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A Bootstrap-Regression Procedure to Capture Unit Specific Effects In Data Envelopment Analysis

Evangelia Desli () and Subhash Ray ()

Indian Economic Review, 2004, vol. 39, issue 1, 89-110

Abstract: The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to bootstrapping in order to generate empirical distributions of efficiency scores. This procedure assumes that all firms have the same probability of getting an efficiency score from any specified interval within the [0,1] range. We propose a bootstrap procedure that empirically generates the conditional distribution of efficiency for each individual firm given systematic factors that influence its efficiency. Instead of resampling directly from the pooled DEA scores, we first regress these scores on a set of explanatory variables not included at the DEA stage and bootstrap the residuals from this regression. These pseudo-efficiency scores incorporate the systematic effects of unit-specific factors along with the contribution of the randomly drawn residual. Data from the U.S. airline industry are utilized in an empirical application.

Keywords: DEA; Kernel Smoothing; Reflection Method; Empirical Density (search for similar items in EconPapers)
JEL-codes: C15 C63 (search for similar items in EconPapers)
Date: 2004
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Indian Economic Review is currently edited by Pami Dua (Editor) & Ram Singh (Associate Editor) and Sunil Kanwar

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