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Production risk and the estimation of ex-ante cost functions
Journal of Econometrics
  • Giancarlo Moschini, Iowa State University
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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.

This is a working paper of an article from Journal of Econometrics 100 (2001): 357, doi: 10.1016/S0304-4076(00)00041-5.

Citation Information
Giancarlo Moschini. "Production risk and the estimation of ex-ante cost functions" Journal of Econometrics Vol. 100 Iss. 2 (2001) p. 357 - 380
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