IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/20212614.html
   My bibliography  Save this paper

Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach

Author

Listed:
  • Bluwstein, Kristina
  • Buckmann, Marcus
  • Joseph, Andreas
  • Kapadia, Sujit
  • Şimşek, Özgür

Abstract

We develop early warning models for financial crisis prediction by applying machine learning techniques to macrofinancial data for 17 countries over 1870–2016. Most nonlin-ear machine learning models outperform logistic regression in out-of-sample predictions and forecasting. We identify economic drivers of our machine learning models using a novel framework based on Shapley values, uncovering nonlinear relationships between the predic-tors and crisis risk. Throughout, the most important predictors are credit growth and the slope of the yield curve, both domestically and globally. A flat or inverted yield curve is of most concern when nominal interest rates are low and credit growth is high. JEL Classification: C40, C53, E44, F30, G01

Suggested Citation

  • Bluwstein, Kristina & Buckmann, Marcus & Joseph, Andreas & Kapadia, Sujit & Şimşek, Özgür, 2021. "Credit growth, the yield curve and financial crisis prediction: evidence from a machine learning approach," Working Paper Series 2614, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20212614
    Note: 2453540
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecb.wp2614~6974517ac3.en.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Akinci, Ozge & Olmstead-Rumsey, Jane, 2018. "How effective are macroprudential policies? An empirical investigation," Journal of Financial Intermediation, Elsevier, vol. 33(C), pages 33-57.
    2. López-Salido, J David & Baker, Sarah S. & Nelson, Edward, 2018. "The Money View Versus the Credit View," CEPR Discussion Papers 12982, C.E.P.R. Discussion Papers.
    3. Maurice Obstfeld & Jay C. Shambaugh & Alan M. Taylor, 2005. "The Trilemma in History: Tradeoffs Among Exchange Rates, Monetary Policies, and Capital Mobility," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 423-438, August.
    4. Hyman P. Minsky, 1977. "The Financial Instability Hypothesis: An Interpretation of Keynes and an Alternative to“Standard” Theory," Challenge, Taylor & Francis Journals, vol. 20(1), pages 20-27, March.
    5. Aikman, David & Nelson, Benjamin & Tanaka, Misa, 2015. "Reputation, risk-taking, and macroprudential policy," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 428-439.
    6. Diebold, Francis X. & Li, Canlin & Yue, Vivian Z., 2008. "Global yield curve dynamics and interactions: A dynamic Nelson-Siegel approach," Journal of Econometrics, Elsevier, vol. 146(2), pages 351-363, October.
    7. Robert Z. Aliber & Charles P. Kindleberger, 2015. "Manias, Panics, and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-1-137-52574-1, March.
    8. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    9. Òscar Jordà & Moritz Schularick & Alan M. Taylor, 2017. "Macrofinancial History and the New Business Cycle Facts," NBER Macroeconomics Annual, University of Chicago Press, vol. 31(1), pages 213-263.
    10. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
    11. Claudio Borio & Mathias Drehmann, 2011. "Toward an Operational Framework for Financial Stability: “Fuzzy” Measurement and Its Consequences," Central Banking, Analysis, and Economic Policies Book Series, in: Rodrigo Alfaro (ed.),Financial Stability, Monetary Policy, and Central Banking, edition 1, volume 15, chapter 4, pages 063-123, Central Bank of Chile.
    12. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    13. Björn Richter & Moritz Schularick & Paul Wachtel, 2021. "When to Lean against the Wind," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(1), pages 5-39, February.
    14. 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.
    15. Andreas Joseph, 2019. "Parametric inference with universal function approximators," Papers 1903.04209, arXiv.org, revised Oct 2020.
    16. 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.
    17. Drehmann, Mathias & Juselius, Mikael, 2014. "Evaluating early warning indicators of banking crises: Satisfying policy requirements," International Journal of Forecasting, Elsevier, vol. 30(3), pages 759-780.
    18. Tobias Adrian & Arturo Estrella & Hyun Song Shin, 2010. "Monetary cycles, financial cycles, and the business cycle," Staff Reports 421, Federal Reserve Bank of New York.
    19. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
    20. Jeremy Fouliard & Michael Howell & Hélène Rey & Vania Stavrakeva, 2020. "Answering the Queen: Machine Learning and Financial Crises," NBER Working Papers 28302, National Bureau of Economic Research, Inc.
    21. 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.
    22. David Aikman & Mirta Galesic & Gerd Gigerenzer & Sujit Kapadia & Konstantinos Katsikopoulos & Amit Kothiyal & Emma Murphy & Tobias Neumann, 2021. "Taking uncertainty seriously: simplicity versus complexity in financial regulation [Uncertainty in macroeconomic policy-making: art or science?]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(2), pages 317-345.
    23. Iñaki Aldasoro & Claudio Borio & Mathias Drehmann, 2018. "Early warning indicators of banking crises: expanding the family," BIS Quarterly Review, Bank for International Settlements, March.
    24. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    25. Manasse, Paolo & Roubini, Nouriel, 2009. ""Rules of thumb" for sovereign debt crises," Journal of International Economics, Elsevier, vol. 78(2), pages 192-205, July.
    26. Patrice Ollivaud & David Turner, 2015. "The effect of the global financial crisis on OECD potential output," OECD Journal: Economic Studies, OECD Publishing, vol. 2014(1), pages 41-60.
    27. Frankel, Jeffrey & Schmukler, Sergio L. & Serven, Luis, 2004. "Global transmission of interest rates: monetary independence and currency regime," Journal of International Money and Finance, Elsevier, vol. 23(5), pages 701-733, September.
    28. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    29. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Varieties of Crises and Their Dates," Introductory Chapters, in: This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press.
    30. Concha Betrán & María A. Pons, 2013. "Understanding Spanish Financial crises, 1850-2000: What determined their severity?," Working Papers 0048, European Historical Economics Society (EHES).
    31. Casabianca, Elizabeth Jane & Catalano, Michele & Forni, Lorenzo & Giarda, Elena & Passeri, Simone, 2022. "A machine learning approach to rank the determinants of banking crises over time and across countries," Journal of International Money and Finance, Elsevier, vol. 129(C).
    32. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    33. Robin Greenwood & Samuel G. Hanson & Andrei Shleifer & Jakob Ahm Sørensen, 2022. "Predictable Financial Crises," Journal of Finance, American Finance Association, vol. 77(2), pages 863-921, April.
    34. John C. Driscoll & Aart C. Kraay, 1998. "Consistent Covariance Matrix Estimation With Spatially Dependent Panel Data," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 549-560, November.
    35. Lars Jonoug & Jaakko Kiander & Pentti Vartia (ed.), 2009. "The Great Financial Crisis in Finland and Sweden," Books, Edward Elgar Publishing, number 13404.
    36. Cesa-Bianchi, Ambrogio & Eguren Martin, Fernando & Thwaites, Gregory, 2019. "Foreign booms, domestic busts: The global dimension of banking crises," Journal of Financial Intermediation, Elsevier, vol. 37(C), pages 58-74.
    37. Mr. Fabian Valencia & Mr. Luc Laeven, 2008. "Systemic Banking Crises: A New Database," IMF Working Papers 2008/224, International Monetary Fund.
    38. Mitchener, Kris James & Weidenmier, Marc D., 2008. "The Baring Crisis and the Great Latin American Meltdown of the 1890s," The Journal of Economic History, Cambridge University Press, vol. 68(2), pages 462-500, June.
    39. √Íscar Jord√Ä & Moritz Schularick & Alan M. Taylor, 2013. "When Credit Bites Back," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(s2), pages 3-28, December.
    40. 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.
    41. Jon Danielsson & Marcela Valenzuela & Ilknur Zer, 2018. "Learning from History: Volatility and Financial Crises," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2774-2805.
    42. Robert J. Shiller, 2017. "Narrative Economics," American Economic Review, American Economic Association, vol. 107(4), pages 967-1004, April.
    43. Cerutti, Eugenio & Claessens, Stijn & Laeven, Luc, 2017. "The use and effectiveness of macroprudential policies: New evidence," Journal of Financial Stability, Elsevier, vol. 28(C), pages 203-224.
    44. Bernanke, Ben S & Blinder, Alan S, 1992. "The Federal Funds Rate and the Channels of Monetary Transmission," American Economic Review, American Economic Association, vol. 82(4), pages 901-921, September.
    45. Serena Ng, 2014. "Viewpoint: Boosting Recessions," Canadian Journal of Economics, Canadian Economics Association, vol. 47(1), pages 1-34, February.
    46. Hoggarth, Glenn & Reis, Ricardo & Saporta, Victoria, 2002. "Costs of banking system instability: Some empirical evidence," Journal of Banking & Finance, Elsevier, vol. 26(5), pages 825-855, May.
    47. Victor Chernozhukov & Mert Demirer & Esther Duflo & Ivan Fernandez-Val, 2017. "Generic machine learning inference on heterogenous treatment effects in randomized experiments," CeMMAP working papers CWP61/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    48. Mirko Abbritti & Salvatore Dell’Erba & Antonio Moreno & Sergio Sola, 2018. "Global Factors in the Term Structure of Interest Rates," International Journal of Central Banking, International Journal of Central Banking, vol. 14(2), pages 301-340, March.
    49. Robert Vermeulen & Marco Hoeberichts & Bořek Vašíček & Diana Žigraiová & Kateřina Šmídková & Jakob Haan, 2015. "Financial Stress Indices and Financial Crises," Open Economies Review, Springer, vol. 26(3), pages 383-406, July.
    50. 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.
    51. Michael Bordo & Barry Eichengreen & Daniela Klingebiel & Maria Soledad Martinez-Peria, 2001. "Is the crisis problem growing more severe?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 16(32), pages 52-82.
    52. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    53. Borio, Claudio & Zhu, Haibin, 2012. "Capital regulation, risk-taking and monetary policy: A missing link in the transmission mechanism?," Journal of Financial Stability, Elsevier, vol. 8(4), pages 236-251.
    54. Aikman, David & Bridges, Jonathan & Hacioglu Hoke, Sinem & O’Neill, Cian & Raja, Akash, 2019. "Credit, capital and crises: a GDP-at-Risk approach," Bank of England working papers 824, Bank of England, revised 18 Oct 2019.
    55. 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.
    56. Rudebusch, Glenn D. & Williams, John C., 2009. "Forecasting Recessions: The Puzzle of the Enduring Power of the Yield Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 492-503.
    57. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    58. Döpke, Jörg & Fritsche, Ulrich & Pierdzioch, Christian, 2017. "Predicting recessions with boosted regression trees," International Journal of Forecasting, Elsevier, vol. 33(4), pages 745-759.
    59. John B. Taylor, 2009. "The Financial Crisis and the Policy Responses: An Empirical Analysis of What Went Wrong," NBER Working Papers 14631, National Bureau of Economic Research, Inc.
    60. Matthew Baron & Emil Verner & Wei Xiong, 2021. "Banking Crises Without Panics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 136(1), pages 51-113.
    61. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Is the 2007 US Sub-Prime Financial Crisis So Different?: An International Historical Comparison," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 56(3), pages 291-299.
    62. Wade, Robert, 1998. "The Asian debt-and-development crisis of 1997-?: Causes and consequences," World Development, Elsevier, vol. 26(8), pages 1535-1553, August.
    63. Aikman, David & Haldane, Andrew & Hinterschweiger, Marc & Kapadia, Sujit, 2018. "Rethinking financial stability," Bank of England working papers 712, Bank of England.
    64. Mark Joy & Marek Rusnák & Kateřina Šmídková & Bořek Vašíček, 2017. "Banking and Currency Crises: Differential Diagnostics for Developed Countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 44-67, January.
    65. 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.
    66. Menard, Scott, 2004. "Six Approaches to Calculating Standardized Logistic Regression Coefficients," The American Statistician, American Statistical Association, vol. 58, pages 218-223, August.
    67. Pagan, Adrian, 1984. "Econometric Issues in the Analysis of Regressions with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 25(1), pages 221-247, February.
    68. Stephen G. Cecchetti & Marion Kohler & Christian Upper, 2009. "Financial crises and economic activity," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 89-135.
    69. Duttagupta, Rupa & Cashin, Paul, 2011. "Anatomy of banking crises in developing and emerging market countries," Journal of International Money and Finance, Elsevier, vol. 30(2), pages 354-376, March.
    70. Philip Lowe & Claudio Borio, 2002. "Asset prices, financial and monetary stability: exploring the nexus," BIS Working Papers 114, Bank for International Settlements.
    71. Coleman IV, Major & LaCour-Little, Michael & Vandell, Kerry D., 2008. "Subprime lending and the housing bubble: Tail wags dog?," Journal of Housing Economics, Elsevier, vol. 17(4), pages 272-290, December.
    72. Adrian, Tobias & Song Shin, Hyun, 2010. "Financial Intermediaries and Monetary Economics," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 12, pages 601-650, Elsevier.
    73. Fujimoto, Katsushige & Kojadinovic, Ivan & Marichal, Jean-Luc, 2006. "Axiomatic characterizations of probabilistic and cardinal-probabilistic interaction indices," Games and Economic Behavior, Elsevier, vol. 55(1), pages 72-99, April.
    74. Rey, Hélène, 2015. "Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence," CEPR Discussion Papers 10591, C.E.P.R. Discussion Papers.
    75. Giese, Julia & Nelson, Benjamin & Tanaka, Misa & Tarashev, Nikola, 2013. "Financial Stability Paper No 21: How could macroprudential policy affect financial system resilience and credit? Lessons from the literature," Bank of England Financial Stability Papers 21, Bank of England.
    76. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    77. Mr. Luc Laeven & Mr. Fabian Valencia, 2018. "Systemic Banking Crises Revisited," IMF Working Papers 2018/206, International Monetary Fund.
    78. Claudio Borio & Leonardo Gambacorta & Boris Hofmann, 2017. "The influence of monetary policy on bank profitability," International Finance, Wiley Blackwell, vol. 20(1), pages 48-63, March.
    79. Roberto Savona & Marika Vezzoli, 2015. "Fitting and Forecasting Sovereign Defaults using Multiple Risk Signals," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 66-92, February.
    80. B. De Backer & M. Deroose & Ch. Van Nieuwenhuyze, 2019. "Is a recession imminent? The signal of the yield curve," Economic Review, National Bank of Belgium, issue i, pages 69-93, June.
    81. Kauko, Karlo & Tölö, Eero, 2019. "On the long-run calibration of the credit-to-GDP gap as a banking crisis predictor," Bank of Finland Research Discussion Papers 6/2019, Bank of Finland.
    82. Felix Ward, 2017. "Spotting the Danger Zone: Forecasting Financial Crises With Classification Tree Ensembles and Many Predictors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(2), pages 359-378, March.
    83. Rey, Hélène & ,, 2017. "Financial Cycles with Heterogeneous Intermediaries," CEPR Discussion Papers 11907, C.E.P.R. Discussion Papers.
    84. Marcus Buckmann & Andreas Joseph, 2023. "An Interpretable Machine Learning Workflow with an Application to Economic Forecasting," International Journal of Central Banking, International Journal of Central Banking, vol. 19(4), pages 449-522, October.
    85. Aikman, David & Galesic, Mirta & Gigerenzer, Gerd & Kapadia, Sujit & Katsikopoulos, Konstantinos & Kothiyal, Amit & Murphy, Emma & Neumann, Tobias, 2014. "Financial Stability Paper No 28: Taking uncertainty seriously - simplicity versus complexity in financial regulation," Bank of England Financial Stability Papers 28, Bank of England.
    86. Mukund Sundararajan & Amir Najmi, 2019. "The many Shapley values for model explanation," Papers 1908.08474, arXiv.org, revised Feb 2020.
    87. Bussiere, Matthieu & Fratzscher, Marcel, 2006. "Towards a new early warning system of financial crises," Journal of International Money and Finance, Elsevier, vol. 25(6), pages 953-973, October.
    88. 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.
    89. Robert Vermeulen & Marco Hoeberichts & Bořek Vašíček & Diana Žigraiová & Kateřina Šmídková & Jakob Haan, 2015. "Financial Stress Indices and Financial Crises," Open Economies Review, Springer, vol. 26(3), pages 383-406, July.
    90. Plosser, Charles I. & Geert Rouwenhorst, K., 1994. "International term structures and real economic growth," Journal of Monetary Economics, Elsevier, vol. 33(1), pages 133-155, February.
    91. Dean Croushore & Katherine Marsten, 2016. "Reassessing the Relative Power of the Yield Spread in Forecasting Recessions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(6), pages 1183-1191, September.
    92. repec:zbw:bofrdp:2019_006 is not listed on IDEAS
    93. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    94. Carmona, Pedro & Climent, Francisco & Momparler, Alexandre, 2019. "Predicting failure in the U.S. banking sector: An extreme gradient boosting approach," International Review of Economics & Finance, Elsevier, vol. 61(C), pages 304-323.
    95. Jonathan H. Wright, 2006. "The yield curve and predicting recessions," Finance and Economics Discussion Series 2006-07, Board of Governors of the Federal Reserve System (U.S.).
    96. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
    97. Pablo Martín-Aceña, 2014. "The Savings Banks crises in Spain: When and How?," Documentos de Trabajo (DT-AEHE) 1404, Asociación Española de Historia Económica.
    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. Potjagailo, Galina & Wolters, Maik H., 2023. "Global financial cycles since 1880," Journal of International Money and Finance, Elsevier, vol. 131(C).
    2. Simon Lloyd & Ed Manuel & Konstantin Panchev, 2024. "Foreign Vulnerabilities, Domestic Risks: The Global Drivers of GDP-at-Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 72(1), pages 335-392, March.
    3. Jeremy Fouliard & Michael Howell & Hélène Rey & Vania Stavrakeva, 2020. "Answering the Queen: Machine Learning and Financial Crises," NBER Working Papers 28302, National Bureau of Economic Research, Inc.
    4. Hurley, James & Karmakar, Sudipto & Markoska, Elena & Walczak, Eryk & Walker, Danny, 2021. "Impacts of the Covid-19 crisis: evidence from 2 million UK SMEs," Bank of England working papers 924, Bank of England.
    5. Hyeongwoo Kim & Wen Shi, 2021. "Forecasting financial vulnerability in the USA: A factor model approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(3), pages 439-457, April.
    6. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    7. Seulki Chung, 2023. "Inside the black box: Neural network-based real-time prediction of US recessions," Papers 2310.17571, arXiv.org, revised May 2024.
    8. Buckmann, Marcus & Haldane, Andy & Hüser, Anne-Caroline, 2021. "Comparing minds and machines: implications for financial stability," Bank of England working papers 937, Bank of England.
    9. Tamás Kristóf, 2021. "Sovereign Default Forecasting in the Era of the COVID-19 Crisis," JRFM, MDPI, vol. 14(10), pages 1-24, October.
    10. Luca Tiozzo Pezzoli & Elisa Tosetti, 2022. "Seismonomics: Listening to the heartbeat of the economy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 288-309, December.
    11. Moreno Badia, Marialuz & Medas, Paulo & Gupta, Pranav & Xiang, Yuan, 2022. "Debt is not free," Journal of International Money and Finance, Elsevier, vol. 127(C).
    12. 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).
    13. Barbara Jarmulska, 2022. "Random forest versus logit models: Which offers better early warning of fiscal stress?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 455-490, April.
    14. Antulov-Fantulin, Nino & Lagravinese, Raffaele & Resce, Giuliano, 2021. "Predicting bankruptcy of local government: A machine learning approach," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 681-699.
    15. du Plessis, Emile & Fritsche, Ulrich, 2022. "New forecasting methods for an old problem: Predicting 147 years of systemic financial crises," WiSo-HH Working Paper Series 67, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
    16. Peter Breyer & Stefan Girsch & Jakob Hanzl & Mario Hübler & Sophie Steininger & Elisabeth Wittig, 2023. "An analysis of Austrian banks during the high inflation period of the 1970s," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 45, pages 45-59.
    17. Bitetto, Alessandro & Cerchiello, Paola & Mertzanis, Charilaos, 2023. "On the efficient synthesis of short financial time series: A Dynamic Factor Model approach," Finance Research Letters, Elsevier, vol. 53(C).
    18. Ademmer, Martin & Beckmann, Joscha & Bode, Eckhardt & Boysen-Hogrefe, Jens & Funke, Manuel & Hauber, Philipp & Heidland, Tobias & Hinz, Julian & Jannsen, Nils & Kooths, Stefan & Söder, Mareike & Stame, 2021. "Big Data in der makroökonomischen Analyse," Kieler Beiträge zur Wirtschaftspolitik 32, Kiel Institute for the World Economy (IfW Kiel).
    19. Simona Malovaná & Josef Bajzík & Dominika Ehrenbergerová & Jan Janků, 2023. "A prolonged period of low interest rates in Europe: Unintended consequences," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 526-572, April.
    20. Jiaming Liu & Chengzhang Li & Peng Ouyang & Jiajia Liu & Chong Wu, 2023. "Interpreting the prediction results of the tree‐based gradient boosting models for financial distress prediction with an explainable machine learning approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1112-1137, August.
    21. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
    22. Roy, Dibyendu & Zhu, Shunmin & Wang, Ruiqi & Mondal, Pradip & Ling-Chin, Janie & Roskilly, Anthony Paul, 2024. "Techno-economic and environmental analyses of hybrid renewable energy systems for a remote location employing machine learning models," Applied Energy, Elsevier, vol. 361(C).
    23. Klieber, Karin, 2024. "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 159(C).
    24. Bitetto, Alessandro & Cerchiello, Paola & Mertzanis, Charilaos, 2023. "Measuring financial soundness around the world: A machine learning approach," International Review of Financial Analysis, Elsevier, vol. 85(C).
    25. Suss, Joel & Treitel, Henry, 2019. "Predicting bank distress in the UK with machine learning," Bank of England working papers 831, Bank of England.

    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. Casabianca, Elizabeth Jane & Catalano, Michele & Forni, Lorenzo & Giarda, Elena & Passeri, Simone, 2022. "A machine learning approach to rank the determinants of banking crises over time and across countries," Journal of International Money and Finance, Elsevier, vol. 129(C).
    2. Dieckelmann, Daniel, 2020. "Cross-border lending and the international transmission of banking crises," Discussion Papers 2020/13, Free University Berlin, School of Business & Economics.
    3. Bordo, M.D. & Meissner, C.M., 2016. "Fiscal and Financial Crises," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 355-412, Elsevier.
    4. Antunes, António & Bonfim, Diana & Monteiro, Nuno & Rodrigues, Paulo M.M., 2018. "Forecasting banking crises with dynamic panel probit models," International Journal of Forecasting, Elsevier, vol. 34(2), pages 249-275.
    5. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    6. Tran Huynh & Silke Uebelmesser, 2022. "Early warning models for systemic banking crises: can political indicators improve prediction?," Jena Economics Research Papers 2022-007, Friedrich-Schiller-University Jena.
    7. Tölö, Eero, 2020. "Predicting systemic financial crises with recurrent neural networks," Journal of Financial Stability, Elsevier, vol. 49(C).
    8. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
    9. du Plessis, Emile, 2022. "Multinomial modeling methods: Predicting four decades of international banking crises," Economic Systems, Elsevier, vol. 46(2).
    10. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    11. 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.
    12. Stijn Claessens & M. Ayhan Kose, 2013. "Financial Crises: Explanations, Types and Implications," CAMA Working Papers 2013-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    13. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "Does machine learning help us predict banking crises?," Journal of Financial Stability, Elsevier, vol. 45(C).
    14. 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.
    15. Ihejirika, Peters. O, 2020. "Does the Credit-to-GDP Gap Predict Financial Crisis in Nigeria?," International Journal of Social and Administrative Sciences, Asian Economic and Social Society, vol. 5(2), pages 109-126, June.
    16. Levieuge, Grégory & Lucotte, Yannick & Pradines-Jobet, Florian, 2021. "The cost of banking crises: Does the policy framework matter?," Journal of International Money and Finance, Elsevier, vol. 110(C).
    17. Fernandez-Gallardo, Alvaro, 2023. "Preventing financial disasters: Macroprudential policy and financial crises," European Economic Review, Elsevier, vol. 151(C).
    18. André K. Anundsen & Karsten Gerdrup & Frank Hansen & Kasper Kragh‐Sørensen, 2016. "Bubbles and Crises: The Role of House Prices and Credit," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1291-1311, November.
    19. Bitetto, Alessandro & Cerchiello, Paola & Mertzanis, Charilaos, 2023. "Measuring financial soundness around the world: A machine learning approach," International Review of Financial Analysis, Elsevier, vol. 85(C).
    20. Aikman, David & Haldane, Andrew & Hinterschweiger, Marc & Kapadia, Sujit, 2018. "Rethinking financial stability," Bank of England working papers 712, Bank of England.

    More about this item

    Keywords

    credit growth; machine learning; Shapley values; yield curve; financial crises; financial stability;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • F30 - International Economics - - International Finance - - - General
    • G01 - Financial Economics - - General - - - Financial Crises

    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:ecb:ecbwps:20212614. 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/emieude.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.