Production risk and the estimation of ex-ante cost functions

GianCarlo Moschini

ISU General Staff Papers from Iowa State University, Department of Economics

Abstract: Cost function estimation under production uncertainty is problematic because the relevant cost is conditional on unobservable expected output. If input demand functions are also stochastic, then a nonlinear errors-in-variables model is obtained and standard estimation procedures typically fail to attain consistency. But by exploiting the full implications of the expected profit maximization hypothesis that gives rise to ex-ante cost functions, it is shown that the errors-in-variables problem can be effectively removed, and consistent estimation of the parameters of interest achieved. A Monte Carlo experiment illustrates the advantages of the proposed procedure as well as the pitfalls of other existing estimators.

Date: 2001-02-01
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Related works:
Journal Article: Production risk and the estimation of ex-ante cost functions (2001)
Working Paper: Production Risk and the Estimation of Ex Ante Cost Functions (2001)
Working Paper: Production Risk and the Estimation of Ex Ante Cost Functions (2000)
Working Paper: Production Risk and the Estimation of Ex-ante Cost Functions (1999)
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