IDEAS home Printed from https://ideas.repec.org/a/kap/rqfnac/v54y2020i2d10.1007_s11156-019-00797-5.html
   My bibliography  Save this article

Systemic risk-shifting in U.S. commercial banking

Author

Listed:
  • Angelos Kanas

    (University of Piraeus
    Scientific Committee, Parliamentary Budget Office, Hellenic Parliament)

  • Panagiotis D. Zervopoulos

    (University of Sharjah)

Abstract

This paper puts forward the proposition that U.S. commercial banks use dividends as a mechanism to shift systemic risk to debt-holders and the deposit insurer. Using a mixed data sampling modeling approach, it is shown that monthly systemic risk factors are associated with a positive effect on future quarterly bank dividends indicating systemic risk-shifting. These factors include absorption (Kritzman et al. in MIT working paper, 2010), catfin (Allen et al. in Rev Financ Stud 25:3000–3036, 2012), covar (Adrian and Brunnermeier in CoVaR. NBER Working Paper 17454. National Bureau Economic Research, Cambridge, MA, 2011), delta_covar (Adrian and Brunnermeier 2011, mes (Acharya et al. in Rev Financ Stud 24:2166–2205, 2011b), real_vol (Giglio et al. in J Financ Econ 119:457–471, 2016), and size_con (Giglio et al. 2016). In addition, they can now-cast the upward trend in systemic risk-shifting in the 1990s and the downward trend from the early 2000s to 2007. The findings suggest that the rules governing bank dividends need be revised, support the imposition of a dividend tax to mitigate the negative externalities of dividends as a risk-shifting mechanism, and document a reduced effectiveness of Prompt Corrective Action in controlling risk-shifting.

Suggested Citation

  • Angelos Kanas & Panagiotis D. Zervopoulos, 2020. "Systemic risk-shifting in U.S. commercial banking," Review of Quantitative Finance and Accounting, Springer, vol. 54(2), pages 517-539, February.
  • Handle: RePEc:kap:rqfnac:v:54:y:2020:i:2:d:10.1007_s11156-019-00797-5
    DOI: 10.1007/s11156-019-00797-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11156-019-00797-5
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11156-019-00797-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    2. Viral V. Acharya & Hanh T. Le & Hyun Song Shin, 2017. "Bank Capital and Dividend Externalities," Review of Financial Studies, Society for Financial Studies, vol. 30(3), pages 988-1018.
    3. Luc Laeven, 2002. "Bank Risk and Deposit Insurance," The World Bank Economic Review, World Bank, vol. 16(1), pages 109-137, June.
    4. Armen Hovakimian & Edward J. Kane, 2000. "Effectiveness of Capital Regulation at U.S. Commercial Banks, 1985 to 1994," Journal of Finance, American Finance Association, vol. 55(1), pages 451-468, February.
    5. Dahl, Drew & Spivey, Michael F., 1995. "Prompt corrective action and bank efforts to recover from undercapitalization," Journal of Banking & Finance, Elsevier, vol. 19(2), pages 225-243, May.
    6. Adam Zawadowski, 2013. "Entangled Financial Systems," Review of Financial Studies, Society for Financial Studies, vol. 26(5), pages 1291-1323.
    7. Charles W. Calomiris & Joseph R. Mason, 2003. "Consequences of Bank Distress During the Great Depression," American Economic Review, American Economic Association, vol. 93(3), pages 937-947, June.
    8. Enrico Onali, 2014. "Moral Hazard, Dividends, and Risk in Banks," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 41(1-2), pages 128-155, January.
    9. Eugene F. Fama, 2002. "Testing Trade-Off and Pecking Order Predictions About Dividends and Debt," Review of Financial Studies, Society for Financial Studies, vol. 15(1), pages 1-33, March.
    10. Barros, Carlos Pestana & Ferreira, Candida & Williams, Jonathan, 2007. "Analysing the determinants of performance of best and worst European banks: A mixed logit approach," Journal of Banking & Finance, Elsevier, vol. 31(7), pages 2189-2203, July.
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    12. Kanas, Angelos, 2013. "Bank dividends, risk, and regulatory regimes," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 1-10.
    13. Armen Hovakimian & Edward J. Kane, 1996. "Risk-Shifting by Federally Insured Commercial Banks," NBER Working Papers 5711, National Bureau of Economic Research, Inc.
    14. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    15. John, Kose & Saunders, Anthony & Senbet, Lemma W, 2000. "A Theory of Bank Regulation and Management Compensation," Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 95-125.
    16. Pervaiz Alam & Min Liu & Zhefeng Liu & Xiaofeng Peng, 2015. "Stock Options, Idiosyncratic Volatility, and Earnings Quality," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 1-30.
    17. John H. Boyd & Stanley L. Graham, 1988. "The profitability and risk effects of allowing bank holding companies to merge with other financial firms: a simulation study," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 12(Spr), pages 3-20.
    18. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    19. Duan, Jin-Chuan & Moreau, Arthur F. & Sealey, C. W., 1992. "Fixed-rate deposit insurance and risk-shifting behavior at commercial banks," Journal of Banking & Finance, Elsevier, vol. 16(4), pages 715-742, August.
    20. Varouj Aivazian & Laurence Booth & Sean Cleary, 2003. "Do Emerging Market Firms Follow Different Dividend Policies From U.S. Firms?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 26(3), pages 371-387, September.
    21. Flannery, Mark J., 1989. "Capital regulation and insured banks choice of individual loan default risks," Journal of Monetary Economics, Elsevier, vol. 24(2), pages 235-258, September.
    22. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    23. Chuang-Chang Chang & Ruey-Jenn Ho, 2017. "Risk-Shifting Behavior At Commercial Banks With Different Deposit Insurance Assessments: Further Evidence From U.S. Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 40(1), pages 55-80, March.
    24. Michael J. Barclay & Clifford W. Smith & Ross L. Watts, 1995. "The Determinants Of Corporate Leverage And Dividend Policies," Journal of Applied Corporate Finance, Morgan Stanley, vol. 7(4), pages 4-19, January.
    25. Michael D. Bordo & Bruce Mizrach & Anna J. Schwartz, 1998. "Real versus Pseudo-International Systemic Risk Some Lessons from History," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 31-58.
    26. Bernanke, Ben S, 1983. "Nonmonetary Effects of the Financial Crisis in Propagation of the Great Depression," American Economic Review, American Economic Association, vol. 73(3), pages 257-276, June.
    27. Mohammad Alomari & David. M. Power & Nongnuch Tantisantiwong, 2018. "Determinants of equity return correlations: a case study of the Amman Stock Exchange," Review of Quantitative Finance and Accounting, Springer, vol. 50(1), pages 33-66, January.
    28. Yi-Kai Chen & Chung-Hua Shen & Lanfeng Kao & Chuan-Yi Yeh, 2018. "Bank Liquidity Risk and Performance," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-40, March.
    29. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    30. Anat R. Admati & Peter M. DeMarzo & Martin F. Hellwig & Paul Pfleiderer, 2013. "Fallacies, Irrelevant Facts, and Myths in the Discussion of Capital Regulation: Why Bank Equity is Not Socially Expensive," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2013_23, Max Planck Institute for Research on Collective Goods.
    31. Linda Allen & Turan G. Bali & Yi Tang, 2012. "Does Systemic Risk in the Financial Sector Predict Future Economic Downturns?," Review of Financial Studies, Society for Financial Studies, vol. 25(10), pages 3000-3036.
    32. Clements, Michael P & Galvão, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 546-554.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuhao Liu & Petar M. Djurić & Young Shin Kim & Svetlozar T. Rachev & James Glimm, 2021. "Systemic Risk Modeling with Lévy Copulas," JRFM, MDPI, vol. 14(6), pages 1-20, June.
    2. Angelos Kanas & Panagiotis D. Zervopoulos, 2021. "Systemic risk, real GDP growth, and sentiment," Review of Quantitative Finance and Accounting, Springer, vol. 57(2), pages 461-485, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kanas, Angelos, 2013. "Bank dividends, risk, and regulatory regimes," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 1-10.
    2. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72, October.
    3. Hecq, A.W. & Götz, T.B. & Urbain, J.R.Y.J., 2012. "Real-time forecast density combinations (forecasting US GDP growth using mixed-frequency data)," Research Memorandum 021, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    4. Hanan Naser, 2015. "Estimating and forecasting Bahrain quarterly GDP growth using simple regression and factor-based methods," Empirical Economics, Springer, vol. 49(2), pages 449-479, September.
    5. Kertlly de Medeiros, Rennan & da Nóbrega Besarria, Cássio & Pitta de Jesus, Diego & Phillipe de Albuquerquemello, Vinicius, 2022. "Forecasting oil prices: New approaches," Energy, Elsevier, vol. 238(PC).
    6. João C. Claudio & Katja Heinisch & Oliver Holtemöller, 2020. "Nowcasting East German GDP growth: a MIDAS approach," Empirical Economics, Springer, vol. 58(1), pages 29-54, January.
    7. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    8. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    9. Laeven, Luc & Levine, Ross, 2009. "Bank governance, regulation and risk taking," Journal of Financial Economics, Elsevier, vol. 93(2), pages 259-275, August.
    10. Deschamps, Bruno & Ioannidis, Christos & Ka, Kook, 2020. "High-frequency credit spread information and macroeconomic forecast revision," International Journal of Forecasting, Elsevier, vol. 36(2), pages 358-372.
    11. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201316, University of Hawaii at Manoa, Department of Economics.
    12. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    13. Carl Bonham & Peter Fuleky & James Jones & Ashley Hirashima, 2015. "Nowcasting Tourism Industry Performance Using High Frequency Covariates," Working Papers 2015-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    14. Antipa, Pamfili & Barhoumi, Karim & Brunhes-Lesage, Véronique & Darné, Olivier, 2012. "Nowcasting German GDP: A comparison of bridge and factor models," Journal of Policy Modeling, Elsevier, vol. 34(6), pages 864-878.
    15. Warmedinger, Thomas & Paredes, Joan & Asimakopoulos, Stylianos, 2013. "Forecasting fiscal time series using mixed frequency data," Working Paper Series 1550, European Central Bank.
    16. Stefan Neuwirth, 2017. "Time-varying mixed frequency forecasting: A real-time experiment," KOF Working papers 17-430, KOF Swiss Economic Institute, ETH Zurich.
    17. Che Johari, Edie Erman & Chronopoulos, Dimitris K. & Scholtens, Bert & Sobiech, Anna L. & Wilson, John O.S., 2020. "Deposit insurance and bank dividend policy," Journal of Financial Stability, Elsevier, vol. 48(C).
    18. Sarun Kamolthip, 2021. "Macroeconomic Forecasting with LSTM and Mixed Frequency Time Series Data," PIER Discussion Papers 165, Puey Ungphakorn Institute for Economic Research.
    19. Zhang, Yue-Jun & Wang, Jin-Li, 2019. "Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models," Energy Economics, Elsevier, vol. 78(C), pages 192-201.
    20. Kanas, Angelos & Molyneux, Philip, 2020. "Do measures of systemic risk predict U.S. corporate bond default rates?," International Review of Financial Analysis, Elsevier, vol. 71(C).

    More about this item

    Keywords

    Systemic risk; Dividend payout; Mixed data sampling; Risk-shifting;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:rqfnac:v:54:y:2020:i:2:d:10.1007_s11156-019-00797-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.