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Parametrizing nonparametric translog models: A goal programming/constrained regression study of U.S. manufacturing

Author

Listed:
  • Houshmand Ziari

    (IRZ Consulting, 505 E. Main, Hermiston, Oregon 97838, USA)

  • Azzeddine Azzam

    (207C Filley Hall, University of Nebraska-Lincoln, Lincoln, Nebraska 68583-0922, USA)

Abstract

This paper demonstrates how Goal Programming/Constrained Regression can be used for cross-checking results from standard econometric models as well as a stand alone methodology in empirical production analysis. For illustration, we re-examine Berndt and Wood's (BW) seminal study of the U.S. manufacturing industry. Whereas energy and capital were found to be complements in BW's study, we found them to be substitutes.

Suggested Citation

  • Houshmand Ziari & Azzeddine Azzam, 1999. "Parametrizing nonparametric translog models: A goal programming/constrained regression study of U.S. manufacturing," Empirical Economics, Springer, vol. 24(2), pages 331-339.
    • Handle: RePEc:spr:empeco:v:24:y:1999:i:2:p:331-339
    Note: received: September 1996/final version received: September 1997
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    Cited by:

    1. Andrés J. Picazo-Tadeo & Ernest Reig-Martínez, 2005. "Calculating shadow wages for family labour in agriculture : An analysis for Spanish citrus fruit farms," Cahiers d'Economie et Sociologie Rurales, INRA Department of Economics, vol. 75, pages 5-21.

    More about this item

    Keywords

    Goal programming/constrained regression · bootstrapping · translog cost-function · Berndt and Wood;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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