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Agency Problems in Banking: Types of and Incentives for Risk Shifting

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Financial Crisis, Bank Behaviour and Credit Crunch

Part of the book series: Contributions to Economics ((CE))

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Abstract

The banking literature has extensively examined risk shifting, especially in theoretical terms and in relation to the safety net and regulation. To set a framework of analysis for this moral hazard problem, we provide a brief synthesis of the incentive scheme underlying risk shifting. Then, we propose an empirical method to determine whether banks engage in risk shifting. This method also allows us, first, to classify risk shifting practices depending on the group of creditors to which shareholders transfer risk (that is, our method implies a taxonomy of risk shifting), and second, to identify positive and negative incentives for risk shifting. We apply our method to the banking systems of the United States and the European Union and discuss the resulting findings.

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Notes

  1. 1.

    In addition to Shrieves and Dahl (1992), see, e.g., Jacques and Nigro (1997), Aggarwal and Jacques (2001), Rime (2001), Bichsel and Blum (2004), Heid et al. (2004), Jokipii and Milne (2011).

  2. 2.

    See the Appendix for definitions of the variables.

  3. 3.

    Note that we do not include ΔCR k,t , ΔDR k,t , ΔNDR k,t , or ΔRISK k,t in the set X k,t .

  4. 4.

    If we do not focus on risk-increasing banks, a negative relation between ΔRISK and ΔCR could also correspond to a situation in which banks that increase their capital ratio more also reduce their risk to a greater extent, which can hardly be considered a case of risk shifting.

  5. 5.

    See Duran and Lozano-Vivas (2014, 2015).

  6. 6.

    See Duran and Lozano-Vivas (2014, 2015).

  7. 7.

    For further details about how these datasets are used to generate the variables of our analysis, see the Appendix.

  8. 8.

    Risk-increasing banks account for 46 % and 44 % of the total (cleaned-up) US and EU15 samples, respectively.

  9. 9.

    We use the additive inverse of the Z-score instead of the Z-score itself because the latter is an inverse measure of risk, i.e., a larger Z-score indicates less risk. See the Appendix for the definition of ZS.

  10. 10.

    Table 3 does not display results that are not essential to determining whether there is risk shifting, its type, or which variables incentivise/disincentivise it. Similarly, we do not show or discuss robustness checks. Information on these matters is available upon request. In addition, for a more detailed discussion, see Duran and Lozano-Vivas (2014, 2015).

  11. 11.

    Following the Business Cycle Dating Committee of the National Bureau of Economic Research, the crisis period in the US is 2008–2009, so the pre-crisis and post-crisis periods are 1998–2007 and 2010–2011, respectively. For EU15, the pre-crisis and crisis periods are 2002–2006 and 2007–2009, respectively.

  12. 12.

    Results from this analysis are available upon request.

  13. 13.

    To calculate the capital buffer in the US sample, CR is the capital to risk-weighted-assets ratio.

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Acknowledgement

The authors gratefully acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness [project ECO2011-26996].

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Correspondence to Miguel A. Duran .

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Appendix. Definitions of Variables

Appendix. Definitions of Variables

  • Capital-to-assets ratio (CR): \( \frac{\mathrm{C}}{\mathrm{A}} \).

  • Deposits-to-assets ratio (DR): \( \frac{\mathrm{D}}{\mathrm{A}} \).

  • Ratio of non-depository debt to assets (NDR): \( \frac{\mathrm{ND}}{\mathrm{A}} \).

  • Risk-weighted assets to total assets ratio (RWAR): \( \frac{\mathrm{RWA}}{\mathrm{A}} \).

  • Additive inverse of Z-Score (ZS): \( - \frac{\mathrm{CR}+\mathrm{R}\mathrm{O}\mathrm{A}}{\upsigma^{\mathrm{ROA}}} \).

  • Size (SIZ): ln A.

  • Profitability (PROF): \( \mathrm{R}\mathrm{O}\mathrm{A}=\frac{\mathrm{NI}}{\mathrm{A}} \).

  • Capital buffer (BUF): \( \mathrm{C}\mathrm{R}-\mathrm{R}\mathrm{C}\mathrm{R} \).Footnote 13

  • Generosity of deposit insurance scheme (DI): To build this index, we follow Demirgüç-Kunt and Detragiache (2002). See also Duran and Lozano-Vivas (2014, 2015). The index is increasing in the generosity of the deposit insurance scheme.

  • Strictness of restrictions on bank activities (REST): To build this index, we follow Barth et al. (2001, 2008). The index is increasing in the strictness of the restrictions on bank activities.

  • Strictness of capital requirements (CAP): As regards the method to build this index and its properties, see REST above.

  • Strictness of supervision (SUPERV): As regards the method to build this index and its properties, see REST above.

  • Strictness of market discipline (MKDISC): As regards the method to build this index and its properties, see REST above.

A :

Total assets

C :

Equity

D :

Deposits

ND :

Non-depository debt

NI :

Net income

RCR :

Regulatory capital-to-assets ratio

ROA :

See profitability above

RWA :

Risk-weighted assets

σ ROA :

Standard deviation of ROA

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Duran, M.A., Lozano-Vivas, A. (2016). Agency Problems in Banking: Types of and Incentives for Risk Shifting. In: Rossi, S., Malavasi, R. (eds) Financial Crisis, Bank Behaviour and Credit Crunch. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-17413-6_4

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