Inference in Dynamic, Nonparametric Models of Production for General Technologies

Leopold Simar and Paul W. Wilson
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Paul W. Wilson: Clemson University

No 2024028, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: Nonparametric envelopment estimators are often used to estimate the attainable set and its efficient boundary, and to assess efficiency and changes in productivity. Kneip et al. [11] provide asymptotic results that can be used to make inference about expected changes in productivity measured by Malmquist indices and about the sources of productivity changes. These results require convexity of the attainable set, but in a number of situations this assumption is questionable. Recently, Kneip et al. [12] extend these results to allow for possibly non-convex technologies where the DEA estimators are known to be inconsistent. This paper summarizes these results, and explains how researchers should choose the appropriate method in a particular application.

Keywords: Nonparametric production frontiers; DEA; FDH; Malmquist Indices (search for similar items in EconPapers)
Pages: 12
Date: 2024-09-03
Note: In: A. Emrouznejad, e.a. (eds), Advances in the Theory and Applications of Performance Measurement and Management, Springer, 2024, p. 9-20
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Related works:
Chapter: Inference in Dynamic, Nonparametric Models of Production for General Technologies (2024)
Working Paper: Inference in Dynamic, Nonparametric Models of Production for General Technologies (2023)
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