IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v61y2021i6d10.1007_s00181-020-01993-2.html
   My bibliography  Save this article

Model-based indicators for the identification of cyclical systemic risk

Author

Listed:
  • Jorge E. Galán

    (Banco de España. Alcalá)

  • Javier Mencía

    (Banco de España. Alcalá)

Abstract

The credit-to-GDP gap, as proposed by the Basel methodology, is the reference measure for the activation of the Countercyclical Capital Buffer. However, most of the countries implementing this instrument in recent years are not following its signals due to the large downward biases that it is presenting after the last financial crisis that do not reflect properly the current macrofinancial environment. In this context, credit gap measures that incorporate economic fundamentals may provide more accurate signals of cyclical systemic risk. We propose two alternative model-based indicators that account for these factors. We assess their performance using time series data from the 1970s for six European countries and compare them to the Basel gap. We find that our proposed models provide more accurate early warning signals of the build-up of cyclical systemic risk than the Basel gap, as well as lower biases after rapid changes in fundamentals. Furthermore, we identify the model specifications that are optimal for each of the countries considered. Our flexible approach can easily accommodate national specificities, which are key to maximize the performance of the models.

Suggested Citation

  • Jorge E. Galán & Javier Mencía, 2021. "Model-based indicators for the identification of cyclical systemic risk," Empirical Economics, Springer, vol. 61(6), pages 3179-3211, December.
  • Handle: RePEc:spr:empeco:v:61:y:2021:i:6:d:10.1007_s00181-020-01993-2
    DOI: 10.1007/s00181-020-01993-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-020-01993-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00181-020-01993-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cottarelli, Carlo & Dell'Ariccia, Giovanni & Vladkova-Hollar, Ivanna, 2005. "Early birds, late risers, and sleeping beauties: Bank credit growth to the private sector in Central and Eastern Europe and in the Balkans," Journal of Banking & Finance, Elsevier, vol. 29(1), pages 83-104, January.
    2. Mikael Juselius & Claudio Borio & Piti Disyatat & Mathias Drehmann, 2017. "Monetary Policy, the Financial Cycle, and Ultra-Low Interest Rates," International Journal of Central Banking, International Journal of Central Banking, vol. 13(3), pages 55-89, September.
    3. Duchi, Fabio & Elbourne, Adam, 2016. "Credit supply shocks in the Netherlands," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 51-71.
    4. Galati, Gabriele & Hindrayanto, Irma & Koopman, Siem Jan & Vlekke, Marente, 2016. "Measuring financial cycles in a model-based analysis: Empirical evidence for the United States and the euro area," Economics Letters, Elsevier, vol. 145(C), pages 83-87.
    5. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    6. Lang, Jan Hannes & Welz, Peter, 2018. "Semi-structural credit gap estimation," Working Paper Series 2194, European Central Bank.
    7. André Lucas & Siem Jan Koopman, 2005. "Business and default cycles for credit risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 311-323.
    8. Schüler, Yves Stephan & Hiebert, Paul P. & Peltonen, Tuomas A., 2015. "Characterising the financial cycle: A multivariate and time-varying approach," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112985, Verein für Socialpolitik / German Economic Association.
    9. Claessens, Stijn & Kose, M. Ayhan & Terrones, Marco E., 2012. "How do business and financial cycles interact?," Journal of International Economics, Elsevier, vol. 87(1), pages 178-190.
    10. Iñaki Aldasoro & Claudio Borio & Mathias Drehmann, 2018. "Early warning indicators of banking crises: expanding the family," BIS Quarterly Review, Bank for International Settlements, March.
    11. Babecký, Jan & Havránek, Tomáš & Matějů, Jakub & Rusnák, Marek & Šmídková, Kateřina & Vašíček, Bořek, 2013. "Leading indicators of crisis incidence: Evidence from developed countries," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 1-19.
    12. Chen, Xiaoshan & Kontonikas, Alexandros & Montagnoli, Alberto, 2012. "Asset prices, credit and the business cycle," Economics Letters, Elsevier, vol. 117(3), pages 857-861.
    13. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, November.
    14. Christian Dembiermont & Mathias Drehmann & Siriporn Muksakunratana, 2013. "How much does the private sector really borrow - a new database for total credit to the private non-financial sector," BIS Quarterly Review, Bank for International Settlements, March.
    15. 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.
    16. Rochelle M. Edge & Ralf R. Meisenzahl, 2011. "The unreliability of credit-to-GDP ratio gaps in real-time: Implications for countercyclical capital buffers," Finance and Economics Discussion Series 2011-37, Board of Governors of the Federal Reserve System (U.S.).
    17. Uwe Hassler & Jürgen Wolters, 2006. "Autoregressive distributed lag models and cointegration," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 59-74, March.
    18. Thomas Laubach & John C. Williams, 2003. "Measuring the Natural Rate of Interest," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1063-1070, November.
    19. 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.
    20. Rafael Repullo & Jesús Saurina, 2011. "The Countercyclical Capital Buffer of Basel III: A Critical Assessment," Working Papers wp2011_1102, CEMFI, revised Jun 2011.
    21. repec:zbw:bofrdp:2015_008 is not listed on IDEAS
    22. Harvey, Andrew & Snyder, Ralph D., 1990. "Structural time series models in inventory control," International Journal of Forecasting, Elsevier, vol. 6(2), pages 187-198, July.
    23. Mathias Drehmann & Claudio Borio & Kostas Tsatsaronis, 2012. "Characterising the financial cycle: don't lose sight of the medium term!," BIS Working Papers 380, Bank for International Settlements.
    24. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    25. Mathias Drehmann & Mikael Juselius, 2012. "Do debt service costs affect macroeconomic and financial stability?," BIS Quarterly Review, Bank for International Settlements, September.
    26. Peter K. Clark, 1987. "The Cyclical Component of U. S. Economic Activity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 797-814.
    27. Gerlach, Stefan & Peng, Wensheng, 2005. "Bank lending and property prices in Hong Kong," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 461-481, February.
    28. Moritz Schularick & Alan M. Taylor, 2012. "Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008," American Economic Review, American Economic Association, vol. 102(2), pages 1029-1061, April.
    29. 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.
    30. Mathias Drehmann & Claudio Borio & Kostas Tsatsaronis, 2011. "Anchoring Countercyclical Capital Buffers: The role of Credit Aggregates," International Journal of Central Banking, International Journal of Central Banking, vol. 7(4), pages 189-240, December.
    31. Hristov, Nikolay & Hülsewig, Oliver & Wollmershäuser, Timo, 2012. "Loan supply shocks during the financial crisis: Evidence for the Euro area," Journal of International Money and Finance, Elsevier, vol. 31(3), pages 569-592.
    32. Markus K. Brunnermeier & Yuliy Sannikov, 2014. "A Macroeconomic Model with a Financial Sector," American Economic Review, American Economic Association, vol. 104(2), pages 379-421, February.
    33. Maria Dolores Gadea Rivas & Gabriel Perez-Quiros, 2015. "The Failure To Predict The Great Recession—A View Through The Role Of Credit," Journal of the European Economic Association, European Economic Association, vol. 13(3), pages 534-559, June.
    34. 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.
    35. Adam Elbourne & Fabio Duchi, 2016. "Credit Supply Shocks in the Netherlands," CPB Discussion Paper 320, CPB Netherlands Bureau for Economic Policy Analysis.
    36. V. Coudert & J. Idier, 2016. "An Early Warning System for Macro-prudential Policy in France," Working papers 609, Banque de France.
    37. 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.
    38. Charles Goodhart & Boris Hofmann, 2008. "House prices, money, credit, and the macroeconomy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 24(1), pages 180-205, spring.
    39. Duchi, Fabio & Elbourne, Adam, 2016. "Credit supply shocks in the Netherlands," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 51-71.
    40. Gabriele Galati & Irma Hindrayanto & Siem Jan Koopman & Marente Vlekke, 2016. "Measuring financial cycles with a model-based filter: Empirical evidence for the United States and the euro area," DNB Working Papers 495, Netherlands Central Bank, Research Department.
    41. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    42. Travis J. Berge & Òscar Jordà, 2011. "Evaluating the Classification of Economic Activity into Recessions and Expansions," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(2), pages 246-277, April.
    43. Rochelle M. Edge & Ralf R. Meisenzahl, 2011. "The Unreliability of Credit-to-GDP Ratio Gaps in Real Time: Implications for Countercyclical Capital Buffers," International Journal of Central Banking, International Journal of Central Banking, vol. 7(4), pages 261-298, December.
    44. Eero Tölö & Helinä Laakkonen & Simo Kalatie, 2018. "Evaluating Indicators for Use in Setting the Countercyclical Capital Buffer," International Journal of Central Banking, International Journal of Central Banking, vol. 14(2), pages 51-112, March.
    45. Claudio Borio & Mathias Drehmann, 2009. "Assessing the risk of banking crises - revisited," BIS Quarterly Review, Bank for International Settlements, March.
    46. Julia Giese & Henrik Andersen & Oliver Bush & Christian Castro & Marc Farag & Sujit Kapadia, 2014. "The Credit‐To‐Gdp Gap And Complementary Indicators For Macroprudential Policy: Evidence From The Uk," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 19(1), pages 25-47, January.
    47. Mathias Drehmann & Claudio Borio & Leonardo Gambacorta & Gabriel Jiminez & Carlos Trucharte, 2010. "Countercyclical capital buffers: exploring options," BIS Working Papers 317, Bank for International Settlements.
    48. Christian Castro & Ángel Estrada & Jorge Martínez, 2016. "The countercyclical capital buffer in spain: an analysis of key guiding indicators," Working Papers 1601, Banco de España.
    49. 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.
    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. Jorge E. Galán & Javier Mencía, 2018. "Empirical assessment of alternative structural methods for identifying cyclical systemic risk in Europe," Working Papers 1825, Banco de España.
    2. Mathias Drehmann & James Yetman, 2021. "Which Credit Gap Is Better at Predicting Financial Crises? A Comparison of Univariate Filters," International Journal of Central Banking, International Journal of Central Banking, vol. 17(70), pages 1-31, October.
    3. Jorge E. Galán, 2019. "Measuring credit-to-gdp gaps. The hodrick-prescott filter revisited," Occasional Papers 1906, Banco de España.
    4. Terhi Jokipii & Reto Nyffeler & Stéphane Riederer, 2021. "Exploring BIS credit-to-GDP gap critiques: the Swiss case," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 157(1), pages 1-19, December.
    5. Hartwig, Benny & Meinerding, Christoph & Schüler, Yves S., 2021. "Identifying indicators of systemic risk," Journal of International Economics, Elsevier, vol. 132(C).
    6. O'Brien, Martin & Velasco, Sofia, 2020. "Unobserved components models with stochastic volatility for extracting trends and cycles in credit," Research Technical Papers 09/RT/20, Central Bank of Ireland.
    7. Lang, Jan Hannes & Welz, Peter, 2018. "Semi-structural credit gap estimation," Working Paper Series 2194, European Central Bank.
    8. Markus Behn & Carsten Detken & Tuomas Peltonen & Willem Schudel, 2017. "Predicting Vulnerabilities in the EU Banking Sector: The Role of Global and Domestic Factors," International Journal of Central Banking, International Journal of Central Banking, vol. 13(4), pages 147-189, December.
    9. Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2022. "Measuring financial cycles: Empirical evidence for Germany, United Kingdom and United States of America," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 599-630.
    10. Tihana Skrinjaric, 2023. "Leading indicators of financial stress in Croatia: a regime switching approach," Public Sector Economics, Institute of Public Finance, vol. 47(2), pages 205-232.
    11. 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.
    12. policy, Work stream on macroprudential & Albertazzi, Ugo & Martin, Alberto & Assouan, Emmanuelle & Tristani, Oreste & Galati, Gabriele & Vlassopoulos, Thomas, 2021. "The role of financial stability considerations in monetary policy and the interaction with macroprudential policy in the euro area," Occasional Paper Series 272, European Central Bank.
    13. Lenarčič, Črt, 2021. "Estimating business and financial cycles in Slovenia," MPRA Paper 109977, University Library of Munich, Germany.
    14. Christian Castro & Ángel Estrada & Jorge Martínez, 2016. "The countercyclical capital buffer in spain: an analysis of key guiding indicators," Working Papers 1601, Banco de España.
    15. Audit, Dooneshsingh & Alam, Nafis, 2022. "Why have credit variables taken centre stage in predicting systemic banking crises?," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 3(1).
    16. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    17. Gabriele Galati & Irma Hindrayanto & Siem Jan Koopman & Marente Vlekke, 2016. "Measuring financial cycles with a model-based filter: Empirical evidence for the United States and the euro area," DNB Working Papers 495, Netherlands Central Bank, Research Department.
    18. 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.
    19. policy, Work stream on macroprudential & Policy, Monetary & Stability, Financial & Albertazzi, Ugo & Martin, Alberto & Assouan, Emmanuelle & Tristani, Oreste & Galati, Gabriele & Vlassopoulos, Thomas , 2023. "The role of financial stability considerations in monetary policy and the interaction with macroprudential policy in the euro area," Occasional Paper Series 272, European Central Bank.
    20. Piotr Bańbuła & Marcin Pietrzak, 2021. "Early Warning Models of Banking Crises: VIX and High Profits," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(4), pages 381-403, December.

    More about this item

    Keywords

    Credit imbalances; Cyclical systemic risk; Early warning models; Macroprudential policy; Model-based indicators;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    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:spr:empeco:v:61:y:2021:i:6:d:10.1007_s00181-020-01993-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.