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Least squares estimation of joint production functions by the Differential Evolution method of global optimization

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  • Mishra, SK

Abstract

In the economics of joint production one often distinguishes between the two cases: the one in which a firm produces multiple products each produced under separate production process, and the other “true joint production” where a number of outputs are produced from a single production process, where each product shares common inputs. In the econometric practice the first case has often been dealt with by aggregation of individual production functions into a macro production function. The second case has often called for estimation of an implicit aggregate production function. Most of the studies relating to estimation of joint production functions have noted two difficulties: first that allocation of inputs to different outputs are not known, and the second that a method of estimation (such as the Least Squares) cannot have more than one dependent variable. Construction of a composite (macro) output function is at least partly motivated by the inability of the estimation methods to deal with multiple dependent variables and different forms of production function for different outputs. This study has conducted some simulation experiments on joint estimation of the CES, the Transcendental and the Nerlove-Ringstad functions. Allocation parameters (of inputs) across the products have been introduced. Estimation has been done jointly, but without constructing a composite macro production function or an output transformation function. We use nonlinear least squares based on the Differential Evolution method of global optimization that permits fitting multiple production functions simultaneously.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 4813.

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Date of creation: 11 Sep 2007
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Handle: RePEc:pra:mprapa:4813

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Keywords: Joint production; multiple output; allocation parameters; nonlinear least squares; Differential Evolution; Nerlove-Ringstad; Transcendental; CES; macro; implicit; composite production function; transformation function; canonical correlation; multiple dependent variables;

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  1. Chizmar, John F & Zak, Thomas A, 1983. "Modeling Multiple Outputs in Educational Production Functions," American Economic Review, American Economic Association, vol. 73(2), pages 17-22, May.
  2. Rao, Potluri, 1969. "A Note on Econometrics of Joint Production," Econometrica, Econometric Society, vol. 37(4), pages 737-38, October.
  3. Diewert, W E, 1971. "An Application of the Shephard Duality Theorem: A Generalized Leontief Production Function," Journal of Political Economy, University of Chicago Press, vol. 79(3), pages 481-507, May-June.
  4. Dhrymes, Phoebus J & Mitchell, B M, 1969. "Estimation of Joint Production Functions," Econometrica, Econometric Society, vol. 37(4), pages 732-36, October.
  5. Vinod, H. D., 1976. "Canonical ridge and econometrics of joint production," Journal of Econometrics, Elsevier, vol. 4(2), pages 147-166, May.
  6. Vinod, Hrishikesh D, 1969. "Econometrics of Joint Production-A Reply," Econometrica, Econometric Society, vol. 37(4), pages 739-40, October.
  7. Chetty, V Karuppan, 1969. "Econometrics of Joint Production: A Comment," Econometrica, Econometric Society, vol. 37(4), pages 731, October.
  8. Mishra, SK, 2007. "Performance of Differential Evolution Method in Least Squares Fitting of Some Typical Nonlinear Curves," MPRA Paper 4634, University Library of Munich, Germany.
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Cited by:
  1. S K Mishra, 2010. "A Brief History of Production Functions," The IUP Journal of Managerial Economics, IUP Publications, vol. 0(4), pages 6-34, November.

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