Statistical Inference in Nonparametric Frontier Models: the State of the Art
AbstractThe 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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Bibliographic InfoPaper provided by Catholique de Louvain - Institut de statistique in its series Papers with number 9904.
Length: 36 pages
Date of creation: 1999
Date of revision:
Contact details of provider:
Postal: Universite Catholique de Louvain, Institut de Statistique, Voie du Roman Pays, 34 B-1348 Louvain- La-Neuve, Belgique.
ECONOMETRICS ; STATISTICAL ANALYSIS ; ESTIMATION OF PARAMETERS;
Other versions of this item:
- Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
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