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


  • 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)


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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    References listed on IDEAS

    1. Taylor, John B, 1980. "Aggregate Dynamics and Staggered Contracts," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 1-23, February.
    2. Gunnar Bardsen & Eilev S. Jansen & Ragnar Nymoen, 2004. "Econometric Evaluation of the New Keynesian Phillips Curve," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(s1), pages 671-686, September.
    3. Gali, Jordi & Gertler, Mark & Lopez-Salido, J. David, 2001. "European inflation dynamics," European Economic Review, Elsevier, vol. 45(7), pages 1237-1270.
    4. Hendry, David F. & Ericsson, Neil R., 1991. "Modeling the demand for narrow money in the United Kingdom and the United States," European Economic Review, Elsevier, vol. 35(4), pages 833-881, May.
    5. Engsted, Tom & Haldrup, Niels, 1997. "Money demand, adjustment costs, and forward-looking behavior," Journal of Policy Modeling, Elsevier, vol. 19(2), pages 153-173, April.
    6. Neil R. Ericsson & John S. Irons, 1995. "The Lucas critique in practice: theory without measurement," International Finance Discussion Papers 506, Board of Governors of the Federal Reserve System (U.S.).
    7. Banerjee, Anindya & Russell, Bill, 2004. "A reinvestigation of the markup and the business cycle," Economic Modelling, Elsevier, vol. 21(2), pages 267-284, March.
    8. Engsted, Tom, 2002. " Measures of Fit for Rational Expectations Models," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 301-355, July.
    9. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-1088, October.
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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.
    2. Ioannis E. Tsolas & Dimitris I. Giokas, 2012. "Bank branch efficiency evaluation by means of least absolute deviations and DEA," Managerial Finance, Emerald Group Publishing, vol. 38(8), pages 768-785, June.

    More about this item


    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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