Statistical Tests Based on DEA Efficiency Scores

Rajiv D. Banker () and Ram Natarajan ()
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Rajiv D. Banker: Temple University
Ram Natarajan: The University of Texas at Dallas

Chapter Chapter 11 in Handbook on Data Envelopment Analysis, 2011, pp 273-295 from Springer

Abstract: Abstract This chapter is written for analysts and researchers who may use data envelopment analysis (DEA) to statistically evaluate hypotheses about characteristics of production correspondences and factors affecting productivity. Contrary to some characterizations, it is shown that DEA is a full-fledged statistical methodology, based on the characterization of DMU efficiency as a stochastic variable. The DEA estimator of the production frontier has desirable statistical properties, and provides a basis for the construction of a wide range of formal statistical tests (Banker RD Mgmt Sci. 1993;39(10):1265–73). Specific tests described here address issues such as comparisons of efficiency of groups of DMUs, existence of scale economies, existence of allocative inefficiency, separability and substitutability of inputs in production systems, analysis of technical change and productivity change, impact of contextual variables on productivity, and the adequacy of parametric functional forms in estimating monotone and concave production functions.

Keywords: Data envelopment analysis; Statistical tests (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1007/978-1-4419-6151-8_11

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