Nonparametric estimation of concave production technologies by entropic methods

Gad Allon, Michael Beenstock (), Steven Hackman, Ury Passy and Alex Shapiro
Additional contact information
Gad Allon: Northwestern University
Steven Hackman: Georgia Tech
Ury Passy: Technion
Alex Shapiro: Georgia Tech

Econometrics from University Library of Munich, Germany

Abstract: An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, bases on the priciple of maximum likelihood, uses entropic distance and concvex programming techniques to estimate production functions.

Keywords: convex programming; production functions; entropy (search for similar items in EconPapers)
JEL-codes: C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Pages: 30 pages
Date: 2005-12-06
New Economics Papers: this item is included in nep-ecm and nep-eff
Note: Type of Document - pdf; pages: 30. Nonparametric estimation subject to shape constraints
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Nonparametric estimation of concave production technologies by entropic methods (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0512003

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