IDEAS home Printed from https://ideas.repec.org/a/gam/jecnmx/v7y2019i1p5-d198651.html
   My bibliography  Save this article

Information Flow in Times of Crisis: The Case of the European Banking and Sovereign Sectors

Author

Listed:
  • Mardi Dungey

    (Tasmanian School of Business and Economics, University of Tasmania, Hobart TAS 7001, Australia
    Mardi Dungey passed away just as this manuscript was accepted for publication.)

  • Stan Hurn

    (School of Economics and Finance, Queensland University of Technology, Brisbane QLD 4000, Australia)

  • Shuping Shi

    (Department of Economics, Macquarie University, Sydney 2109, Australia)

  • Vladimir Volkov

    (Tasmanian School of Business and Economics, University of Tasmania, Hobart TAS 7001, Australia)

Abstract

Crises in the banking and sovereign debt sectors give rise to heightened financial fragility. Of particular concern is the development of self-fulfilling feedback loops where crisis conditions in one sector are transmitted to the other sector and back again. We use time-varying tests of Granger causality to demonstrate how empirical evidence of connectivity between the banking and sovereign sectors can be detected, and provide an application to the Greek, Irish, Italian, Portuguese and Spanish (GIIPS) countries and Germany over the period 2007 to 2016. While the results provide evidence of domestic feedback loops, the most important finding is that financial fragility is an international problem and cannot be dealt with purely on a country-by-country basis.

Suggested Citation

  • Mardi Dungey & Stan Hurn & Shuping Shi & Vladimir Volkov, 2019. "Information Flow in Times of Crisis: The Case of the European Banking and Sovereign Sectors," Econometrics, MDPI, vol. 7(1), pages 1-20, January.
    • Handle: RePEc:gam:jecnmx:v:7:y:2019:i:1:p:5-:d:198651
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2225-1146/7/1/5/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2225-1146/7/1/5/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peter C. B. Phillips & Shu-Ping Shi & Jun Yu, 2011. "Testing for Multiple Bubbles," Working Papers CoFie-03-2011, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    2. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    3. Markus K. Brunnermeier & Luis Garicano & Philip R. Lane & Marco Pagano & Ricardo Reis & Tano Santos & David Thesmar & Stijn Van Nieuwerburgh & Dimitri Vayanos, 2016. "The Sovereign-Bank Diabolic Loop and ESBies," American Economic Review, American Economic Association, vol. 106(5), pages 508-512, May.
    4. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    5. Emmanuel Farhi & Jean Tirole, 2018. "Deadly Embrace: Sovereign and Financial Balance Sheets Doom Loops," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 85(3), pages 1781-1823.
    6. 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.
    7. Dungey, Mardi & Milunovich, George & Thorp, Susan & Yang, Minxian, 2015. "Endogenous crisis dating and contagion using smooth transition structural GARCH," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 71-79.
    8. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    9. Jean-Marie Dufour & Eric Renault, 1998. "Short Run and Long Run Causality in Time Series: Theory," Econometrica, Econometric Society, vol. 66(5), pages 1099-1126, September.
    10. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    11. Broto, Carmen & Pérez-Quirós, Gabriel, 2015. "Disentangling contagion among sovereign CDS spreads during the European debt crisis," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 165-179.
    12. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2015. "Systemic Risk and Stability in Financial Networks," American Economic Review, American Economic Association, vol. 105(2), pages 564-608, February.
    13. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    14. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    15. Peter C. B. Phillips, 2017. "Detecting Financial Collapse and Ballooning Sovereign Risk," Cowles Foundation Discussion Papers 3010, Cowles Foundation for Research in Economics, Yale University.
    16. Dungey, Mardi & Harvey, John & Volkov, Vladimir, 2019. "The changing international network of sovereign debt and financial institutions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 60(C), pages 149-168.
    17. Shuping Shi & Stan Hurn & Peter C B Phillips, 2016. "Causal Change Detection in Possibly Integrated Systems: Revisiting the Money-Income Relationship," NCER Working Paper Series 113, National Centre for Econometric Research.
    18. Jun Pan & Kenneth J. Singleton, 2008. "Default and Recovery Implicit in the Term Structure of Sovereign CDS Spreads," Journal of Finance, American Finance Association, vol. 63(5), pages 2345-2384, October.
    19. Peter C. B. Phillips & Shuping Shi, 2019. "Detecting Financial Collapse and Ballooning Sovereign Risk," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(6), pages 1336-1361, December.
    20. Swanson, Norman R., 1998. "Money and output viewed through a rolling window," Journal of Monetary Economics, Elsevier, vol. 41(3), pages 455-474, May.
    21. Selin Sayek & Fatma Taskin, 2014. "Financial crises: lessons from history for today [Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies]," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 29(79), pages 447-493.
    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. Meng-Horng Lee & Chee-Wooi Hooy & Robert Brooks, 2023. "A New Measure for Idiosyncratic Risk Based on Decomposition Method," JRFM, MDPI, vol. 16(1), pages 1-8, January.
    2. Matthew Greenwood‐Nimmo & Viet Hoang Nguyen & Eliza Wu, 2021. "On the International Spillover Effects of Country‐Specific Financial Sector Bailouts and Sovereign Risk Shocks," The Economic Record, The Economic Society of Australia, vol. 97(317), pages 285-309, June.
    3. Ahmed BenSaïda & Houda Litimi, 2021. "Financial contagion across G10 stock markets: A study during major crises," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4798-4821, July.

    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. Tomohiro Ando & Matthew Greenwood-Nimmo & Yongcheol Shin, 2022. "Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks," Management Science, INFORMS, vol. 68(4), pages 2401-2431, April.
    2. Mardi Dungey & John Harvey & Pierre Siklos & Vladimir Volkov, 2017. "Signed spillover effects building on historical decompositions," CAMA Working Papers 2017-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. Chowdhury, Biplob & Dungey, Mardi & Kangogo, Moses & Sayeed, Mohammad Abu & Volkov, Vladimir, 2019. "The changing network of financial market linkages: The Asian experience," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 71-92.
    4. Dungey, Mardi & Harvey, John & Volkov, Vladimir, 2019. "The changing international network of sovereign debt and financial institutions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 60(C), pages 149-168.
    5. Jonathan B. Hill, 2007. "Efficient tests of long-run causation in trivariate VAR processes with a rolling window study of the money-income relationship," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 747-765.
    6. Greenwood-Nimmo, Matthew & Huang, Jingong & Nguyen, Viet Hoang, 2019. "Financial sector bailouts, sovereign bailouts, and the transfer of credit risk," Journal of Financial Markets, Elsevier, vol. 42(C), pages 121-142.
    7. Hurn, Stan & Shi, Shuping & Wang, Ben, 2022. "Housing networks and driving forces," Journal of Banking & Finance, Elsevier, vol. 134(C).
    8. Marta Gómez-Puig & Simón Sosvilla-Rivero & Manish K. Singh, 2018. "“The robustness of the sovereign-bank interconnection: Evidence from contingent claims analysis”," IREA Working Papers 201804, University of Barcelona, Research Institute of Applied Economics, revised Feb 2018.
    9. Dungey, Mardi & Islam, Raisul & Volkov, Vladimir, 2020. "Crisis transmission: Visualizing vulnerability," Pacific-Basin Finance Journal, Elsevier, vol. 59(C).
    10. Dufour, Jean-Marie & Pelletier, Denis & Renault, Eric, 2006. "Short run and long run causality in time series: inference," Journal of Econometrics, Elsevier, vol. 132(2), pages 337-362, June.
    11. Capponi, Agostino & Corell, Felix & Stiglitz, Joseph E., 2022. "Optimal bailouts and the doom loop with a financial network," Journal of Monetary Economics, Elsevier, vol. 128(C), pages 35-50.
    12. Spyros Alogoskoufis & Sam Langfield, 2020. "Regulating the Doom Loop," International Journal of Central Banking, International Journal of Central Banking, vol. 16(4), pages 251-292, September.
    13. Jonathan B. Hill, 2005. "Causation Delays and Causal Neutralization up to Three Steps Ahead: The Money-Output Relationship Revisited," Econometrics 0503016, University Library of Munich, Germany, revised 23 Mar 2005.
    14. Bauer, Dietmar & Maynard, Alex, 2012. "Persistence-robust surplus-lag Granger causality testing," Journal of Econometrics, Elsevier, vol. 169(2), pages 293-300.
    15. Tang, Chor Foon, 2008. "A re-examination of the relationship between electricity consumption and economic growth in Malaysia," Energy Policy, Elsevier, vol. 36(8), pages 3067-3075, August.
    16. Paraskevi Salamaliki & Ioannis Venetis & Nicholas Giannakopoulos, 2013. "The causal relationship between female labor supply and fertility in the USA: updated evidence via a time series multi-horizon approach," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(1), pages 109-145, January.
    17. Jonathan B. Hill, 2004. "Causation Delays and Causal Neutralization for General Horizons: The Money-Output Relationship Revisited," Econometrics 0402002, University Library of Munich, Germany, revised 23 Mar 2005.
    18. Irina Balteanu & Aitor Erce, 2018. "Linking Bank Crises and Sovereign Defaults: Evidence from Emerging Markets," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 66(4), pages 617-664, December.
    19. DUFOUR, Jean-Marie & JOUINI, Tarek, 2005. "Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing," Cahiers de recherche 2005-12, Universite de Montreal, Departement de sciences economiques.
    20. Hoang, Thi Hong Van & Shahzad, Syed Jawad Hussain & Czudaj, Robert L., 2020. "Renewable energy consumption and industrial production: A disaggregated time-frequency analysis for the U.S," Energy Economics, Elsevier, vol. 85(C).

    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:gam:jecnmx:v:7:y:2019:i:1:p:5-:d:198651. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.