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Too-connected versus too-big-to-fail: banks’ network centrality and overnight interest rates

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  • Gabrieli, S.

Abstract

What influences banks’ borrowing costs in the unsecured money market? The objective of this paper is to test whether measures of centrality, quantifying network effects due to interactions among banks in the market, can help explain heterogeneous patterns in the interest rates paid to borrow unsecured funds once bank size and other bank and market factors that affect the overnight segment are controlled for. Preliminary evidence shows that large banks borrow on average at better rates compared to smaller institutions, both before and after the start of the financial crisis. Nonetheless, controlling for size, centrality measures can capture part of the cross-sectional variation in overnight rates. More specifically: (1) Before the start of the crisis all the banks, independently of their size, profit from different forms of interconnectedness, but the economic size of the effect is small. Bank reputation and perceived credit riskiness are the most relevant factors to reduce average daily interest rates. Foreign banks borrow at a discount over Italian ones. (2) After August 2007 the impact of banks’ interconnectedness becomes larger but changes sign: the “reward” stemming from a higher centrality becomes a “punishment”, which possibly reflects market discipline. Bank reputation becomes even more important. (3) After Lehman’s bankruptcy the effect of centrality on the spread maintains the same sign as after August 2007, but the magnitude increases remarkably. Foreign banks borrow at a relevant premium over Italian ones; reputation becomes outstandingly more important than in normal times.

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  • Gabrieli, S., 2012. "Too-connected versus too-big-to-fail: banks’ network centrality and overnight interest rates," Working papers 398, Banque de France.
  • Handle: RePEc:bfr:banfra:398
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    References listed on IDEAS

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    Cited by:

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    2. Vasilis Hatzopoulos & Giulia Iori & Rosario N. Mantegna & Salvatore Miccich� & Michele Tumminello, 2015. "Quantifying preferential trading in the e-MID interbank market," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 693-710, April.
    3. Adrian Alter & Ben R. Craig & Peter Raupach, 2015. "Centrality-Based Capital Allocations," International Journal of Central Banking, International Journal of Central Banking, vol. 11(3), pages 329-377, June.
    4. Temizsoy, Asena & Iori, Giulia & Montes-Rojas, Gabriel, 2017. "Network centrality and funding rates in the e-MID interbank market," Journal of Financial Stability, Elsevier, vol. 33(C), pages 346-365.
    5. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.
    6. Bennani, T. & Després, M. & Dujardin, M. & Duprey, T. & Kelber, A., 2014. "Macroprudential framework:key questions applied to the French case," Occasional papers 9, Banque de France.
    7. Iori, G. & Kapar, B. & Olmo, J., 2012. "The Cross-Section of Interbank Rates: A Nonparametric Empirical Investigation," Working Papers 12/03, Department of Economics, City University London.
    8. Barthélemy, J. & Marx, M., 2012. "Generalizing the Taylor Principle: New Comment," Working papers 403, Banque de France.
    9. Jose Fique & Frank Page, 2013. "Rollover risk and endogenous network dynamics," Computational Management Science, Springer, vol. 10(2), pages 213-230, June.
    10. Olivier Brossard & Susanna Saroyan, 2016. "Hoarding and short-squeezing in times of crisis: Evidence from the Euro overnight money market," Post-Print hal-01293693, HAL.
    11. Marco Pelliccia, 2013. "Ambiguous Networks," Birkbeck Working Papers in Economics and Finance 1303, Birkbeck, Department of Economics, Mathematics & Statistics.
    12. Paul Glasserman & H. Peyton Young, 2016. "Contagion in Financial Networks," Journal of Economic Literature, American Economic Association, vol. 54(3), pages 779-831, September.
    13. Caterina Liberati & Massimiliano Marzo & Paolo Zagaglia & Paola Zappa, 2015. "Drivers of demand and supply in the Euro interbank market: the role of “Key Players” during the recent turmoil," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 29(3), pages 207-250, August.
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    More about this item

    Keywords

    Network centrality; Interbank market; Financial crisis; Money market integration; Macro-prudential analysis.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G01 - Financial Economics - - General - - - Financial Crises
    • 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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