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Journal ArticleDOI

Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models

Léopold Simar, +1 more
- 01 Jan 1998 - 
- Vol. 44, Iss: 1, pp 49-61
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TLDR
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.

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Citations
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Journal ArticleDOI

Estimation and inference in two-stage, semi-parametric models of production processes

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

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

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

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

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

The Measurement of Productive Efficiency

M. J. Farrell
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.
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