On the Consistency of the DEA-based Average Technical Efficiency Bootstrap
AbstractThis paper shows that the bootstrap algorithm for average technical efficiency by Atkinson and Wilson (1995) should be applied with great care for the Data Envelopment Analysis (DEA) estimator if the production frontier is stochastic. A stochastic frontier implies that the DEA estimator is inconsistent, which in turn leads to inconsistent and potentially highly misleading bootstrap confidence intervals. A Monte Carlo simulation study reveals that the bootstrap confidence interval coverage accuracy goes to zero as the sample size increases, even for small contributions of frontier variance to total frontier and efficiency variance.
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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 179.
Length: 14 pages
Date of creation: 05 Aug 1997
Date of revision:
Publication status: Published in Applied Economics Letters, 2000, pages 53-57.
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More information through EDIRC
Bootstrap confidence intervals; Consistency; Data Envelopment Analysis; Distance function; Monte Carlo simulation; Stochastic frontier;
Find related papers by JEL classification:
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- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
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