Production risk and the estimation of ex-ante cost functions.
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 at...
| Publicado en: | Journal of Econometrics Vol. 100; no. 2; pp. 357 - 381 |
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| Autor principal: | |
| Formato: | Artículo |
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Elsevier Science
February 2001
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | 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. Copyright (c) 2000 Elsevier Science S.A. |
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