Nonparametric estimation of concave production technologies by entropic methods

Gad Allon; Michael Beenstock; Steven Hackman; Ury Passy; Alexander Shapiro

doi:10.1002/jae.918

Nonparametric estimation of concave production technologies by entropic methods

Gad Allon, Michael Beenstock^*, Steven Hackman, Ury Passy, Alexander Shapiro

^*Corresponding author for this work

Department of Economics

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, based on the principle of maximum likelihood, uses entropic distance and convex programming techniques to estimate production functions. Empirical applications are presented to demonstrate the feasibility of the methodology in small and large datasets.

Original language	English
Pages (from-to)	795-816
Number of pages	22
Journal	Journal of Applied Econometrics
Volume	22
Issue number	4
DOIs	https://doi.org/10.1002/jae.918
State	Published - Jun 2007

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Nonparametric estimation of concave production technologies by entropic methods

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