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Integrating bank profit and risk-avoidance decisions for selected European countries: A micro–macro analysis

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  • Gander, James P.

Abstract

A two-equation integrated model is developed to capture bank profit and risk-avoidance decisions. Output is limited to customer loans. The profit function is based on output and selected inputs. Risk-avoidance (using the capitalization ratio) depends on micro and micro∗macro interactive variables. The SUR method is used to test the hypothesis that the two functions are interdependent. Also, a single reduced-form equation is derived from the SUR model to analyze the volatility of the capitalization ratio. Five European countries and their banks for the period 1991–2001 are used to run the regressions and to test the hypothesis. The individual statistical results were generally consistent with similar results found in the literature. The Breusch–Pagan test of independence was rejected. A key finding from the volatility analysis suggests that bank profit rates are inversely related to the volatility of the banks' capitalization ratios as measured by their variances.

Suggested Citation

  • Gander, James P., 2013. "Integrating bank profit and risk-avoidance decisions for selected European countries: A micro–macro analysis," Economic Modelling, Elsevier, vol. 31(C), pages 717-722.
  • Handle: RePEc:eee:ecmode:v:31:y:2013:i:c:p:717-722
    DOI: 10.1016/j.econmod.2013.01.014
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    1. Berger, Allen N, 1995. "The Relationship between Capital and Earnings in Banking," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(2), pages 432-456, May.
    2. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    3. Tsai, Ming-Shann & Chen, Lien-Chuan, 2011. "The calculation of capital requirement using Extreme Value Theory," Economic Modelling, Elsevier, vol. 28(1-2), pages 390-395, January.
    4. Goddard, John & Molyneux, Phil & Wilson, John O S, 2004. "Dynamics of Growth and Profitability in Banking," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(6), pages 1069-1090, December.
    5. Riccardo Lucchetti & Luca Papi & Alberto Zazzaro, 2001. "Banks’ Inefficiency and Economic Growth: A Micro‐Macro Approach," Scottish Journal of Political Economy, Scottish Economic Society, vol. 48(4), pages 400-424, September.
    6. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    7. Bert Scholtens, 2000. "Competition, Growth, and Performance in the Banking Industry," Center for Financial Institutions Working Papers 00-18, Wharton School Center for Financial Institutions, University of Pennsylvania.
    8. Shrieves, Ronald E. & Dahl, Drew, 1992. "The relationship between risk and capital in commercial banks," Journal of Banking & Finance, Elsevier, vol. 16(2), pages 439-457, April.
    9. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    10. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    11. Allen, Franklin & Santomero, Anthony M., 1997. "The theory of financial intermediation," Journal of Banking & Finance, Elsevier, vol. 21(11-12), pages 1461-1485, December.
    12. Ronald A. Ratti, 1980. "Bank Attitude Toward Risk, Implicit Rates of Interest, and the Behavior of an Index of Risk Aversion for Commercial Banks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(2), pages 309-331.
    13. Tsai, Ming-Shann & Chen, Lien-Chuan, 2011. "The calculation of capital requirement using Extreme Value Theory," Economic Modelling, Elsevier, vol. 28(1), pages 390-395.
    14. Heid, Frank, 2005. "Cyclical implications of minimum capital requirements," Discussion Paper Series 2: Banking and Financial Studies 2005,06, Deutsche Bundesbank.
    15. Yener Altunbas & Santiago Carbo & Edward P.M. Gardener & Philip Molyneux, 2007. "Examining the Relationships between Capital, Risk and Efficiency in European Banking," European Financial Management, European Financial Management Association, vol. 13(1), pages 49-70, January.
    16. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    17. Xavier Freixas & Jean-Charles Rochet, 1997. "Microeconomics of Banking," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061937, April.
    18. World Bank, 2003. "World Development Indicators 2003," World Bank Publications - Books, The World Bank Group, number 13920.
    19. Johnsen, Thomajean & Melicher, Ronald W., 1994. "Predicting corporate bankruptcy and financial distress: Information value added by multinomial logit models," Journal of Economics and Business, Elsevier, vol. 46(4), pages 269-286, October.
    20. Santomero, Anthony M, 1984. "Modeling the Banking Firm: A Survey," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 16(4), pages 576-602, November.
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    More about this item

    Keywords

    Bank behavior; Profit; Capital ratios; Volatility;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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