Journal ArticleDOI
Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models
Léopold Simar,Paul W. Wilson +1 more
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In this paper, the authors provide a general methodology of bootstrapping in nonparametric frontier models and some adapted methods are illustrated in analyzing the bootstrap sampling variations of input efficiency measures of electricity plants.Abstract:
Efficiency scores of production units are generally measured relative to an estimated pro-duction frontier. Nonparametric estimators (DEA, FDH,···) are based on a finite sample of observed production units. The bootstrap is one easy way to analyze the sensitivity of efficiency scores relative to the sampling variations of the estimated frontier. The main point in order to validate the bootstrap is to define a reasonable data-generating process in this complex framework and to propose a reasonable estimator of it. This paper provides a general methodology of bootstrapping in nonparametric frontier models. Some adapted methods are illustrated in analyzing the bootstrap sampling variations of input efficiency measures of electricity plants.read more
Citations
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Journal ArticleDOI
Estimation and inference in two-stage, semi-parametric models of production processes
Léopold Simar,Paul W. Wilson +1 more
TL;DR: In this paper, a coherent data-generating process (DGP) is described for nonparametric estimates of productive efficiency on environmental variables in two-stage procedures to account for exogenous factors that might affect firms’ performance.
Journal ArticleDOI
Data envelopment analysis (DEA) - Thirty years on
Wade D. Cook,Lawrence M. Seiford +1 more
TL;DR: A sketch of some of the major research thrusts in data envelopment analysis (DEA) over the three decades since the appearance of the seminal work of Charnes et al. is provided.
Book ChapterDOI
The Econometric Approach to Efficiency Analysis
TL;DR: The Econometrics of Panel DataSpringer Handbook of Science and Technology IndicatorsPanel Data and Econometric Methods for Productivity Measurement and Efficiency Analysis as discussed by the authors, and a Practitioner's Guide to Stochastic Frontier Analysis Using StataBenchmarking for Performance EvaluationEssays on Microeconomics and Industrial OrganisationHealth System EfficiencyInternational Journal of Production EconomicsEconometric Analysis of Model Selection and Model TestingInternational Applications of Productivity and Efficiency analysisAdvanced Robust and Nonparametric Methods in Efficiency Analysis
Journal ArticleDOI
Statistical inference in nonparametric frontier models: the state of the art
Léopold Simar,Paul W. Wilson +1 more
TL;DR: In this article, the authors define a statistical model allowing determination of the statistical properties of the nonparametric estimators in the multi-output and multi-input case, and provide the asymptotic sampling distribution of the FDH estimator in a multivariate setting and of the DEA estimator for the bivariate case.
Journal ArticleDOI
A general methodology for bootstrapping in non-parametric frontier models
Leâ Opold Simar,Paul W. Wilson +1 more
TL;DR: This paper proposes a general methodology for bootstrapping in frontier models, extending the more restrictive method proposed in Simar & Wilson (1998) by allowing for heterogeneity in the structure of efficiency.
References
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Book
An introduction to the bootstrap
Bradley Efron,Robert Tibshirani +1 more
TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
Journal ArticleDOI
Measuring the efficiency of decision making units
TL;DR: A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs and methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs.
BookDOI
Density estimation for statistics and data analysis
TL;DR: The Kernel Method for Multivariate Data: Three Important Methods and Density Estimation in Action.
Journal ArticleDOI
Bootstrap Methods: Another Look at the Jackknife
TL;DR: In this article, the authors discuss the problem of estimating the sampling distribution of a pre-specified random variable R(X, F) on the basis of the observed data x.