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On the cross-methodological validation of bank efficiency assessments

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  • Shrimal Perera
  • Michael Skully

Abstract

Purpose – Since there is no agreement on the consistency of their estimates, the purpose of this paper is to investigate whether parametric stochastic frontier analysis (SFA) and nonparametric data envelopment analysis (DEA) generate consistent bank efficiency assessments. Design/methodology/approach – The authors utilize four alternative efficiency computation models: two DEA technical efficiency models based on constant and variable returns to scale, and two SFA cost efficiency models employing Translog and Fourier functional specifications. An unbalanced panel of 59 Indian banks over 1990-2007 is employed as a model, developing country, banking market. Findings – The Translog and Fourier specifications in SFA and the constant and variable returns to scale assumptions in DEA are found to rank and identify “best-practice” and “worst-practice” approximately in the same order. The association between DEA efficiency estimates and non-frontier standard performance measures, however, is mixed and inconclusive. Unlike DEA scores, SFA efficiency assessments were found to be consistent with cost and profit ratios and hence are “believable”. Practical implications – For regulators and bankers alike, the authors' findings highlight the importance of investigating the consistency of efficiency scores across various research methods. They should ensure that frontier-based efficiency assessments are not simply “artificial constructs” of models' assumptions/specifications. Originality/value – This paper extends the existing literature by checking jointly the statistical consistency of both DEA technical efficiency scores and SFA cost efficiency scores. The prior studies focus either on technical efficiency or cost efficiency, but not both. Moreover, as far as the authors are aware, this is the first cross-methodological validation study to focus on bank efficiency in the context of a developing country banking market.

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Bibliographic Info

Article provided by Emerald Group Publishing in its journal Studies in Economics and Finance.

Volume (Year): 29 (2012)
Issue (Month): 1 (March)
Pages: 26-42

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Handle: RePEc:eme:sefpps:v:29:y:2012:i:1:p:26-42

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Web page: http://www.emeraldinsight.com

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Postal: Emerald Group Publishing, Howard House, Wagon Lane, Bingley, BD16 1WA, UK
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Related research

Keywords: Assessment; Bank efficiency; Banks; Cross-methodological validation; Data envelopment analysis; Developing countries; India; Non parametric measures; Parametric measures; Stochastic frontier analysis;

References

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  1. Allen N. Berger & David B. Humphrey, 1997. "Efficiency of Financial Institutions: International Survey and Directions for Future Research," Center for Financial Institutions Working Papers 97-05, Wharton School Center for Financial Institutions, University of Pennsylvania.
  2. Thanassoulis, E. & Boussofiane, A. & Dyson, R. G., 1996. "A comparison of data envelopment analysis and ratio analysis as tools for performance assessment," Omega, Elsevier, vol. 24(3), pages 229-244, June.
  3. Tulkens, H. & Vanden Eeckaut, P., . "Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects," CORE Discussion Papers RP -1132, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  4. Laura Cavallo & Stefania Rossi, 2002. "Do environmental variables affect the performance and technical efficiency of the European banking systems? A parametric analysis using the stochastic frontier approach," The European Journal of Finance, Taylor & Francis Journals, vol. 8(1), pages 123-146.
  5. Shrimal Perera & Michael Skully & J. Wickramanayake, 2007. "Cost Efficiency in South Asian Banking: The Impact of Bank Size, State Ownership and Stock Exchange Listings-super-," International Review of Finance, International Review of Finance Ltd., vol. 7(1-2), pages 35-60.
  6. Gallant, A. Ronald, 1982. "Unbiased determination of production technologies," Journal of Econometrics, Elsevier, vol. 20(2), pages 285-323, November.
  7. Leamer, Edward E & Leonard, Herman B, 1983. "Reporting the Fragility of Regression Estimates," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 306-17, May.
  8. Resti, Andrea, 1997. "Evaluating the cost-efficiency of the Italian Banking System: What can be learned from the joint application of parametric and non-parametric techniques," Journal of Banking & Finance, Elsevier, vol. 21(2), pages 221-250, February.
  9. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1973. "Transcendental Logarithmic Production Frontiers," The Review of Economics and Statistics, MIT Press, vol. 55(1), pages 28-45, February.
  10. Das, Abhiman & Ghosh, Saibal, 2006. "Financial deregulation and efficiency: An empirical analysis of Indian banks during the post reform period," Review of Financial Economics, Elsevier, vol. 15(3), pages 193-221.
  11. Altunbas, Yener & Liu, Ming-Hau & Molyneux, Philip & Seth, Rama, 2000. "Efficiency and risk in Japanese banking," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1605-1628, October.
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