Statistical Tests Based on Dea Efficiency Scores

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 1993). Specific tests described here address issues such as comparisons of efficiency of groups of DMAUs, existence of scale economies, existence of allocative inefficiency, separability and substitutabiluty 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.

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