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Inference in dynamic stochastic frontier models

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Author Info

  • Efthymios G. Tsionas

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

Abstract

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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Bibliographic Info

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

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References

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  1. 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.
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Citations

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Cited by:
  1. Assaf, A. George & Barros, Carlos & Sellers-Rubio, Ricardo, 2011. "Efficiency determinants in retail stores: a Bayesian framework," Omega, Elsevier, vol. 39(3), pages 283-292, June.
  2. A. Peyrache & A. N. Rambaldi, 2012. "A State-Space Stochastic Frontier Panel Data Model," CEPA Working Papers Series WP012012, School of Economics, University of Queensland, Australia.
  3. Karlaftis, Matthew G. & Tsamboulas, Dimitrios, 2012. "Efficiency measurement in public transport: Are findings specification sensitive?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 392-402.
  4. Lambarraa, Fatima & Stefanou, Spiro E. & Gil, Jose Maria, 2009. "The analysis of irreversibility, uncertainty and dynamic technical inefficiency on the investment decision in Spanish olive sector," 2009 Conference, August 16-22, 2009, Beijing, China 51397, International Association of Agricultural Economists.
  5. Jorge E. Galán & Helena Veiga & Michael P. Wiper, 2013. "Bayesian analysis of dynamic effects in inefficiency : evidence from the Colombian banking sector," Statistics and Econometrics Working Papers ws131918, Universidad Carlos III, Departamento de Estadística y Econometría.
  6. Arnab Bhattacharjee & Eduardo Castro & Chris Jensen-Butler, 2009. "Regional variation in productivity: a study of the Danish economy," Journal of Productivity Analysis, Springer, vol. 31(3), pages 195-212, June.
  7. Mike, Tsionas & Subal, Kumbhakar, 2011. "Firm-Heterogeneity, Persistent and Transient Technical Inefficiency," MPRA Paper 30737, University Library of Munich, Germany, revised 10 Apr 2011.
  8. Gardebroek, Cornelis & Oude Lansink, Alfons G.J.M., 2008. "Dynamic Microeconometric Approaches To Analysing Agricultural Policy," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6592, European Association of Agricultural Economists.
  9. Guohua Feng & Apostolos Serletis, 2009. "Efficiency, Technical Change, and Returns to Scale in Large U.S. Banks: Panel Data Evidence from an Output Distance Function Satisfying Theoretical Regularity," Monash Econometrics and Business Statistics Working Papers 5/09, Monash University, Department of Econometrics and Business Statistics.
  10. Lambarraa, Fatima, 2012. "The Spanish Horticulture Sector: A dynamic efficiency analysis of Outdoor and Greenhouse farms," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126797, International Association of Agricultural Economists.
  11. Assaf, A. George & Gillen, David & Barros, Carlos, 2012. "Performance assessment of UK airports: Evidence from a Bayesian dynamic frontier model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 603-615.
  12. Stefanou, Spiro E., 2009. "A Dynamic Characterization of Efficiency," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 10(1), January.
  13. Barros, Carlos Pestana & Wanke, Peter, 2014. "Banking efficiency in Brazil," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 54-65.
  14. Lambarraa, Fatima, 2011. "Dynamic Efficiency Analysis of Spanish Outdoor and Greenhouse Horticulture Sector," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114408, European Association of Agricultural Economists.
  15. Sheng-Kai Chang & Yi-Yi Chen & Hung-Jen Wang, 2012. "A Bayesian estimator for stochastic frontier models with errors in variables," Journal of Productivity Analysis, Springer, vol. 38(1), pages 1-9, August.
  16. Yan, Jia & Sun, Xinyu & Liu, John J., 2009. "Assessing container operator efficiency with heterogeneous and time-varying production frontiers," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 172-185, January.
  17. Grigorios Emvalomatis, 2012. "Adjustment and unobserved heterogeneity in dynamic stochastic frontier models," Journal of Productivity Analysis, Springer, vol. 37(1), pages 7-16, February.
  18. Jorge E. Galán & Helena Veiga & Michael P. Wiper, 2012. "Bayesian estimation of inefficiency heterogeneity in stochastic frontier models," Statistics and Econometrics Working Papers ws121007, Universidad Carlos III, Departamento de Estadística y Econometría.
  19. Arnab Bhattacharjee & Eduardo de Castro & (Late) Chris Jensen-Butler, 2007. "Evaluating Economic Theories of Growth and Inequality: A Study of the Danish Economy," CDMA Working Paper Series 200723, Centre for Dynamic Macroeconomic Analysis.

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