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Early Warning Indicators of Economic Crises: Evidence from a Panel of 40 Developed Countries

Author

Listed:
  • Jan Babecky
  • Tomas Havranek
  • Jakub Mateju
  • Marek Rusnak
  • Katerina Smidkova
  • Borek Vasicek
Abstract
Using a panel of 40 EU and OECD countries for the period 1970-2010 we construct an early warning system. The system consists of a discrete and a continuous model. In the discrete model, we collect an extensive database of various types of economic crises called CDEC 40-40 and examine potential leading indicators. In the continuous model, we construct an index of real crisis incidence as the response variable. We determine the optimal lead employing panel vector autoregression for each potential indicator, and then select useful indicators employing Bayesian model averaging. We re-estimate the resulting specification by system GMM and, to allow for country heterogeneity, additionally evaluate the random coefficients estimator and divide countries into clusters. Our results suggest that global variables are among the most useful early warning indicators. In addition, housing prices emerge consistently as an important source of risk. Finally, we simulate the past effectiveness of several policy instruments and conclude that some central bank tools (for example, reserves) could be useful in mitigating crisis incidence.

Suggested Citation

  • Jan Babecky & Tomas Havranek & Jakub Mateju & Marek Rusnak & Katerina Smidkova & Borek Vasicek, 2011. "Early Warning Indicators of Economic Crises: Evidence from a Panel of 40 Developed Countries," Working Papers 2011/08, Czech National Bank.
    • Handle: RePEc:cnb:wpaper:2011/08
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Geršl, Adam & Lešanovská, Jitka, 2014. "Explaining the Czech interbank market risk premium," Economic Systems, Elsevier, vol. 38(4), pages 536-551.
    2. Hans-Eggert Reimers, 2012. "Early Warning Indicator Model of Financial Developments Using an Ordered Logit," Business and Economic Research, Macrothink Institute, vol. 2(2), pages 171-191, December.
    3. Lainà, Patrizio & Nyholm, Juho & Sarlin, Peter, 2015. "Leading indicators of systemic banking crises: Finland in a panel of EU countries," Review of Financial Economics, Elsevier, vol. 24(C), pages 18-35.
    4. Yusuf Yıldırım & Anirban Sanyal, 2022. "Evaluating the Effectiveness of Early Warning Indicators: An Application of Receiver Operating Characteristic Curve Approach to Panel Data," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, vol. 69(4), pages 557-597, December.
    5. Piergiorgio Alessandri & Pierluigi Bologna & Roberta Fiori & Enrico Sette, 2015. "A note on the implementation of the countercyclical capital buffer in Italy," Questioni di Economia e Finanza (Occasional Papers) 278, Bank of Italy, Economic Research and International Relations Area.
    6. Jan Frait & Zlatuse Komarkova, 2012. "Macroprudential Policy and Its Instruments in a Small EU Economy," Research and Policy Notes 2012/03, Czech National Bank.
    7. Petr Jakubík & Tomáš Slacík, 2013. "Measuring Financial (In)Stability in Emerging Europe: A New Index-Based Approach," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 25, pages 102-117.
    8. Detken, Carsten & Weeken, Olaf & Alessi, Lucia & Bonfim, Diana & Boucinha, Miguel & Castro, Christian & Frontczak, Sebastian & Giordana, Gaston & Giese, Julia & Wildmann, Nadya & Kakes, Jan & Klaus, B, 2014. "Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options," ESRB Occasional Paper Series 5, European Systemic Risk Board.
    9. Catullo, Ermanno & Gallegati, Mauro & Palestrini, Antonio, 2015. "Towards a credit network based early warning indicator for crises," Journal of Economic Dynamics and Control, Elsevier, vol. 50(C), pages 78-97.
    10. Bussière, M., 2013. "In Defense of Early Warning Signals," Working papers 420, Banque de France.
    11. Mojmír Hampl and Tomáš Havránek, 2017. "Should monetary policy pay attention to house prices? The Czech National Bank’s approach," BIS Papers chapters, in: Bank for International Settlements (ed.), Macroprudential policy frameworks, implementation and relationships with other policies, volume 94, pages 129-140, Bank for International Settlements.
    12. Ayi Supriyadi, 2015. "External vulnerability indicators: the case of Indonesia," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Indicators to support monetary and financial stability analysis: data sources and statistical methodologies, volume 39, Bank for International Settlements.
    13. Baker Shnekat & Ghazi Al-Assaf, 2020. "The Impact of Political Stability on the Effectiveness of the Early Warning Systems in Predicting the Financial Crises: The Case of Jordan and Qatar," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(4), pages 398-407, July.
    14. Fabio Saracco & Riccardo Di Clemente & Andrea Gabrielli & Tiziano Squartini, 2015. "Detecting early signs of the 2007-2008 crisis in the world trade," Papers 1508.03533, arXiv.org, revised Jul 2016.
    15. Diana Zigraiova & Petr Jakubik, 2014. "Systemic Event Prediction by Early Warning System," Working Papers IES 2014/01, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Jan 2014.
    16. Lainà, Patrizio & Nyholm, Juho & Sarlin, Peter, 2015. "Leading indicators of systemic banking crises: Finland in a panel of EU countries," Review of Financial Economics, Elsevier, vol. 24(C), pages 18-35.
    17. Lukáš Pfeifer & Zdeněk Pikhart, 2014. "Vztah finanční a cenové stability v podmínkách ČR [The Relationship of Financial and Price Stability in the Context of the Czech Republic]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(1), pages 49-66.
    18. Jesús Crespo Cuaresma & Martin Feldkircher, 2012. "Drivers of Output Loss during the 2008–09 Crisis: A Focus on Emerging Europe," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue 2, pages 46-64.
    19. Rakesh Padhan & K. P. Prabheesh, 2019. "Effectiveness Of Early Warning Models: A Critical Review And New Agenda For Future Direction," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 457-484, December.
    20. repec:zbw:bofrdp:2014_014 is not listed on IDEAS
    21. Tomas Adam & Sona Benecka, 2013. "Financial Stress Spillover and Financial Linkages between the Euro Area and the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(1), pages 46-64, March.
    22. Martin Mandel & Vladimír Tomšík, 2015. "Dynamika a rovnováha úspor, investic a úvěru v hospodářském cyklu: příklad České republiky [Dynamics and Balance of Savings, Investments, and Credits in Business Cycle: The Case of the Czech Republ," Politická ekonomie, Prague University of Economics and Business, vol. 2015(1), pages 32-56.
    23. Ermanno Catullo & Antonio Palestrini & Ruggero Grilli & Mauro Gallegati, 2018. "Early warning indicators and macro-prudential policies: a credit network agent based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 81-115, April.
    24. Carsten Detken & Olaf Weeken & Lucia Alessi & Diana Bonfim & Miguel M. Boucinha & Christian Castro & Sebastian Frontczak & Gaston Giordana & Julia Giese & Nadya Jahn & Jan Kakes & Benjamin Klaus & Jan, 2014. "Operationalising the countercyclical capital buffer: indicator selection, threshold identification and calibration options," ESRB Occasional Paper Series 05, European Systemic Risk Board.

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    More about this item

    Keywords

    Bayesian model averaging; dynamic panel; early warning indicators; macroprudential policies; panel VAR.;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G01 - Financial Economics - - General - - - Financial Crises

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