Production Risk and the Estimation of Ex Ante Cost Functions

GianCarlo Moschini

Center for Agricultural and Rural Development (CARD) Publications from Center for Agricultural and Rural Development (CARD) at Iowa State University

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 can be achieved. A Monte Carlo experiment illustrates the advantages of the proposed procedure as well as the pitfalls of other existing estimators.

Date: 2000-12
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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 (2001)
Working Paper: Production Risk and the Estimation of Ex-ante Cost Functions (1999)
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