On Testing Equality of Distributions of Technical Efficiency Scores
Leopold Simar () and
Econometric Reviews, 2006, vol. 25, issue 4, 497-522
The challenge of the econometric problem in production efficiency analysis is that the efficiency scores to be analyzed are unobserved. Statistical properties have recently been discovered for a type of estimator popular in the literature, known as data envelopment analysis (DEA). This opens up a wide range of possibilities for well-grounded statistical inference about the true efficiency scores from their DEA estimates. In this paper we investigate the possibility of using existing tests for the equality of two distributions in such a context. Considering the statistical complications pertinent to our context, we consider several approaches to adapting the Li test to the context and explore their performance in terms of the size and power of the test in various Monte Carlo experiments. One of these approaches shows good performance for both the size and the power of the test, thus encouraging its use in empirical studies. We also present an empirical illustration analyzing the efficiency distributions of countries in the world, following up a recent study by Kumar and Russell (2002), and report very interesting results.
Keywords: Bootstrap; DEA; Kernel density estimation and tests (search for similar items in EconPapers)
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Working Paper: On testing equality of distributions of technical efficiency scores (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:taf:emetrv:v:25:y:2006:i:4:p:497-522
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