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Inference in dynamic stochastic frontier models

  • Efthymios G. Tsionas

    (Department of Economics, Athens University of Economics and Business, 76 Patission Street, 104 34 Athens, Greece)

An important issue in models of technical efficiency measurement concerns the temporal behaviour of inefficiency. Consideration of dynamic models is necessary but inference in such models is complicated. In this paper we propose a stochastic frontier model that allows for technical inefficiency effects and dynamic technical inefficiency, and use Bayesian inference procedures organized around data augmentation techniques to provide inferences. Also provided are firm-specific efficiency measures. The new methods are applied to a panel of large US commercial banks over the period 1989-2000. Copyright © 2006 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/jae.862
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File URL: http://qed.econ.queensu.ca:80/jae/2006-v21.5/
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 21 (2006)
Issue (Month): 5 ()
Pages: 669-676

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Handle: RePEc:jae:japmet:v:21:y:2006:i:5:p:669-676
DOI: 10.1002/jae.862
Contact details of provider: Web page: http://www.interscience.wiley.com/jpages/0883-7252/

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  1. Berger, Allen N. & Humphrey, David B., 1991. "The dominance of inefficiencies over scale and product mix economies in banking," Journal of Monetary Economics, Elsevier, vol. 28(1), pages 117-148, August.
  2. Tsionas, E.G., 2001. "Stochastic Frontier Models with Random Coefficients," DEOS Working Papers 130, Athens University of Economics and Business.
  3. Greene, W., 2001. "Estimating Econometric Models with Fixed Effects," New York University, Leonard N. Stern School Finance Department Working Paper Seires 01-10, New York University, Leonard N. Stern School of Business-.
  4. 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).
  5. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-32.
  6. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
  7. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
  8. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S19-40, Suppl. De.
  9. Koop, Gary, 1994. " Recent Progress in Applied Bayesian Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 8(1), pages 1-34, March.
  10. Greene, W., 2001. "Fixed and Random Effects in Nonlinear Models," New York University, Leonard N. Stern School Finance Department Working Paper Seires 01-01, New York University, Leonard N. Stern School of Business-.
  11. Seung Ahn & Robin Sickles, 2000. "Estimation of long-run inefficiency levels: a dynamic frontier approach," Econometric Reviews, Taylor & Francis Journals, vol. 19(4), pages 461-492.
  12. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
  13. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 2000. "A Stochastic Frontier Analysis of Output Level and Growth in Poland and Western Economies," Economic Change and Restructuring, Springer, vol. 33(3), pages 185-202.
  14. 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.
  15. 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).
  16. Fernandez C. & Koop G. & Steel M.F.J., 2002. "Multiple-Output Production With Undesirable Outputs: An Application to Nitrogen Surplus in Agriculture," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 432-442, June.
  17. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 2000. "Modeling the Sources of Output Growth in a Panel of Countries," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 284-99, July.
  18. 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.
  19. Stevenson, Rodney E., 1980. "Likelihood functions for generalized stochastic frontier estimation," Journal of Econometrics, Elsevier, vol. 13(1), pages 57-66, May.
  20. Nickell, Stephen J, 1996. "Competition and Corporate Performance," Journal of Political Economy, University of Chicago Press, vol. 104(4), pages 724-46, August.
  21. Roberts, G. O. & Smith, A. F. M., 1994. "Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms," Stochastic Processes and their Applications, Elsevier, vol. 49(2), pages 207-216, February.
  22. Fernandez, Carmen & Koop, Gary & Steel, Mark, 2000. "A Bayesian analysis of multiple-output production frontiers," Journal of Econometrics, Elsevier, vol. 98(1), pages 47-79, September.
  23. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
  24. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-86, July.
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