A Nonlinear Generalized Additive Error Model of Production and Cost
AbstractIn 1944, Marschak and Andrews published a seminal paper on how to obtain consistent estimates of a production technology. The original formulation of the econometric model regarded the joint estimation of the production function together with the first-order necessary conditions for profit-maximizing behavior. In the seventies, with the advent of econometric duality, the preference seemed to have shifted to a dual approach. Recently, however, Mundlak resurrected the primal-versus-dual debate with a provocative paper titled “Production Function Estimation: Reviving the Primal.” In that paper, the author asserts that the dual estimator, unlike the primal approach, is not efficient because it fails to utilize all the available information. In this paper we demonstrate that efficient estimates of the production technology can be obtained only by jointly estimating all the relevant primal and dual relations. Thus, the primal approach of Mundlak and the dual approach of McElroy become nested special cases of the general specification. In the process of putting to rest the primal-versus-dual debate, we solve also the nonlinear errors-in-variables problem when all the variables are measured with error.
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Bibliographic InfoPaper provided by University of California, Davis, Department of Agricultural and Resource Economics in its series Working Papers with number 93743.
Date of creation: 2004
Date of revision:
Primal; Dual; Cobb-Douglas; Nonlinear errors-in-variables; Productivity Analysis; Research Methods/ Statistical Methods; D0; C3;
Find related papers by JEL classification:
- D0 - Microeconomics - - General
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
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- Schmidt, Peter, 1988. "Estimation of a fixed-effect Cobb-Douglas system using panel data," Journal of Econometrics, Elsevier, vol. 37(3), pages 361-380, March.
- Fuller, Wayne A., 1980. "The use of indicator variables in computing predictions," Journal of Econometrics, Elsevier, vol. 12(2), pages 231-243, February.
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