Bayesian efficiency analysis with a flexible form: The aim cost function
AbstractIn 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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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1994-13.
Date of creation: 1994
Date of revision:
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Web page: http://center.uvt.nl
Sampling; Bayesian Statistics;
Other versions of this item:
- Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 339-46, July.
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- 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.
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- KOOP, Gary & STEEL, Mark F. & OSIEWALSKI, Jacek, 1994. "Posterior Analysis of Stochastic Frontier Models using Gibbs Sampling," CORE Discussion Papers 1994061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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538, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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- 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.
- 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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