Statistical Inference in Nonparametric Frontier Models: the State of the Art
The economic literature proposes several nonparametric frontier estimators based on the idea of enveloping the data (FDH and DEA-type estimators). Many have claimed that FDH and DEA techniques are non-statistical, as opposed to econometric approaches where particular parametric expressions are posited to model the frontier. We can now define a statistical model allowing determinion of the statistical properties of the non-parametric estimators in the multi-output and multi-input case. This paper summarizes the results wihic are now available, and provides a brief guide to the existing literature. Stressing the role of hypotheses and inference, we show how the results can be used or adapted for practical purposes.
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- Simar, L. & Wilson, P.W., 1998.
"A General Methodology for Bootstrapping in Nonparametric Frontier Models,"
9811, Catholique de Louvain - Institut de statistique.
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"Sensitivity analysis of efficiency scores: how to bootstrap in nonparametric frontier models,"
CORE Discussion Papers RP
-1304, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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"Explaining Bank Failures: Deposit Insurance, Regulation, and Efficiency,"
The Review of Economics and Statistics,
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- Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
- SIMAR, Léopold & WILSON, Paul, 1996.
"Estimating and bootstrapping malmquist indices,"
CORE Discussion Papers
1996060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Kneip, Alois & Park, Byeong U. & Simar, L opold, 1998. "A Note On The Convergence Of Nonparametric Dea Estimators For Production Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 14(06), pages 783-793, December.
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