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Accounting for Unobservables in Production Models: Management and Inefficiency

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  • Álvarez, Antonio
  • Arias, Carlos
  • Greene, William
Abstract
This paper explores the role of unobserved managerial ability in production and its relationship with technical efficiency. Previous analyses of managerial ability have been based on strong assumptions about its role in production or on the use of proxies. We avoid these limitations by introducing managerial ability as an unobserved random variable in a translog production function. The resulting empirical model can be estimated as a stochastic production frontier with random coefficients.

Suggested Citation

  • Álvarez, Antonio & Arias, Carlos & Greene, William, 2005. "Accounting for Unobservables in Production Models: Management and Inefficiency," Efficiency Series Papers 2005/07, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    • Handle: RePEc:oeg:wpaper:2005/07
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    File URL: https://www.unioviedo.es/oeg/ESP/esp_2005_07.pdf
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    References listed on IDEAS

    as
    1. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318, Elsevier.
    2. Efthymios G. Tsionas, 2002. "Stochastic frontier models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 127-147.
    3. Antonio Alvarez & Carlos Arias, 2003. "Diseconomies of Size with Fixed Managerial Ability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 134-142.
    4. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    5. Yair Mundlak, 1961. "Empirical Production Function Free of Management Bias," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 43(1), pages 44-56.
    6. Jovanovic, Boyan, 1982. "Selection and the Evolution of Industry," Econometrica, Econometric Society, vol. 50(3), pages 649-670, May.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    8. Zvi Griliches, 1957. "Specification Bias in Estimates of Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 39(1), pages 8-20.
    9. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    10. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    11. ZELLNER, Arnold & KMENTA, Jan & DREZE, Jacques H., 1966. "Specification and estimation of Cobb-Douglas production function models," LIDAM Reprints CORE 12, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Greene, William, 2005. "Reconsidering heterogeneity in panel data estimators of the stochastic frontier model," Journal of Econometrics, Elsevier, vol. 126(2), pages 269-303, June.
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    More about this item

    Keywords

    Managerial ability; technical efficiency; production frontier; random coefficients model; maximum simulated likelihood;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • D2 - Microeconomics - - Production and Organizations

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