Heteroscedasticity in Stochastic Frontier Models: a Monte Carlo Analysis

C. Guermat and Kaddour Hadri ()

Discussion Papers from University of Exeter, Department of Economics

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.

Keywords: STATISTICAL ANALYSIS; ECONOMETRICS; ENTERPRISES (search for similar items in EconPapers)
JEL-codes: C15 C21 C24 D24 Q12 (search for similar items in EconPapers)
Pages: 18 pages
Date: 1999
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:exe:wpaper:9914

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