The sole focus of the paper is on a combined measure of output and the data analyzed refers to the year 2001. The factors of interest in the analysis and likely to affect efficiency are bank nature (multiple and commercial), bank type (credit, business, bursary and retail), bank size (large, medium, small and micro), bank control (private and public), bank origin (domestic and foreign), and non-performing loans. The latter is a measure of bank risk. All quantitative variables, including non-performing loans, are measured on a per employee basis. The best fits to the data are provided by the exponential family and the nonparametric Analysis of Covariance. The significance of a factor however varies according to the model fit although it can be said that there is some agreements between the best models. A highly significant association in all models fitted is observed only for nonperforming loans. The nonparametric Analysis of Covariance is more consistent with the inefficiency median responses observed for the qualitative factors. The findings of the analysis reinforce the significant association of the level of bank inefficiency, measured by DEA residuals, with the risk of bank failure.

Information mining and visualization of data from the Brazilian Supreme Court (STF): a case study

EMAp - Escola de Matemática Aplicada