Avaliação dos desempenhos econômico e socioambiental de sistemas modais de pecuária de cria com modelos dea com restrições aos pesos.

Este estudo avaliou o desempenho de 21 sistemas modais de produção de gado de corte que realizam apenas a fase de cria, em municípios de sete estados do Brasil. Foram propostos e aplicados dois modelos DEA BCC segundo enfoques distintos. O modelo econômico mede a capacidade de um sistema de produção de gerar receita com preservação da mata nativa, usando trabalho, capital e gastos correntes.No modelo socioambiental o fator de produção ?mão de obra? é output e o interesse é avaliar se capital e custos geram benefícios econômicos, ambientais e sociais. Restrições aos pesos foram impostas às variáveis de output de cada o modelo para explicitar os enfoques e impedir resultados incoerentes. Os resultados apontaram fontes de ineficiências em função de mão de obra com baixa qualificação e utilização de touros de qualidade questionável, situação comum nos sistemas extensivos, importantes gargalos dos sistemas pecuários como um todo

Estudo da sustentabilidade agrícola em um município amazônico com análise envoltória de dados.

O Conceito de sustentabilidade agrícola considera diferentes dimensões. Entretanto, tem como base a valorização dos recursos internos dos sistemas agrícolas produtivos, que se traduz pela manutenção desses sistemas de produção e, consequentemente, de sua produtividade, ao longo do tempo. Este artigo tem como objetivo medir a sustentabilidade de produtores agrícolas a partir de modelos Análise de Envoltória de Dados (Data Envelopment Analysis - DEA) com restrições aos pesos. Nesta abordagem, além de considerar várias dimensões, a medida de eficiência resultante é calculada de forma relativa. Foi usado um modelo no qual de explora o desempenho econômico-ambiental (variáveis: área total, mão-de-obra, custo, receita bruta, área com mata), para dois períodos de tempo, 1986 e 2002

Effectiveness in the prevention and control of tuberculosis – a comparative analysis of countries using data envelopment analysis

Dissertação de mestrado, Gestão de Unidades de Saúde, Faculdade de Economia, Universidade do Algarve, 2017Tuberculosis (TB) is the first cause of death from infectious diseases worldwide. The current panorama of restrictions that most of the countries are experiencing, makes it necessary to assess efficiency and effectiveness as the only way to provide guidance so that the investments made can have a sound basis of good practice and continuous improvement. The present study proposes to explore Data Envelopment Analysis (DEA) to assess countries performance in TB prevention and control, and in doing so establish comparisons between countries and identify good practices as a platform for improvement. To achieve these objectives, we used data regarding TB treatment success from 33 low and middle income countries. Our results show Bangladesh, Burundi, China and Pakistan as the only effective countries in our sample. Despite the variation of effectiveness not being substantial, our results show margin for great improvement and suggest that a better use of resources and more effective practices regarding TB prevention and control can be established for the non-effective countries. Moreover, our results also support DEA as a versatile tool for effective strategic planning and decision making.A Tuberculose é a primeira causa de morte por doenças infeciosas em todo o mundo. O atual panorama de restrições que a maioria dos países atravessa, reforça a avaliação da eficiência e efetividade, como a única forma de orientação para que os investimentos feitos assentem sobre uma base sólida de boas práticas e melhoria contínua. O presente estudo tem como objetivo explorar o uso da técnica Data Envelopment Analysis (DEA) por forma a analisar o desempenho dos países no que se refere ao controlo da Tuberculose e identificar boas práticas como uma plataforma de melhoria. Para esse efeito, utilizamos dados de 33 países de baixo e médio rendimento referentes ao sucesso de tratamento. Os resultados mostram que o Bangladesh, Burundi, China e Paquistão são os únicos países efetivos na nossa amostra. Apesar da variação da efetividade entre países não ser substancial, os resultados mostram margem para melhorias e sugerem que uma melhor utilização dos recursos e práticas mais efetivas de prevenção e controlo podem ser estabelecidas. Além disso, os nossos resultados também apoiam o DEA como uma ferramenta versátil para o planeamento estratégico e tomada de decisões efetivas

An extended multiple criteria data envelopment analysis model

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Several researchers have adapted the data envelopment analysis (DEA) models to deal with two inter-related problems: weak discriminating power and unrealistic weight distribution. The former problem arises as an application of DEA in the situations where decision-makers seek to reach a complete ranking of units, and the latter problem refers to the situations in which basic DEA model simply rates units 100% efficient on account of irrational input and/or output weights and insufficient number of degrees of freedom. Improving discrimination power and yielding more reasonable dispersion of input and output weights simultaneously remain a challenge for DEA and multiple criteria DEA (MCDEA) models. This paper puts emphasis on weight restrictions to boost discriminating power as well as to generate true weight dispersion of MCDEA when a priori information about the weights is not available. To this end, we modify a very recent MCDEA models in the literature by determining an optimum lower bound for input and output weights. The contribution of this paper is sevenfold: first, we show that a larger amount for the lower bound on weights often leads to improving discriminating power and reaching realistic weights in MCDEA models due to imposing more weight restrictions; second, the procedure for sensitivity analysis is designed to define stability for the weights of each evaluation criterion; third, we extend a weighted MCDEA model to three evaluation criteria based on the maximum lower bound for input and output weights; fourth, we develop a super-efficiency model for efficient units under the proposed MCDEA model in this paper; fifth, we extend an epsilon-based minsum BCC-DEA model to proceed our research objectives under variable returns to scale (VRS); sixth, we present a simulation study to statistically analyze weight dispersion and rankings between five different methods in terms of non-parametric tests; and seventh, we demonstrate the applicability of the proposed models with an application to European Union member countries

New developments in frontier models for objective assessments

This dissertation is the result of some innovative proposals, in the wide framework of production efficiency frontier models, that have the common goal of reducing subjective choices of the researcher by using, as far as possible, objective methods. In particular, the first proposal links the economic efficiency theory to the spatial econometrics with the aim of taking into account - in the efficiency evaluation of a productive unit - the neighborhood effects in a global way avoiding the subjective selection of a set of variables identifying territorial effects. The method called Spatial Stochastic Frontier Analysis (SSFA) has been published in Fusco and Vidoli (2013) for the production efficiency analysis and generalized in this thesis to be able to also analyze the cost efficiency. The second proposal, instead aims to introduce enhancements in the methods using frontier techniques to aggregate simple indicators in a composite indicator. Subjectivity is avoided in the identification of the set of aggregation weights necessary for constructing the composite indicator, in the definition of a preference structure among simple indicators and in the extreme values and outliers influence removal. The two methods proposed, called respectively Directional Benefit of the Doubt (D-BoD) and Robust Directional Benefit of the Doubt (RD-BoD), have been published in Fusco (2015) and Vidoli, Fusco and Mazziotta (2015). The dissertation consists of four parts: the first one introduces the foundations of the economic efficiency analysis and gives key economic concepts and definitions needed for a proper understanding of the following parts, focusing both on parametric and on nonparametric methods for cross-sectional and panel data and for mono-output and multi-output production processes; the second one discusses the fundamentals of the spatial econometrics, on the main connection proposals with the efficiency theory and shows in detail the SSFA method and the related R package called SSFA implemented to allow other researchers to use it; in the third part the concept of composite indicator and the required steps for its construction are discussed and D-BoD and RD-BoD are shown, moreover the related R package Compind is presented; all proposed methods have been tested both on simulated data and on real data and the results are shown in the fourth part. In the last part, two innovative applications, respectively on the estimation of non performing loans of commercial banks (Fusco and Maggi, 2016) and on the estimation of the local governments’ expenditure needs (Vidoli and Fusco, 2017) by using the efficiency and spatial theories, are also included