A DEA-based stochastic estimation framework is presented to evaluate contextual variables affecting productivity. Conditions are identified under which a two-stage procedure consisting of DEA followed by regression analysis yields consistent estimators of the impact of contextual variables. Conditions are also identified under which DEA in the first stage followed by maximum likelihood estimati...

on account of the existence of uncertainty, dea occasionally faces the situation of imprecise data, especially when a set of dmus include missing data, ordinal data, interval data, stochastic data, or fuzzy data. therefore, how to evaluate the efficiency of a set of dmus in interval environments is a problem worth studying. in this paper, we discussed the new method for evaluation and ranking i...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiency of decision making units (DMUs) which ‎consume the same types of inputs and producing the same types of outputs. Believing that future planning and predicting the ‎efficiency are very important for DMUs, this paper first presents a new dynamic random fuzzy DEA model (DRF-DEA) with ‎common weights (using...

This study investigated various factors explaining the technical, allocative and cost efficiency of Finnish hospitals using parametric frontier models and nonparametric DEA models. DEA scores were correlated to the same set of variables as efficiency scores by stochastic frontier models. Specialization, specialization in expensive DRGs, sufficiently high proportion of resident physicians and in...

The field of productive efficiency analysis is currently divided between two main paradigms: the deterministic, nonparametric Data Envelopment Analysis (DEA) and the parametric Stochastic Frontier Analysis (SFA). This paper examines an encompassing semiparametric frontier model that combines the DEA-type nonparametric frontier, which satisfies monotonicity and concavity, with the SFA-style stoc...

This paper provides simulation evidence concerning some statistical properties of two different approaches to technical efficiency estimation for multipleoutput production under noisy conditions: The Ray Frontier Approach (RFA) from Löthgren (1997) and DEA+ proposed in Gstach (1996). RFA, unlike earlier approaches in the realm of stochastic frontier analysis, is capable of efficiency estimation...

The purpose of this study is to evaluate the efficiency indices for 60 Brazilian electricity distribution utilities. These scores are obtained by DEA Data Envelopment Analysis and Bayesian Stochastic Frontier Analysis models, two techniques that can reduce the information asymmetry and improve the regulator’s skill to compare the performance of the utilities, a fundamental aspect in incentive r...

Literature of productive efficiency analysis is currently divided between two main paradigms: the parametric Stochastic Frontier Analysis (SFA) and the deterministic, nonparametric Data Envelopment Analysis (DEA). This paper develops a new encompassing framework that melds the SFA-style stochastic composite error term to the DEA-type nonparametric frontier that satisfies monotonicity and concav...