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 can be 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 Center for Agricultural and Rural Development (CARD) at Iowa State University in its series Center for Agricultural and Rural Development (CARD) Publications with number 00-wp262.
Date of creation: Dec 2000
Date of revision:
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.
- Moschini, GianCarlo, 2001. "Production Risk and the Estimation of Ex Ante Cost Functions," Staff General Research Papers 1922, Iowa State University, Department of Economics.
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