Pitfalls of Normal-Gamma Stochastic Frontier Models
Christian Ritter and
Leopold Simar ()
Journal of Productivity Analysis, 1997, vol. 8, issue 2, 167-182
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)
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Working Paper: Pitfalls of normal-gamma stochastic frontier models (1997)
Working Paper: Pitfalls of Normal-Gamma Stochastic Frontier Models (1994)
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