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Linking Distress of Financial Institutions to Macrofinancial Shocks

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Listed:
  • Filippo di Mauro
  • Alexander Al-Haschimi
  • Stephane Dees
  • Martina Jancokova

Abstract

This paper links granular data of financial institutions to global macroeconomic variables using an infinite-dimensional vector autoregressive (IVAR) model framework. This framework is used to assess the impact of foreign macroeconomic shocks on default risks of euro area financial firms. In addition, the macroeconomic impact of firm-specific shocks is investigated. The approach taken nests a global VAR (GVAR) model, which allows an assessment of the two-way links between the financial system and the macroeconomy, while accounting for heterogeneity among financial institutions and the role of international linkages in the transmission of shocks. The model is estimated using macroeconomic data for 21 countries and default probability estimates for 35 euro area financial institutions. Overall, the results show that accounting for heterogeneity among firms is important for investigating the transmisson of shocks through the financial system. The model also captures the important role of international linkages, showing that macroeconomic shocks scaled to those observed following the Lehman bankruptcy generate a rise in firm-level default probabilities that is close to those observed during this time period. By linking a firm-level framework to a global model, the IVAR approach provides promising avenues for developing macro-prudential tools that can explicitly model spillover effects among a potentially large group of firms, while accounting for the two-way linkages between the financial sector and the macroeconomy, which were key transmission channels during the recent financial crisis.

Suggested Citation

  • Filippo di Mauro & Alexander Al-Haschimi & Stephane Dees & Martina Jancokova, 2014. "Linking Distress of Financial Institutions to Macrofinancial Shocks," EcoMod2014 6807, EcoMod.
    • Handle: RePEc:ekd:006356:6807
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    1. Pesaran, M. Hashem & Shin, Yongcheol & Smith, Richard J., 2000. "Structural analysis of vector error correction models with exogenous I(1) variables," Journal of Econometrics, Elsevier, vol. 97(2), pages 293-343, August.
    2. Bussiere Matthieu & Chudik Alexander & Mehl Arnaud, 2013. "How have global shocks impacted the real effective exchange rates of individual euro area countries since the euro’s creation?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 13(1), pages 1-48, April.
    3. Eickmeier, Sandra & Ng, Tim, 2015. "How do US credit supply shocks propagate internationally? A GVAR approach," European Economic Review, Elsevier, vol. 74(C), pages 128-145.
    4. Antonella Foglia, 2009. "Stress Testing Credit Risk: A Survey of Authorities' Aproaches," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 9-45, September.
    5. Filippo di Mauro & L. Vanessa Smith & Stephane Dees & M. Hashem Pesaran, 2007. "Exploring the international linkages of the euro area: a global VAR analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 1-38.
    6. Bailey, Natalia & Pesaran, M. Hashem & Smith, L. Vanessa, 2019. "A multiple testing approach to the regularisation of large sample correlation matrices," Journal of Econometrics, Elsevier, vol. 208(2), pages 507-534.
    7. De Bandt, Olivier & Hartmann, Philipp, 2000. "Systemic risk: A survey," Working Paper Series 35, European Central Bank.
    8. Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
    9. Alexander Chudik & M. Hashem Pesaran, 2013. "Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 592-649, August.
    10. Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 45-90, February.
    11. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    12. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    13. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    14. Mr. Dale F Gray, 2013. "Modeling Banking, Sovereign, and Macro Risk in a CCA Global VAR," IMF Working Papers 2013/218, International Monetary Fund.
    15. Rodrigo Alfaro & Mathias Drehmann, 2009. "Macro stress tests and crises: what can we learn?," BIS Quarterly Review, Bank for International Settlements, December.
    16. Castrén, Olli & Dées, Stéphane & Zaher, Fadi, 2010. "Stress-testing euro area corporate default probabilities using a global macroeconomic model," Journal of Financial Stability, Elsevier, vol. 6(2), pages 64-78, June.
    17. Kok, Christoffer & Gross, Marco, 2013. "Measuring contagion potential among sovereigns and banks using a mixed-cross-section GVAR," Working Paper Series 1570, European Central Bank.
    18. Heon Jin Park & Wayne A. Fuller, 1995. "Alternative Estimators And Unit Root Tests For The Autoregressive Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(4), pages 415-429, July.
    19. di Mauro, Filippo & Pesaran, M. Hashem (ed.), 2013. "The GVAR Handbook: Structure and Applications of a Macro Model of the Global Economy for Policy Analysis," OUP Catalogue, Oxford University Press, number 9780199670086.
    20. Mr. Papa M N'Diaye & Mr. Dale F Gray & Ms. Natalia T. Tamirisa & Ms. Hiroko Oura & Qianying Chen, 2010. "International Transmission of Bank and Corporate Distress," IMF Working Papers 2010/124, International Monetary Fund.
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    Cited by:

    1. Kok, Christoffer & Gross, Marco & Żochowski, Dawid, 2016. "The impact of bank capital on economic activity - evidence from a mixed-cross-section GVAR model," Working Paper Series 1888, European Central Bank.
    2. Laura Gianfagna & Armando Rungi, 2017. "Does corporate control matter to financial volatility?," Working Papers 09/2017, IMT School for Advanced Studies Lucca, revised Nov 2017.
    3. Behn, Markus & Gross, Marco & Peltonen, Tuomas A., 2016. "Assessing the costs and benefits of capital-based macroprudential policy," ESRB Working Paper Series 17, European Systemic Risk Board.

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    More about this item

    Keywords

    European countries; Macroeconometric modeling; Finance;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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