Data envelopment analysis (DEA) is compared to stochastic production function estimation (SPFE) in a noisy setting. The statistic of interest is the average efficiency estimator. Monte-Carlo simulations show that the mean squared error of the DEA-estimator even for considerable noise remains below the MSE of the SPFE analogue. A bootstrapping approach is designed to get some first-step statistical underpinning of this DEA average efficiency estimator. The coverage of the bootstrapping approximation to the distribution of this estimator is shown to be fairly good.Series: Department of Economics Working Paper Serie
Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) both approaches are usually u...
Abstract: This chapter is written for analysts and researchers who may use Data Envelopment Analysis...
One of the weak points of DEA (Data Envelopment Analysis) models indicated in literature[1,2] is the...
This article examines the potential benefits of solving a stochastic DEA model over solving a determ...
Robustness of DEA scale efficiency scores is investigared in the context of non-radial efficency mea...
Data envelopment analysis (DEA) measures relative efficiency among the decision making units (DMU) w...
Data Envelopment Analysis (DEA) is a widely applied nonparametric method for comparative evaluation ...
The validity of data envelopment analysis (DEA) efficiency estimators depends on the robustness of t...
Data envelopment analysis (DEA) has been widely used for measuring relative performance of universit...
Stochastic Data Envelopment Analysis (DEA) models have been introduced in the literature to assess t...
Endogeneity, and the distortions on the estimation of economic models that it causes, is a usual pro...
This thesis gives an overall view of the two most commonly used approaches for measuring the relati...
The agricultural productivity is often based on non-parametric models (DEA), or stochastic models (S...
The data envelopment analysis (DEA) model is extensively used to estimate efficiency, but no study h...
Non-parametric data envelopment analysis (DEA) estimators based on linear programming methods have b...
Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) both approaches are usually u...
Abstract: This chapter is written for analysts and researchers who may use Data Envelopment Analysis...
One of the weak points of DEA (Data Envelopment Analysis) models indicated in literature[1,2] is the...
This article examines the potential benefits of solving a stochastic DEA model over solving a determ...
Robustness of DEA scale efficiency scores is investigared in the context of non-radial efficency mea...
Data envelopment analysis (DEA) measures relative efficiency among the decision making units (DMU) w...
Data Envelopment Analysis (DEA) is a widely applied nonparametric method for comparative evaluation ...
The validity of data envelopment analysis (DEA) efficiency estimators depends on the robustness of t...
Data envelopment analysis (DEA) has been widely used for measuring relative performance of universit...
Stochastic Data Envelopment Analysis (DEA) models have been introduced in the literature to assess t...
Endogeneity, and the distortions on the estimation of economic models that it causes, is a usual pro...
This thesis gives an overall view of the two most commonly used approaches for measuring the relati...
The agricultural productivity is often based on non-parametric models (DEA), or stochastic models (S...
The data envelopment analysis (DEA) model is extensively used to estimate efficiency, but no study h...
Non-parametric data envelopment analysis (DEA) estimators based on linear programming methods have b...
Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) both approaches are usually u...
Abstract: This chapter is written for analysts and researchers who may use Data Envelopment Analysis...
One of the weak points of DEA (Data Envelopment Analysis) models indicated in literature[1,2] is the...