A nonpaprametric approach to evaluate the impact of contextual variables on the agricultural research efficiency in Brazil.

In this paper we measure technical efficiency for each of Embrapa (Brazilian Agricultural Research Corporation) research centers. We model DEA efficiency as a function of contextual variables: revenue generation capacity, partnership intensity, improvement of administrative processes, and impact of technologies generated by the research centers. Production is modeled with random and inefficient errors, in a manner similar to stochastic frontiers. The assessment of significance for the set of contextual variables is carried out by means of linear programming and goodness of fit tests and has a nonparametric basis. We conclude that there is joint significance of all contextual variables

Análise fatorial e análise de envoltória de dados na construção de indicadores e determinação de pesos em modelos de produção com respostas múltiplas.

Faz-se uso da análise fatorial e da análise de envoltória de dados (DEA) para definir uma medida de desempenho para aos centros de pesquisa da Empresa Brasileira de Pesquisa Agropecuária. Respostas múltiplas são agrupadas em três categorias de produção e suas ordenações são estudadas, via análise fatorial, dentro de cada categoria. Um sistema de pesos para cada categoria é definido de forma independente de rotações fatoriais, o que conduz a um conjunto de escores de produção de dimensão três. As medidas de desempenho têm por base um modelo de produção DEA-CCR com três produtos e três insumos. É também proposto um índice de alcance de metas gerenciais para as dimensões de produção

Um sistema de informação gerencial para a avaliação e o acompanhamento da produção de pesquisa agropecuária no Brasil.

Apresenta-se neste artigo um sistema de avaliação de produção de pesquisa em uso na Empresa Brasileira de Pesquisa Agropecuária (Embrapa). O sistema utiliza-se de medidas de produtividade e eficiência de produção com base na Análise de Envoltória de Dados. O processo de avaliação fornece uma ferramenta gerencial automatizada extremamente útil. Além de indicar direções de melhoria para a produção técnica e científica da empresa, serve ao propósito de identificar fatores causais de eficiência em bases estatísticas

Região de viabilidade e comparação de grupos para a performance DEA não arquimediana via regressão fracionada.

Considera-se a utilização da constante não arquimediana em modelos DEA-CCR. A aplicação de interesse é definida pela medida de performance dos centros de pesquisa da Empresa Brasileira de Pesquisa Agropecuária. Caracteriza-se uma região de viabilidade e sugere-se um valor para a constante. Tipos de DMUs são, então, comparados por meio do uso de regressão fracionada e do método da máxima quase-verossimilha nça. Conclui-se pela dominância dos centros de pesquisa do tipo produto. As medidas de performance clássica DEA-CCR e com restrições de folga não nula pela constante não arquimediana têm correlação de Spearman superior a 90%

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

Scale of operation, allocative inefficiencies and separability of inputs and outputs in agricultural research: Embrapa case study.

In this article we consider some properties of concern for research production at Embrapa. We address questions related to statistical tests for the scale of operation, the presence of allocative inefficiencies and separability of inputs and outputs. The production process is assessed by nonparametric methods with the use of a Data Envelopment Analysis frontier. The period of concern is 2002-2009. We conclude that Embrapa technology shows variable returns to scale, shows mild allocative inefficiencies in sub-periods, and is separable in inputs and outputs

Improving agricultural economic efficiency in Brazil.

In this article, we use Brazilian census data (1995/1996 and 2006) to model agricultural production at the state level in Brazil. Cost-efficiency measurements are computed using data envelopment analysis techniques, and the response is assessed via fractional regression. We examine the effects of time, geographic region, education, and investment in agricultural research on economic efficiency. We found that investment in agricultural research and regional dummies have a significant effect on efficiency measurements. On average, South and Southeast states are more efficinet than other states. An increase in cost efficiency can be accomplishe through investment in agricultural research

Conditional FDH efficiency, income dispersion and market imperfections: the case of the Brazilian agricultural sensus of 2006.

In this article we assess the effect of market imperfections and income inequality on rural production efficiency. The analysis is carried out using the notion of stochastic conditional efficiency computed in terms of free disposal hull (FDH) efficiency measurements. Free disposal hull and conditional FDH are output oriented with variable returns scale

Alternative approaches to evaluate experts perceptions: an application to agriculture in Brazil.

Governments intervene in agriculture via public policies. It is the objective of this work to identify critical themes for public policies in market, production, and government regulation. Thus, based on a set of ten main groups of agricultural risks and the perceptions of experts relative to both the importance of these themes and the intensity of the corresponding government policies to relieve risk effects, we rank the themes using multicriteria methods. We particularly discuss Thurstone?s law of categorical judgments and the Saaty?s analytic hierarchy process. The two approaches lead to similar results. Infrastructure and logistics are regarded as the most important item for both methods from the perspective of theme importance, and they are the least important from the perspective of the intensity of public policies

Management of agricultural research center in Brazil: a DEA application using a dynamic GMM approach.

In this paper, we measure the performance for each of the Brazilian Agricultural Research Corporation research center by means of a Data Envelopment Analysis model. Performance data are available for a panel covering the period 2002-2009. The approach is instrumentalist, inte sense of Ramalho, Ramalho, and Henriques (2010). We investigate the effects onf performance of contextual variable indicator related to the intensity of partnerships and revenue generation. For this purpose, we propose a fractional nonlinear regression model and dynamic GGM 9Generalized Method of Moments) estimation. We do not rule out the endogeneity of the contextual variables, cross-sectional correlation or autocorrelation within the panel. We conclude that revenue generation and previous performance scores are statistically significant and positively associated with actual performance