Production Risk and the Estimation of Ex Ante Cost Functions
AbstractCost 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.
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 1922.
Date of creation: 01 Jan 2001
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Publication status: Published in Journal of Econometrics 2001, vol. 100, pp. 357-380
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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
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Other versions of this item:
- Moschini, GianCarlo, 2001. "Production risk and the estimation of ex-ante cost functions," Journal of Econometrics, Elsevier, vol. 100(2), pages 357-380, February.
- GianCarlo Moschini, 2000. "Production Risk and the Estimation of Ex Ante Cost Functions," Center for Agricultural and Rural Development (CARD) Publications 00-wp262, Center for Agricultural and Rural Development (CARD) at Iowa State University.
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