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Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function

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Abstract

The normal-gamma stochastic frontier model was proposed in Greene (1990) and Beckers and Hammond (1987) as an extension of the normal-exponential proposed in the original derivations of the stochastic frontier by Aigner, Lovell and Schmidt (1977). The normal-gamma model has the virtue of providing a richer and more flexible parameterization of the inefficiency distribution in the stochastic frontier model than either of the canonical forms, normal-half normal and normal-exponential. However, several attempts to operationalize the normal-gamma model have met with very limited success, as the log likelihood is possesed of a significant degree of complexity. This note will propose an alternative approach to estimation of this model based on the method of maximum simulated likelihood estimation as opposed to the received attempts which have approached the problem by direct maximization. Copyright Kluwer Academic Publishers 2003

Suggested Citation

  • William Greene, 2003. "Simulated Likelihood Estimation of the Normal-Gamma Stochastic Frontier Function," Journal of Productivity Analysis, Springer, vol. 19(2), pages 179-190, April.
  • Handle: RePEc:kap:jproda:v:19:y:2003:i:2:p:179-190
    DOI: 10.1023/A:1022853416499
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    1. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
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    6. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    7. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
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    2. Kumbhakar, Subal C. & Tsionas, Efthymios G., 2006. "Estimation of stochastic frontier production functions with input-oriented technical efficiency," Journal of Econometrics, Elsevier, vol. 133(1), pages 71-96, July.
    3. Greene, William, 2001. "New Developments in the Estimation of Stochastic Frontier Models with Panel Data," Efficiency Series Papers 2001/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    4. Eduardo Fé & Richard Hofler, 2013. "Count data stochastic frontier models, with an application to the patents–R&D relationship," Journal of Productivity Analysis, Springer, vol. 39(3), pages 271-284, June.
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    7. Hung-pin Lai & Cliff Huang, 2013. "Maximum likelihood estimation of seemingly unrelated stochastic frontier regressions," Journal of Productivity Analysis, Springer, vol. 40(1), pages 1-14, August.
    8. Gholamreza Hajargasht, 2015. "Stochastic frontiers with a Rayleigh distribution," Journal of Productivity Analysis, Springer, vol. 44(2), pages 199-208, October.
    9. Huang, Tai-Hsin & Chiang, Dien-Lin & Lin, Chung-I, 2017. "A new approach to estimating a profit frontier using the censored stochastic frontier model," The North American Journal of Economics and Finance, Elsevier, vol. 39(C), pages 68-77.
    10. Mehdi Farsi & Massimo Filippini, 2008. "Effects of ownership, subsidization and teaching activities on hospital costs in Switzerland," Health Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 335-350.
    11. Arabinda Das, 2015. "Copula-based Stochastic Frontier Model with Autocorrelated Inefficiency," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 7(2), pages 111-126, June.
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    15. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.
    16. Lambarraa, Fatima, 2012. "The Spanish Horticulture Sector: A dynamic efficiency analysis of Outdoor and Greenhouse farms," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126797, International Association of Agricultural Economists.
    17. Kumbhakar, Subal & Tsionas, Efthymios, 2003. "Recent Developments in Stochastic Frontier Modeling," Efficiency Series Papers 2003/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    18. Tsionas, Efthymios G., 2012. "Maximum likelihood estimation of stochastic frontier models by the Fourier transform," Journal of Econometrics, Elsevier, vol. 170(1), pages 234-248.
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    20. Shaik, Saleem, 2015. "Impact of liquidity risk on variations in efficiency and productivity: A panel gamma simulated maximum likelihood estimation," European Journal of Operational Research, Elsevier, vol. 245(2), pages 463-469.
    21. Boyd, Gale A., 2014. "Estimating the changes in the distribution of energy efficiency in the U.S. automobile assembly industry," Energy Economics, Elsevier, vol. 42(C), pages 81-87.

    More about this item

    Keywords

    frontier; gamma; simulated likelihood;

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D33 - Microeconomics - - Distribution - - - Factor Income Distribution

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