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An Average Derivative Estimation of Stochastic Frontiers

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  • Cliff Huang
  • Tsu-Tan Fu

Abstract

This paper utilizes the average derivative estimation of Stoker (1986) and the pesudo-likelihood estimation of Fan, Li, and Weersink (1996) to estimate a semiparametric stochastic frontier regression, y=g(x) + ε, where the function g(.)is unknown and ε is a composite error in a standard setting. The proposed semiparametric method of estimation is applied to data on farmers' credit unions in Taiwan. Empirical results show that the banking services of the farmers' credit unions is subject to economies of scale, but high degree of cost inefficiency in operation. Copyright Kluwer Academic Publishers 1999

Suggested Citation

  • Cliff Huang & Tsu-Tan Fu, 1999. "An Average Derivative Estimation of Stochastic Frontiers," Journal of Productivity Analysis, Springer, vol. 12(1), pages 45-53, August.
    • Handle: RePEc:kap:jproda:v:12:y:1999:i:1:p:45-53
    DOI: 10.1023/A:1007851023468
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    References listed on IDEAS

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    1. Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-468, October.
    2. Kopp, Raymond J. & Mullahy, John, 1990. "Moment-based estimation and testing of stochastic frontier models," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 165-183.
    3. Tsu-Tan Fu & Cliff J. Huang & C. A.K. Lovell (ed.), 1999. "Economic Efficiency and Productivity Growth in the Asia-pacific Region," Books, Edward Elgar Publishing, number 1531.
    4. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    5. White, Halbert, 1980. "Using Least Squares to Approximate Unknown Regression Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 149-170, February.
    6. 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.
    7. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
    8. 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.
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    Cited by:

    1. Griffin, J. E. & Steel, M. F. J., 2004. "Semiparametric Bayesian inference for stochastic frontier models," Journal of Econometrics, Elsevier, vol. 123(1), pages 121-152, November.

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