Roberta Blass Staub

Evolution of Bank Efficiency in Brazil: A DEA Approach

This paper investigates cost, technical and allocative efficiencies for Brazilian banks in the recent period (2000-2007). We use Data Envelopment Analysis (DEA) to compute efficiency scores. Brazilian banks were found to have low levels of economic (cost) efficiency compared to banks in Europe and in the US. For the period with high macroeconomic volatility (2000-2002) the economic inefficiency in Brazilian banks can be attributed mainly to technical inefficiency rather than allocative inefficiency. State-owned banks are significantly more cost efficient than foreign, private domestic and private with foreign participation. There is no evidence of differences in economic efficiency due to type of activity and bank size. These results may provide some useful guidance for financial regulators and bank managers.

Two-stage inference using data envelopment analysis efficiency measurements in univariate production models

This article addresses the problem of modeling data envelopment analysis (DEA) inefficiencies as dependent on contextual variables. For this purpose we use a statistical model similar in appearance to inefficiency component specifications in stochastic frontier models. The underlying production response is univariate. The approach is asymptotic and is based on a two-stage statistical inference procedure. In the first stage inefficiencies are estimated using DEA. In the second stage these estimates are modeled as if they were the true inefficiencies by means of a statistical model dependent on the contextual variables. To define this data generating process one could use a flexible family of distributions like the truncated normal. Theoretical inefficiencies are assumed to be independent but not identically distributed. Some of the asymptotic results implied by the two-stage inference procedure are inspected in finite samples by means of Monte Carlo simulations. The procedure is illustrated with an example where a deterministic production model is fitted to research data generated by the major state company responsible for agricultural research in Brazil.

Probabilistic measures of efficiency and the influence of contextual variables in nonparametric production models: an application to agricultural research in Brazil

In a research institution it is important to identify which management practices have influence on production efficiency. In this paper we assess the statistical significance of contextual variables type, size, financial resources acquisition, intensity of partnerships, processes improvements and management change. The analysis is carried out for the Brazilian Agricultural Research Corporation over the period 1999?2006. The statistical analysis uses a balanced dynamic panel data model. We conclude that only financial resources acquisition is statistically significant. The association with the production process is positive. We also found the two lag inertial components of the conditional FDH to unconditional FDH ratio statistically significant, indicating a 2-year effort to improve efficiency.

Influência de variáveis contextuais em medidas não-paramétricas de eficiência: uma aplicação com métodos de reamostragem

We evaluate three bootstrap techniques for the statistical analysis of a non parametric production model for which a DEA measure of efficiency is potentially affected by a set of exogenous factors. The application of interest relates to the assessment of the significance of the contextual variables income generation, processes improvement, intensity of partnerships, type and size on the technical efficiencies of Embrapas research centers. It is concluded that the bootstrap of the maximum likelihood estimator provides the best fit from the point of view of Pearson correlation between observed and predicted values and is the most informative in regard to the significance of the variables considered. With the exception of size all contextual variables are statistically significant. Income generation, processes improvement and intensity of partnerships are all positively associated with technical efficiency.

A Probabilistic Approach for Assessing the Significance of Contextual Variables in Nonparametric Frontier Models: An Application to Brazilian Banks

This article presents an empirical application illustrating the use of a nonparametric frontier model relying on a probabilistic definition of the production frontier. The significance of the variable nonperforming loans in productive efficiency is assessed, for a sample of Brazilian banks, using the concepts of condicional and unconditional efficiency measures, in a context where it is not necessary to impose any particular distribution for the production data. The analysis is robust relative to the assumptions of separability.

Persistence and mean reversion: analyzing sector indices for Brazil

Este artigo contribui para a literatura de testes da hipotese de passeio aleatorio examinando um novo conjunto de dados setoriais de acoes para o mercado Brasileiro e empregando um teste de razao de variâncias com percentis customizados. A rejeicao da hipotese de passeio aleatorio tem implicacoes para ambos os profissionais de mercado e academicos, pois a maioria dos modelos de aprecamento de ativos assume esta hipotese e os profissionais buscam padroes na historia de precos de ativos (implicitamente refutando a hipotese de passeio aleatorio). O artigo sugere que se pode usar a hipotese de passeio aleatorio para aprecar ativos no mercado acionario brasileiro.