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A study on long-run inefficiency levels of a panel dynamic cost frontier under the framework of forward-looking rational expectations

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  • Huang, Tai-Hsin
  • Chen, Ying-Hsiu
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    Abstract

    This paper aims to provide a theoretical underpinning of the dynamic efficiency model pioneered by [Ahn, S.C., Good, D.H., Sickles, R.C., 2000. Estimation of long-run inefficiency levels: A dynamic frontier approach. Econometric Reviews 19, 461-492]. In the context of a quadratic loss function this paper formulates a multi-period forward-looking rational expectations model on the evolution of the technical inefficiency level, which correctly produces a dynamic panel data model. The model is illustrated using panel data of 112 French banks. Encouraging evidence of superiority in favor of the model is reached. Substantial cost inefficiency prevails in this industry, where the constituent banks are characterized as having volatile adjustment speeds toward their long-run steady states. The sample banks exhibit increasing returns to scale and product-mix economies.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Banking & Finance.

    Volume (Year): 33 (2009)
    Issue (Month): 5 (May)
    Pages: 842-849

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    Handle: RePEc:eee:jbfina:v:33:y:2009:i:5:p:842-849

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    Web page: http://www.elsevier.com/locate/jbf

    Related research

    Keywords: Forward-looking rational expectations Adjustment speed Technical efficiency;

    References

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    1. Paul W. Bauer & Allen N. Berger & Gary D. Ferrier & David B. Humphrey, 1997. "Consistency conditions for regulatory analysis of financial institutions: a comparison of frontier efficiency methods," Finance and Economics Discussion Series 1997-50, Board of Governors of the Federal Reserve System (U.S.).
    2. Kim, H Youn, 1986. "Economies of Scale and Economies of Scope in Multiproduct Financial Institutions: Further Evidence from Credit Unions: A Note," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 18(2), pages 220-26, May.
    3. 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.
    4. M. Hashem Pesaran & Takashi Yamagata, 2005. "Testing Slope Homogeneity in Large Panels," CESifo Working Paper Series 1438, CESifo Group Munich.
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    6. Allen, Linda & Rai, Anoop, 1996. "Operational efficiency in banking: An international comparison," Journal of Banking & Finance, Elsevier, vol. 20(4), pages 655-672, May.
    7. R Blundell & Steven Bond, . "Initial conditions and moment restrictions in dynamic panel data model," Economics Papers W14&104., Economics Group, Nuffield College, University of Oxford.
    8. Bos, J.W.B. & Schmiedel, H., 2007. "Is there a single frontier in a single European banking market?," Journal of Banking & Finance, Elsevier, vol. 31(7), pages 2081-2102, July.
    9. Mester, Loretta J., 1996. "A study of bank efficiency taking into account risk-preferences," Journal of Banking & Finance, Elsevier, vol. 20(6), pages 1025-1045, July.
    10. 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.
    11. Stephen Nickell & D Nicolitsas, 1995. "How Does Financial Pressure Affect Firms?," CEP Discussion Papers dp0266, Centre for Economic Performance, LSE.
    12. Nickell, Stephen, 1985. "Error Correction, Partial Adjustment and All That: An Expository Note," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 47(2), pages 119-29, May.
    13. Cuthbertson, Keith & Taylor, Mark P., 1990. "Money demand, expectations, and the forward-looking model," Journal of Policy Modeling, Elsevier, vol. 12(2), pages 289-315.
    14. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
    15. M Arellano & O Bover, 1990. "Another Look at the Instrumental Variable Estimation of Error-Components Models," CEP Discussion Papers dp0007, Centre for Economic Performance, LSE.
    16. Huang, Tai-Hsin & Shen, Chung-Hua, 2002. "Seasonal cointegration and cross-equation restrictions on a forward-looking buffer stock model of money demand," Journal of Econometrics, Elsevier, vol. 111(1), pages 11-46, November.
    17. Kennan, John, 1979. "The Estimation of Partial Adjustment Models with Rational Expectations," Econometrica, Econometric Society, vol. 47(6), pages 1441-55, November.
    18. Altunbas, Yener & Evans, Lynne & Molyneux, Philip, 2001. "Bank Ownership and Efficiency," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 33(4), pages 926-54, November.
    19. Kumbhakar, Subal C., 1990. "Production frontiers, panel data, and time-varying technical inefficiency," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 201-211.
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    Cited by:
    1. Jordan, Dan J. & Rice, Douglas & Sanchez, Jacques & Wort, Donald H., 2011. "Explaining bank market-to-book ratios: Evidence from 2006 to 2009," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 2047-2055, August.
    2. Chen, Ku-Hsieh, 2012. "Incorporating risk input into the analysis of bank productivity: Application to the Taiwanese banking industry," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1911-1927.
    3. Koutsomanoli-Filippaki, Anastasia & Mamatzakis, Emmanuel C., 2010. "Estimating the speed of adjustment of European banking efficiency under a quadratic loss function," Economic Modelling, Elsevier, vol. 27(1), pages 1-11, January.
    4. Shakil Quayes & Baqui Khalily, 2013. "Efficiency of Microfinance Institutions in Bangladesh," Working Papers 19, Institute of Microfinance (InM).

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