Backpropagation Neural Network versus Translog Model in Stochastic Frontiers: a Note Carlo Compatrison

C. Guermat and Kaddour Hadri ()

Discussion Papers from University of Exeter, Department of Economics

Abstract: Little attention has been given to the effects of functional form mis-specification on the estimation of stochastic frontier models and to the possibility of using backpropagation neural netwok as a flexible functional form to approximate the production or cost functions. This paper has two main aims. First, it uses Monte Carlo experimentation to investigate the effects of functional form mis-specification on the finite sample properties of the maximum likelihod (ML) estimators of the half-normal stochastic frontier production functions; second it compared the performance of backpropagation neural network with that of translog.

Keywords: ECONOMETRICS; STATISTICAL ANALYSIS; NETWORK ANALYSIS (search for similar items in EconPapers)
JEL-codes: C15 C21 C24 D24 (search for similar items in EconPapers)
Pages: 11 pages
Date: 1999
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:exe:wpaper:9916

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