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On the Use of Panel Data in Bayesian Stochastic Frontier Models

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Author Info

  • Fernández, C.
  • Osiewalski, J.
  • Steel, M.F.J.

    (Tilburg University, Center for Economic Research)

Abstract

We consider a Bayesian analysis of the stochastic frontier model with composed error.Under a commonly used class of (partly) noninformative prior distributions, the existence of the posterior distribution and of posterior moments is examined.Viewing this model as a Normal linear regression model with regression parameters corresponding to both the frontier and the inefficiency terms, generates the insights used to derive results in a very wide framework.It is found that in pure cross-section models posterior inference is precluded under this ``usual'' class of priors.Existence of a well-defined posterior distribution crucially hinges upon the structure imposed on the inefficiency terms.Exploiting panel data naturally suggests the use of more structured models, where Bayesian inference can be conducted.

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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1996-17.

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Date of creation: 1996
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Handle: RePEc:dgr:kubcen:199617

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Related research

Keywords: panel data; bayesian statistics; stochastic frontier models;

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References

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  1. Koop, G. & Osiewalski, J. & Steel, M.F.J., 1995. "The components of output growth: A cross-country analysis," Discussion Paper 1995-17, Tilburg University, Center for Economic Research.
  2. Fernández, C. & Osiewalski, J. & Steel, M.F.J., 1995. "Inference robustness in multivariate models with a scale parameter," Discussion Paper 1995-25, Tilburg University, Center for Economic Research.
  3. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
  4. 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.
  5. repec:fth:louvco:9530 is not listed on IDEAS
  6. 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.
  7. 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.
  8. 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 435-44, June.
  9. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
  10. John Geweke, . "Posterior Simulators in Econometrics," Computing in Economics and Finance 1996 _019, Society for Computational Economics.
  11. KOOP , Gary & OSIEWALSKI , Jacek & STEEL , Mark, 1995. "Bayesian Efficiency Analysis through Individual Effects : Hospital Cost Frontiers," CORE Discussion Papers 1995036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  12. Osiewalski, J. & Steel, M.F.J., 1996. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Discussion Paper 1996-03, Tilburg University, Center for Economic Research.
  13. 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).
  14. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
  15. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
  16. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-74, October.
  17. 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.
  18. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
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Citations

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Cited by:
  1. Supawat Rungsuriyawiboon & Chris O'Donnell, 2004. "Curvature-Constrained Estimates of Technical Efficiency and Returns to Scale for U.S. Electric Utilities," CEPA Working Papers Series WP072004, School of Economics, University of Queensland, Australia.
  2. Gary Koop, 1998. "Carbon dioxide emissions and economic growth: A structural approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 489-515.

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