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Nonparametric estimation of concave production technologies by entropic methods
Author(s) -
Allon Gad,
Beenstock Michael,
Hackman Steven,
Passy Ury,
Shapiro Alexander
Publication year - 2007
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.918
Subject(s) - nonparametric statistics , production (economics) , econometrics , estimation , computer science , maximum likelihood , mathematical optimization , economics , mathematics , statistics , microeconomics , management
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. Copyright © 2007 John Wiley & Sons, Ltd.