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Least squares estimation of joint production functions by the differential evolution method of global optimization

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  • Sudhanshu Mishra

    (North-Eastern Hill University)

Abstract

Most of the studies relating to estimation of joint production functions have noted two difficulties: first that allocation of inputs to different outputs is not known, and the second that a method of estimation cannot have more than one dependent variable, which necessitates construction of a composite output transformation function. 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.

Suggested Citation

  • Sudhanshu Mishra, 2007. "Least squares estimation of joint production functions by the differential evolution method of global optimization," Economics Bulletin, AccessEcon, vol. 3(51), pages 1-13.
    • Handle: RePEc:ebl:ecbull:eb-07c10007
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    References listed on IDEAS

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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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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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