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Quantifying management's role in bank survival

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  • Thomas F. Siems

Abstract

Analysts often regard the quality of bank management as the most important factor in determining whether a bank fails or survives. Applying data envelopment analysis to multiple bank inputs and outputs, Thomas F. Siems presents a new model that quantitatively assesses bank management quality. This new paradigm considers a bank's essential financial intermediation functions (that is, attracting deposits to make loans and investments) to compute a scalar measure of efficiency. ; Siems' analysis confirms that management's role is important to a bank's survival. Management quality scores for surviving institutions are significantly better than those for failed banks-up to two and one-half years before failure. Banks whose managers poorly allocate resources and disregard the needs of their customers and markets have a greater chance of failing.

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Bibliographic Info

Article provided by Federal Reserve Bank of Dallas in its journal Economic and Financial Policy Review.

Volume (Year): (1992)
Issue (Month): Q I ()
Pages: 29-41

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Handle: RePEc:fip:fedder:y:1992:i:qi:p:29-41

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Keywords: Bank management ; Bank failures;

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Cited by:
  1. Ping-wen Lin, 2005. "An Empirical Analysis of Bank Mergers and Cost Efficiency in Taiwan," Small Business Economics, Springer, vol. 25(2), pages 197-206, 09.
  2. Chiu, Yung-ho & Luo, Zhengying & Chen, Yu-Chuan & Wang, Zebin & Tsai, Min-Pei, 2013. "A comparison of operating performance management between Taiwan banks and foreign banks based on the Meta-Hybrid DEA model," Economic Modelling, Elsevier, vol. 33(C), pages 433-439.
  3. Robert A. Eisenbeis & Gary D. Ferrier & Simon H. Kwan, 1999. "The informativeness of stochastic frontier and programming frontier efficiency scores: Cost efficiency and other measures of bank holding company performance," Working Paper 99-23, Federal Reserve Bank of Atlanta.
  4. Miller, Stephen M. & Noulas, Athanasios G., 1996. "The technical efficiency of large bank production," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 495-509, April.
  5. Stephen M. Miller & Athanasios Noulas, 1995. "Explaining Recent Connecticut Bank Failures," Working papers 1995-01, University of Connecticut, Department of Economics.
  6. Luo, Xueming, 2003. "Evaluating the profitability and marketability efficiency of large banks: An application of data envelopment analysis," Journal of Business Research, Elsevier, vol. 56(8), pages 627-635, August.
  7. Pille, Peter & Paradi, Joseph C., 2002. "Financial performance analysis of Ontario (Canada) Credit Unions: An application of DEA in the regulatory environment," European Journal of Operational Research, Elsevier, vol. 139(2), pages 339-350, June.
  8. Saha, Asish & Ravisankar, T. S., 2000. "Rating of Indian commercial banks: A DEA approach," European Journal of Operational Research, Elsevier, vol. 124(1), pages 187-203, July.
  9. Steven Ongena, 1999. "Lending Relationships, Bank Default and Economic Activity," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 6(2), pages 257-280.
  10. Kao, Chiang & Liu, Shiang-Tai, 2004. "Predicting bank performance with financial forecasts: A case of Taiwan commercial banks," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2353-2368, October.
  11. Ruthenberg, David & Elias, Ricky, 1996. "Cost economies and interest rate margins in a unified European banking market," Journal of Economics and Business, Elsevier, vol. 48(3), pages 231-249, August.
  12. Chen, Yu-Chuan & Chiu, Yung-Ho & Huang, Chin-Wei & Tu, Chien Heng, 2013. "The analysis of bank business performance and market risk—Applying Fuzzy DEA," Economic Modelling, Elsevier, vol. 32(C), pages 225-232.

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