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Systemic Risk, Sovereign Yields and Bank Exposures in the Euro Crisis

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Abstract

Since 2008, euro-area sovereign yields have diverged sharply, and so have the corresponding CDS premia. At the same time, banks’ sovereign debt portfolios featured an increasing home bias. We investigate the relationship between these two facts, and its rationale. First, we inquire to what extent the dynamics of sovereign yield differentials relative to the swap rate and CDS premia reflect changes in perceived sovereign solvency risk or rather different responses to systemic risk due to the possible collapse of the euro. We do so by decomposing yield differentials and CDS spreads in a country-specific and a common risk component via a dynamic factor model. We then investigate how the home bias of banks’ sovereign portfolios responds to yield differentials and to their two components, by estimating a vector error-correction model on 2008-12 monthly data. We find that in most countries of the euro area, and especially in its periphery, banks’ sovereign exposures respond positively to increases in yields. When bank exposures are related to the country-risk and common-risk components of yields, it turns out that (i) in the periphery, banks increase their domestic exposure in response to increases in country risk, while in core countries they do not; (ii) in most euro area banks respond to an increase in the common risk factor by raising their domestic exposures. Finding (i) hints at distorted incentives in periphery banks’ response to changes in their own sovereign’s risk. Finding (ii) indicates that, when systemic risk increases, all banks tend to increase the home bias of their portfolios, making the euro-area sovereign market more segmented.

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  • Niccolò Battistini & Marco Pagano & Saverio Simonelli, 2013. "Systemic Risk, Sovereign Yields and Bank Exposures in the Euro Crisis," CSEF Working Papers 345, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
  • Handle: RePEc:sef:csefwp:345
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    1. Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2005. "Monetary Policy in Real Time," NBER Chapters,in: NBER Macroeconomics Annual 2004, Volume 19, pages 161-224 National Bureau of Economic Research, Inc.
    2. Alessandro Beber & Michael W. Brandt & Kenneth A. Kavajecz, 2009. "Flight-to-Quality or Flight-to-Liquidity? Evidence from the Euro-Area Bond Market," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 925-957, March.
    3. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, vol. 164(1), pages 188-205, September.
    4. Albertazzi, Ugo & Ropele, Tiziano & Sene, Gabriele & Signoretti, Federico Maria, 2014. "The impact of the sovereign debt crisis on the activity of Italian banks," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 387-402.
    5. repec:hal:journl:peer-00844811 is not listed on IDEAS
    6. Raffaela Giordano & Marcello Pericoli & Pietro Tommasino, 2013. "Pure or Wake-up-Call Contagion? Another Look at the EMU Sovereign Debt Crisis," International Finance, Wiley Blackwell, vol. 16(2), pages 131-160, June.
    7. Antonio Di Cesare & Giuseppe Grande & Michele Manna & Marco Taboga, 2012. "Recent estimates of sovereign risk premia for euro-area countries," Questioni di Economia e Finanza (Occasional Papers) 128, Bank of Italy, Economic Research and International Relations Area.
    8. Favero, Carlo & Pagano, Marco & von Thadden, Ernst-Ludwig, 2010. "How Does Liquidity Affect Government Bond Yields?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(01), pages 107-134, February.
    9. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    10. Viral Acharya & Itamar Drechsler & Philipp Schnabl, 2014. "A Pyrrhic Victory? Bank Bailouts and Sovereign Credit Risk," Journal of Finance, American Finance Association, vol. 69(6), pages 2689-2739, December.
    11. Chiara Angeloni & Guntram B. Wolff, 2012. "Are banks affected by their holdings of government debt?," Working Papers 717, Bruegel.
    12. Buch, Claudia M. & Koetter, Michael & Ohls, Jana, 2016. "Banks and sovereign risk: A granular view," Journal of Financial Stability, Elsevier, vol. 25(C), pages 1-15.
    13. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    14. Fontana, Alessandro & Scheicher, Martin, 2016. "An analysis of euro area sovereign CDS and their relation with government bonds," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 126-140.
    15. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    16. Aizenman, Joshua & Hutchison, Michael & Jinjarak, Yothin, 2013. "What is the risk of European sovereign debt defaults? Fiscal space, CDS spreads and market pricing of risk," Journal of International Money and Finance, Elsevier, vol. 34(C), pages 37-59.
    17. Miguel A. Segoviano Basurto & Carlos Caceres & Vincenzo Guzzo, 2010. "Sovereign Spreads; Global Risk Aversion, Contagion or Fundamentals?," IMF Working Papers 10/120, International Monetary Fund.
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    Keywords

    sovereign yield differentials; dynamic latent factor model; home bias; vector error-correction model;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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