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Pitfalls of Normal-Gamma Stochastic Frontier Models

Christian Ritter and Leopold Simar ()

Journal of Productivity Analysis, 1997, vol. 8, issue 2, 167-182

Abstract: Although conceptually pleasing, normal-gamma frontier models lead to difficult estimation problems. It is shown here that unless the sample size reaches several thousands of observations the shape parameter of the gamma density is hard to estimate, and that this carries over to estimates of the stochastic frontier, the individual inefficiencies, and the allocation of the overall variance to the stochastic frontier and to the inefficiencies. Copyright Kluwer Academic Publishers 1997

Keywords: Identifiability; least squares; likelihood; profile; simulation (search for similar items in EconPapers)
Date: 1997
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Related works:
Working Paper: Pitfalls of normal-gamma stochastic frontier models (1997) Downloads
Working Paper: Pitfalls of Normal-Gamma Stochastic Frontier Models (1994) Downloads
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