Statistical inference and nonparametric efficiency: A selective survey |
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Authors: | S Grosskopf |
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Institution: | (1) Department of Economics, Southern Illinois University, 62901-4515 Carbondale, IL |
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Abstract: | The purpose of this paper is to provide a brief and selective survey of statistical inference in nonparametric, deterministic, linear programming-based frontier models. The survey starts with nonparametric regularity tests, sensitivity analysis, two-stage analysis with regression, and nonparametric statistical tests. It then turns to the more recent literature which shows that DEA-type estimators are maximum likelihood, and, more importantly the results concerning the asymptotic properties of these estimators. Also included is a discussion of recent attempts to employ resampling methods to derive empirical distributions for hypothesis testing. |
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Keywords: | Statistical inference nonparametric efficiency DEA estimators |
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