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Towards Better Banking Crisis Prediction: Could an Automatic Variable Selection Process Improve the Performance?

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  • Xianglong Liu

Abstract

This study proposes using the Least Absolute Shrinkage and Selection Operator (LASSO) method with cross‐validation to automate the variable selection process of the conventional multivariate logit early warning system (EWS), the purpose being to improve the prediction of systemic banking crises. Using a dataset covering 23 OECD countries with quarterly data from 1970Q1 to 2018Q3, model performance is evaluated in a recursive out‐of‐sample forecasting exercise, taking policy‐makers' preference of missed crises and false alarms into account. The results suggest that the automatic variable selection process can enhance the predictive performance of the EWS. It also highlights the importance of extracting information from variable interactions and lags that may not be easily identified and accessed by typical subjective variable pre‐selection. This simple approach is easy to interpret and is transparent, which are important aspects for effective policy communication. Five variables, namely credit growth, domestic and global credit gaps, real house price growth and the real effective exchange rate, are identified as the most important key indicators of systemic banking crises.

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  • 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.
  • Handle: RePEc:bla:ecorec:v:99:y:2023:i:325:p:288-312
    DOI: 10.1111/1475-4932.12721
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    1. Athanasios Orphanides & Simon van Norden, 2002. "The Unreliability of Output-Gap Estimates in Real Time," The Review of Economics and Statistics, MIT Press, vol. 84(4), pages 569-583, November.
    2. Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    3. Dawood, Mary & Horsewood, Nicholas & Strobel, Frank, 2017. "Predicting sovereign debt crises: An Early Warning System approach," Journal of Financial Stability, Elsevier, vol. 28(C), pages 16-28.
    4. Davis, J. Scott & Mack, Adrienne & Phoa, Wesley & Vandenabeele, Anne, 2016. "Credit booms, banking crises, and the current account," Journal of International Money and Finance, Elsevier, vol. 60(C), pages 360-377.
    5. 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.
    6. 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.
    7. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    8. 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.
    9. Sarlin, Peter, 2013. "On policymakers’ loss functions and the evaluation of early warning systems," Economics Letters, Elsevier, vol. 119(1), pages 1-7.
    10. 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.
    11. 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.
    12. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin, 2012. "How to Evaluate an Early-Warning System: Toward a Unified Statistical Framework for Assessing Financial Crises Forecasting Methods," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(1), pages 75-113, April.
    13. Hausman, Jerry & McFadden, Daniel, 1984. "Specification Tests for the Multinomial Logit Model," Econometrica, Econometric Society, vol. 52(5), pages 1219-1240, September.
    14. Manasse, Paolo & Roubini, Nouriel, 2009. ""Rules of thumb" for sovereign debt crises," Journal of International Economics, Elsevier, vol. 78(2), pages 192-205, July.
    15. Kaminsky, Graciela L. & Reinhart, Carmen M., 2000. "On crises, contagion, and confusion," Journal of International Economics, Elsevier, vol. 51(1), pages 145-168, June.
    16. Tim R. L. Fry & Mark N. Harris, 1998. "Testing for Independence of Irrelevant Alternatives," Sociological Methods & Research, , vol. 26(3), pages 401-423, February.
    17. Reinhart, Carmen & Rogoff, Kenneth, 2009. "This Time It’s Different: Eight Centuries of Financial Folly-Preface," MPRA Paper 17451, University Library of Munich, Germany.
    18. 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.
    19. Reinhart, Carmen & Rogoff, Kenneth, 2009. "This Time It’s Different: Eight Centuries of Financial Folly-Chapter 1," MPRA Paper 17452, University Library of Munich, Germany.
    20. 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.
    21. Òscar Jordà & Moritz Schularick & Alan M Taylor, 2011. "Financial Crises, Credit Booms, and External Imbalances: 140 Years of Lessons," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 59(2), pages 340-378, June.
    22. 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.).
    23. Caggiano, Giovanni & Calice, Pietro & Leonida, Leone & Kapetanios, George, 2016. "Comparing logit-based early warning systems: Does the duration of systemic banking crises matter?," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 104-116.
    24. Demirgüç-Kunt, Asli & Detragiache, Enrica, 2005. "Cross-Country Empirical Studies of Systemic Bank Distress: A Survey," National Institute Economic Review, National Institute of Economic and Social Research, vol. 192, pages 68-83, April.
    25. Fuertes, Ana-Maria & Kalotychou, Elena, 2006. "Early warning systems for sovereign debt crises: The role of heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1420-1441, November.
    26. van den Berg, Jeroen & Candelon, Bertrand & Urbain, Jean-Pierre, 2008. "A cautious note on the use of panel models to predict financial crises," Economics Letters, Elsevier, vol. 101(1), pages 80-83, October.
    27. Markus Holopainen & Peter Sarlin, 2017. "Toward robust early-warning models: a horse race, ensembles and model uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1933-1963, December.
    28. Davis, E. Philip & Karim, Dilruba, 2008. "Comparing early warning systems for banking crises," Journal of Financial Stability, Elsevier, vol. 4(2), pages 89-120, June.
    29. 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.
    30. Fry, Tim R. L. & Harris, Mark N., 1996. "A Monte Carlo study of tests for the independence of irrelevant alternatives property," Transportation Research Part B: Methodological, Elsevier, vol. 30(1), pages 19-30, February.
    31. 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.
    32. Caggiano, Giovanni & Calice, Pietro & Leonida, Leone, 2014. "Early warning systems and systemic banking crises in low income countries: A multinomial logit approach," Journal of Banking & Finance, Elsevier, vol. 47(C), pages 258-269.
    33. Detken, Carsten & Peltonen, Tuomas A. & Schudel, Willem & Behn, Markus, 2013. "Setting countercyclical capital buffers based on early warning models: would it work?," Working Paper Series 1604, European Central Bank.
    34. Claudio Borio & Mathias Drehmann, 2009. "Assessing the risk of banking crises - revisited," BIS Quarterly Review, Bank for International Settlements, March.
    35. Neunhoeffer, Marcel & Sternberg, Sebastian, 2019. "How Cross-Validation Can Go Wrong and What to Do About It," Political Analysis, Cambridge University Press, vol. 27(1), pages 101-106, January.
    36. Claudio Borio & Philip Lowe, 2002. "Assessing the risk of banking crises," BIS Quarterly Review, Bank for International Settlements, December.
    37. Tanaka, Katsuyuki & Kinkyo, Takuji & Hamori, Shigeyuki, 2016. "Random forests-based early warning system for bank failures," Economics Letters, Elsevier, vol. 148(C), pages 118-121.
    38. 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.
    39. Alessi, Lucia & Antunes, Antonio & Babecky, Jan & Baltussen, Simon & Behn, Markus & Bonfim, Diana & Bush, Oliver & Detken, Carsten & Frost, Jon & Guimaraes, Rodrigo & Havranek, Tomas & Joy, Mark & Kau, 2015. "Comparing different early warning systems: Results from a horse race competition among members of the Macro-prudential Research Network," MPRA Paper 62194, University Library of Munich, Germany.
    40. Asli Demirgüç-Kunt & Enrica Detragiache, 1998. "The Determinants of Banking Crises in Developing and Developed Countries," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 81-109, March.
    41. Philip Lowe & Claudio Borio, 2002. "Asset prices, financial and monetary stability: exploring the nexus," BIS Working Papers 114, Bank for International Settlements.
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