Statistical Inference in Nonparametric Frontier Models: the State of the Art

Leopold Simar and Paul Wilson

Working Papers from Catholique de Louvain - Institut de statistique

Abstract: 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.

Keywords: ECONOMETRICS; STATISTICAL ANALYSIS; ESTIMATION OF PARAMETERS (search for similar items in EconPapers)
JEL-codes: C10 C14 (search for similar items in EconPapers)
Pages: 36 pages
Date: 1999
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Citations: View citations in EconPapers (158)

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Journal Article: Statistical Inference in Nonparametric Frontier Models: The State of the Art (2000)
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Persistent link: https://EconPapers.repec.org/RePEc:fth:louvis:9904

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