Stochastic nonparametric envelopment of data (StoNED) combines the virtues of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) into a unified framework of frontier estimation. StoNED melds the nonparametric piece-wise linear DEA-type frontier with stochastic SFA-type inefficiency and noise terms. We show that the StoNED model can be estimated in the panel data setting in a...

Data envelopment analysis (DEA) is an axiomatic, mathematical programming approach to productive efficiency analysis and performance measurement. This paper shows that DEA can be interpreted as a nonparametric least squares regression subject to shape constraints on production frontier and sign constraints on residuals. Thus, DEA can be seen as a nonparametric counter-part of the corrected ordi...

In this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (DMUs) in stochastic data envelopment analysis (DEA) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. It is shown that this deterministic model can be converted to a quadratic programming model. So fa...

This article combines two techniques: data envelopment analysis (DEA) and Factor analysis (FA) to data reduction in decision making units (DMU). Data envelopment analysis (DEA), a popular linear programming technique is useful to rate comparatively operational efficiency of decision making units (DMU) based on their deterministic (not necessarily stochastic) input–output data and factor analysi...

in this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (dmus) in stochastic data envelopment analysis (dea) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. it is shown that this deterministic model can be converted to a quadratic programming model. so fa...

  Data envelopment analysis (DEA) is a nonparametric approach to evaluate theefficiency of decision making units (DMU) using mathematical programmingtechniques. Almost, all of the previous researches in stochastic DEA have been usedthe stochastic data when the inputs and outputs are normally distributed. But, thisassumption may not be true in practice. Therefore, using a normal distribution wi...

Data envelopment analysis (DEA) is a popular non-parametric approach to examine performance and productivity of airlines; however, it could not provide statistical information such as confidence intervals on the estimated efficiency scores. We combined stochastic frontier DEA into single framework disentangle noise ‘pure’ inefficiency from scores accordingly for Monte-Carlo simulation verified ...

Most, if not all, production technologies are stochastic. This article demonstrates how data envelopment analysis (DEA) methods can be adapted to accommodate stochastic elements in a state-contingent setting. Specifically, we show how observations on a random input, not under the control of the producer and not known at the time that variable input decisions are made, can be used to partition t...

The aim of this paper is to estimate the overall performance of mutual funds in Croatia in terms of their relative efficiency based on several performance indicators using data envelopment analysis (DEA). DEA is a non-parametric method that can provide an overall relative efficiency score of a certain fund given a number of risk, cost or reward or profitability measures. Since traditional mutua...