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Bayesian efficiency analysis with a flexible form : The aim cost function

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  • Koop, G.
  • Osiewalski, J.
  • Steel, M.F.J.

    (Tilburg University, Center For Economic Research)

Abstract

In this article, the authors describe the use of Gibbs sampling methods for drawing posterior inferences in a cost frontier model with an asymptotically ideal price aggregator, nonconstant returns to scale, and composed error. An empirical example illustrates the sensitivity of efficiency measures to assumptions made about the functional form of the frontier. The authors also examine the consequences of imposing regularity through parametric restrictions alone.
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Suggested Citation

  • Koop, G. & Osiewalski, J. & Steel, M.F.J., 1994. "Bayesian efficiency analysis with a flexible form : The aim cost function," Discussion Paper 1994-13, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:0dcc8566-0055-4dc1-9c6b-7ec548e64c95
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    References listed on IDEAS

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    1. William A. Barnett & Michael Wolfe, 2004. "Semi-nonparametric Bayesian Estimation of the Asymptotically Ideal Production Model1," Contributions to Economic Analysis, in: Functional Structure and Approximation in Econometrics, pages 303-349, Emerald Group Publishing Limited.
    2. Gallant, A. Ronald & Golub, Gene H., 1984. "Imposing curvature restrictions on flexible functional forms," Journal of Econometrics, Elsevier, vol. 26(3), pages 295-321, December.
    3. 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.
    4. van den Broeck, Julien & Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1994. "Stochastic frontier models : A Bayesian perspective," Journal of Econometrics, Elsevier, vol. 61(2), pages 273-303, April.
    5. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    6. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    7. W. E. Diewert & T. J. Wales, 1993. "Linear and Quadratic Spline Models for Consumer Demand Functions," Canadian Journal of Economics, Canadian Economics Association, vol. 26(1), pages 77-106, February.
    8. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    9. Caves, Douglas W & Christensen, Laurits R, 1980. "Global Properties of Flexible Functional Forms," American Economic Review, American Economic Association, vol. 70(3), pages 422-432, June.
    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.
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    Sampling; Bayesian Statistics;

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