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Heterogeneity, co-movements and financial fragmentation within the euro area

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  • Arce-Alfaro, Gabriel
  • Blagov, Boris

Abstract

In this article we analyse the degree of commonality across euro area countries in the bank lending rates and credit volumes. Using a time-varying two-level dynamic factor model, we disentangle the relative importance of country-specific and common components in explaining the variance of the macro and financial variables. Our results show that a high share is explained by the common component. However, we find a persistent decline in the importance of the common factor in the bank lending rates, indicating the presence of financial fragmentation. There is heterogeneity across member states, specifically those hit hard by the crisis. We observe high commonality in the financial variables, which increases in periods of high financial volatility.

Suggested Citation

  • Arce-Alfaro, Gabriel & Blagov, Boris, 2021. "Heterogeneity, co-movements and financial fragmentation within the euro area," Ruhr Economic Papers 927, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  • Handle: RePEc:zbw:rwirep:927
    DOI: 10.4419/96973085
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    1. Del Negro, Marco & Giannone, Domenico & Giannoni, Marc P. & Tambalotti, Andrea, 2019. "Global trends in interest rates," Journal of International Economics, Elsevier, vol. 118(C), pages 248-262.
    2. Boris Blagov & Michael Funke & Richhild Moessner, 2015. "Modelling the time-variation in euro area lending spreads," BIS Working Papers 526, Bank for International Settlements.
    3. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    4. Ciccarelli, Matteo & Maddaloni, Angela & Peydró, José-Luis, 2013. "Heterogeneous transmission mechanism: monetary policy and financial fragility in the euro area," Working Paper Series 1527, European Central Bank.
    5. Stéphane Dées & Nico Zorell, 2012. "Business Cycle Synchronisation: Disentangling Trade and Financial Linkages," Open Economies Review, Springer, vol. 23(4), pages 623-643, September.
    6. Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, September.
    7. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    8. Marco Del Negro & Christopher Otrok, 2008. "Dynamic factor models with time-varying parameters: measuring changes in international business cycles," Staff Reports 326, Federal Reserve Bank of New York.
    9. Haroon Mumtaz & Alberto Musso, 2021. "The Evolving Impact of Global, Region-Specific, and Country-Specific Uncertainty," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 466-481, March.
    10. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
    11. Cascaldi-Garcia, Danilo & Ferreira, Thiago R.T. & Giannone, Domenico & Modugno, Michele, 2024. "Back to the present: Learning about the euro area through a now-casting model," International Journal of Forecasting, Elsevier, vol. 40(2), pages 661-686.
    12. Haroon Mumtaz & Paolo Surico, 2012. "Evolving International Inflation Dynamics: World And Country-Specific Factors," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 716-734, August.
    13. Rey, Hélène, 2015. "Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence," CEPR Discussion Papers 10591, C.E.P.R. Discussion Papers.
    14. Matteo Ciccarelli & Angela Maddaloni & José-Luis Peydró, 2013. "Heterogeneous transmission mechanism: monetary policy and financial fragility in the eurozone [Which financial frictions? Parsing the evidence from the financial crisis of 2007-9]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 28(75), pages 459-512.
    15. Altavilla, Carlo & Canova, Fabio & Ciccarelli, Matteo, 2020. "Mending the broken link: Heterogeneous bank lending rates and monetary policy pass-through," Journal of Monetary Economics, Elsevier, vol. 110(C), pages 81-98.
    16. Stijn Claessens, 2019. "Fragmentation in global financial markets: good or bad for financial stability?," BIS Working Papers 815, Bank for International Settlements.
    17. repec:oup:ecpoli:v:28:y:2013:i:75:p:459-512 is not listed on IDEAS
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    More about this item

    Keywords

    Co-movements; financial fragmentation; dynamic factor model;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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