Heteroscedasticity in Stochastic Frontier Models: A Monte Carlo Analysis

Paper number: 99/14

Paper date: March 1999

Year: 1999

Paper Category: Discussion Paper

Authors

C Guermat
University of Exeter

and

K Hadri
City University, London

March 1999

Abstract

This paper uses Monte Carlo experimentation to investigate the finite sample properties of the maximum likelihood (ML) estimators of the half-normal stochastic frontier production functions in the presence of heteroscedasticity. It is found that when heteroscedasticity exists correcting for it leads not only to a substantial improvement of the statistical properties of estimators but also to improved efficiency and ranking measures. On the other hand correcting for heteroscedasticity when there is none has serious adverse results. Hence, there is a need for testing for heteroscedasticity and if there is any the appropriate correction should be made.

JEL Classification Nos: C15, C21, C24, D24, Q12
Keywords: Stochastic frontier production, heteroscedasticity, technical efficiency, Monte Carlo, maximum likelihood estimation, tests

Corresponding Author: Kaddour Hadri, Department of Economics, City University, London, EC1 0HB, UK, tel: (44) 171 477 8919, fax (44) 171 477 8580, email: K.Hadri@city.ac.uk