[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
IDEAS home Printed from https://ideas.repec.org/p/zbw/rwirep/927.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/249306/1/178662611X.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4419/96973085?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
    ---><---

    References listed on IDEAS

    as
    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
    Full references (including those not matched with items on IDEAS)

    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. Arce-Alfaro, Gabriel & Blagov, Boris, 2022. "Financial integration or financial fragmentation? A euro area perspective," Economic Modelling, Elsevier, vol. 114(C).
    2. Lukas Berend & Jan Pruser, 2024. "The Transmission of Monetary Policy via Common Cycles in the Euro Area," Papers 2410.05741, arXiv.org, revised Oct 2024.
    3. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    4. Andrea Carriero & Francesco Corsello & Massimiliano Marcellino, 2022. "The global component of inflation volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 700-721, June.
    5. Filippo Ferroni & Benjamin Klaus, 2015. "Euro Area business cycles in turbulent times: convergence or decoupling?," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3791-3815, July.
    6. Baumeister, Christiane & Liu, Philip & Mumtaz, Haroon, 2013. "Changes in the effects of monetary policy on disaggregate price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 543-560.
    7. Giancarlo Corsetti & Joao B Duarte & Samuel Mann, 2022. "One Money, Many Markets [Fixed Rate Versus Adjustable Rate Mortgages: Evidence from Euro Area Banks]," Journal of the European Economic Association, European Economic Association, vol. 20(1), pages 513-548.
    8. Catherine Doz & Peter Fuleky, 2019. "Dynamic Factor Models," Working Papers 2019-4, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
    9. Potjagailo, Galina & Wolters, Maik H., 2023. "Global financial cycles since 1880," Journal of International Money and Finance, Elsevier, vol. 131(C).
    10. Kristina Barauskaite & Anh D. M. Nguyen, 2022. "Intersectoral network‐based channel of aggregate TFP shocks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 3897-3910, October.
    11. Bai, Jushan & Wang, Peng, 2012. "Identification and estimation of dynamic factor models," MPRA Paper 38434, University Library of Munich, Germany.
    12. Anna Burova & Alexey Ponomarenko & Svetlana Popova & Andrey Sinyakov & Yulia Ushakova, 2022. "Measuring Heterogeneity in Banks’ Interest Rate Setting in Russia," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(14), pages 4103-4119, November.
    13. Corsetti, G. & Duarte, J. B. & Mann, S., 2018. "One Money, Many Markets - A Factor Model Approach to Monetary Policy in the Euro Area with High-Frequency Identification," Cambridge Working Papers in Economics 1816, Faculty of Economics, University of Cambridge.
    14. Liu, Philip & Mumtaz, Haroon & Theophilopoulou, Angeliki, 2014. "The transmission of international shocks to the UK. Estimates based on a time-varying factor augmented VAR," Journal of International Money and Finance, Elsevier, vol. 46(C), pages 1-15.
    15. Christophe Blot & Fabien Labondance, 2021. "Beyond the Interest Rate Pass-through: Monetary Policy and Banks Interest Rates during the Effective Lower Bound," Working Papers hal-04221606, HAL.
    16. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    17. Ashima Goyal & Akhilesh K. Verma & Rajeswari Sengupta, 2022. "External shocks, cross-border flows and macroeconomic risks in emerging market economies," Empirical Economics, Springer, vol. 62(5), pages 2111-2148, May.
    18. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Papers 2310.17278, arXiv.org, revised Jan 2024.
    19. Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
    20. Martin Feldkircher & Gabriele Tondl, 2020. "Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(3), pages 225-247, August.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:rwirep:927. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/rwiesde.html .

    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.