IDEAS home Printed from https://ideas.repec.org/p/srk/srkwps/2019102.html
   My bibliography  Save this paper

Exposition, climax, denouement: Life-cycle evaluation of the recent financial crisis in the EU by linking the ESRB financial crisis database to the European Commission's Macroeconomic Imbalance Procedure Scoreboard

Author

Listed:
  • Erhart, Szilard

Abstract

The paper investigates the life-cycle of the 2008-2009 financial crisis by linking the Macroeconomic Imbalance Procedure (MIP) Scoreboard of the European Commission to the crisis database of the European Systemic Risk Board (ESRB). The novelty of the analysis is that early warning capacity of MIP indicators is empirically tested in case of various crisis events case by case (i) Currency/Balance-of-Payment/Capital flow events, (ii) Sovereign crisis events, (iii) Banking crisis events and (iv) Significant asset price corrections in EU Member States. Furthermore, we contribute to the literature by studying the predicting power of the MIP Scoreboard in the identification of the overheating in the economy in advance of crises (preventive arm of the MIP). We found that the predictive power of the MIP Scoreboard may be twice as high to capture sovereign and Currency/Balance-of-Payment/Capital flow type of crisis events than its power to capture a banking crisis or serious asset price corrections. We confirm the results of earlier empirical studies that some MIP indicators perform relatively well (current account and net international position) in all specifications. A simple composite indicator based on the threshold breaches of MIP Scoreboard Indicators, performed in most cases as good as the best individual indicator, and hence could be considered as an input to a simple, rule based and accountable decision making. JEL Classification: C40, G01, E44, E61, G28

Suggested Citation

  • Erhart, Szilard, 2019. "Exposition, climax, denouement: Life-cycle evaluation of the recent financial crisis in the EU by linking the ESRB financial crisis database to the European Commission's Macroeconomic Imbalance Proced," ESRB Working Paper Series 102, European Systemic Risk Board.
  • Handle: RePEc:srk:srkwps:2019102
    as

    Download full text from publisher

    File URL: https://www.esrb.europa.eu//pub/pdf/wp/esrb.wp102~c6ae1dacd0.en.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    2. Frankel, Jeffrey & Saravelos, George, 2012. "Can leading indicators assess country vulnerability? Evidence from the 2008–09 global financial crisis," Journal of International Economics, Elsevier, vol. 87(2), pages 216-231.
    3. Babecký, Jan & Havránek, Tomáš & Matějů, Jakub & Rusnák, Marek & Šmídková, Kateřina & Vašíček, Bořek, 2014. "Banking, debt, and currency crises in developed countries: Stylized facts and early warning indicators," Journal of Financial Stability, Elsevier, vol. 15(C), pages 1-17.
    4. Christensen, Ian & Li, Fuchun, 2014. "Predicting financial stress events: A signal extraction approach," Journal of Financial Stability, Elsevier, vol. 14(C), pages 54-65.
    5. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    6. repec:ecb:fsrart:2018::2 is not listed on IDEAS
    7. Lo Duca, Marco & Koban, Anne & Basten, Marisa & Bengtsson, Elias & Klaus, Benjamin & Kusmierczyk, Piotr & Lang, Jan Hannes & Detken, Carsten & Peltonen, Tuomas, 2017. "A new database for financial crises in European countries," Occasional Paper Series 194, European Central Bank.
    8. Detken, Carsten & Fahr, Stephan & Lang, Jan Hannes, 2018. "Predicting the likelihood and severity of financial crises over the medium term with a cyclical systemic risk indicator," Financial Stability Review, European Central Bank, vol. 1.
    9. Mr. Luc Laeven & Mr. Fabian Valencia, 2018. "Systemic Banking Crises Revisited," IMF Working Papers 2018/206, International Monetary Fund.
    10. Tomáš, Domonkos & Filip, Ostrihoň & Ivana, Šikulová & Mária, Širaňová, 2017. "Analysing the Relevance of the MIP Scoreboard's Indicators," National Institute Economic Review, National Institute of Economic and Social Research, vol. 239, pages 32-52, February.
    11. Knedlik, Tobias, 2014. "The impact of preferences on early warning systems — The case of the European Commission's Scoreboard," European Journal of Political Economy, Elsevier, vol. 34(C), pages 157-166.
    12. Tomáš, Domonkos & Filip, Ostrihoň & Ivana, Šikulová & Mária, Širaňová, 2017. "Analysing the Relevance of the MIP Scoreboard's Indicators," National Institute Economic Review, National Institute of Economic and Social Research, vol. 239, pages 32-52, February.
    13. Claudio Borio & Mathias Drehmann, 2009. "Assessing the risk of banking crises - revisited," BIS Quarterly Review, Bank for International Settlements, March.
    14. Orsolya Csortos & Zoltán Szalai, 2014. "Early warning indicators: financial and macroeconomic imbalances in Central and Eastern European countries," MNB Working Papers 2014/2, Magyar Nemzeti Bank (Central Bank of Hungary).
    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. Mikkel Hermansen & Oliver Röhn, 2017. "Economic resilience: The usefulness of early warning indicators in OECD countries," OECD Journal: Economic Studies, OECD Publishing, vol. 2016(1), pages 9-35.
    2. Huynh, Tran & Uebelmesser, Silke, 2024. "Early warning models for systemic banking crises: Can political indicators improve prediction?," European Journal of Political Economy, Elsevier, vol. 81(C).
    3. Krzysztof Biegun & Jacek Karwowski & Piotr Luty, 2021. "How Effective is Macroeconomic Imbalance Procedure (MIP) in Predicting Negative Macroeconomic Phenomena?," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 822-837.
    4. Lang, Jan Hannes & Izzo, Cosimo & Fahr, Stephan & Ruzicka, Josef, 2019. "Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises," Occasional Paper Series 219, European Central Bank.
    5. Dieckelmann, Daniel, 2020. "Cross-border lending and the international transmission of banking crises," Discussion Papers 2020/13, Free University Berlin, School of Business & Economics.
    6. Sondermann, David & Zorell, Nico, 2019. "A macroeconomic vulnerability model for the euro area," Working Paper Series 2306, European Central Bank.
    7. Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2023. "Credit growth, the yield curve and financial crisis prediction: Evidence from a machine learning approach," Journal of International Economics, Elsevier, vol. 145(C).
    8. Xianglong Liu, 2023. "Towards Better Banking Crisis Prediction: Could an Automatic Variable Selection Process Improve the Performance?," The Economic Record, The Economic Society of Australia, vol. 99(325), pages 288-312, June.
    9. Boysen-Hogrefe, Jens & Jannsen, Nils & Plödt, Martin & Schwarzmüller, Tim, 2015. "An empirical evaluation of macroeconomic surveillance in the European Union," Kiel Working Papers 2014, Kiel Institute for the World Economy (IfW Kiel).
    10. V. Coudert & J. Idier, 2016. "An Early Warning System for Macro-prudential Policy in France," Working papers 609, Banque de France.
    11. Marcin Pietrzak, 2021. "Can Financial Soundness Indicators Help Predict Financial Sector Distress?," IMF Working Papers 2021/197, International Monetary Fund.
    12. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
    13. Gernát, Peter & Košťálová, Zuzana & Lyócsa, Štefan, 2020. "What drives U.S. financial sector volatility? A Bayesian model averaging perspective," Research in International Business and Finance, Elsevier, vol. 51(C).
    14. Cabral, Inês & Detken, Carsten & Fell, John & Henry, Jérôme & Hiebert, Paul & Kapadia, Sujit & Pires, Fatima & Salleo, Carmelo & Constâncio, Vítor & Nicoletti Altimari, Sergio, 2019. "Macroprudential policy at the ECB: Institutional framework, strategy, analytical tools and policies," Occasional Paper Series 227, European Central Bank.
    15. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    16. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    17. Truong, Chi & Sheen, Jeffrey & Trück, Stefan & Villafuerte, James, 2022. "Early warning systems using dynamic factor models: An application to Asian economies," Journal of Financial Stability, Elsevier, vol. 58(C).
    18. Alonso-Alvarez, Irma & Molina, Luis, 2023. "How to foresee crises? A new synthetic index of vulnerabilities for emerging economies," Economic Modelling, Elsevier, vol. 125(C).
    19. Oliver Röhn & Aida Caldera Sánchez & Mikkel Hermansen & Morten Rasmussen, 2015. "Economic resilience: A new set of vulnerability indicators for OECD countries," OECD Economics Department Working Papers 1249, OECD Publishing.
    20. Fendel Ralf & Stremmel Hanno, 2016. "Characteristics of Banking Crises: A Comparative Study with Geographical Contagion," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 349-388, May.

    More about this item

    Keywords

    boom and bust; early warning system; financial crisis; macroeconomic imbalance procedure; signal approach; systemic risk;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    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:srk:srkwps:2019102. 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: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/esrbede.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.