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Mind the Basel gap

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  • Jylhä, Petri
  • Lof, Matthijs

Abstract

The Basel credit gap, the difference between a country’s credit-to-GDP ratio and its estimated long-term trend, is used as a basis for setting countercyclical capital buffers under the Basel III regulatory framework. Using international data from the BIS, we show that the Basel credit gap, estimated by a one-sided HP filter, is nearly equivalent to a naive 16-quarter change in the credit-to-GDP ratio and performs equally well in terms of predicting banking crises. We demonstrate that the near-equivalence between deviations from trend and simple changes occurs when the one-sided HP filter is applied to a unit-root process. The goal of this paper is not to evaluate the performance of the Basel credit gap as an early-warning-indicator, but rather to demonstrate that its estimation method is unnecessarily complicated.

Suggested Citation

  • Jylhä, Petri & Lof, Matthijs, 2022. "Mind the Basel gap," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:intfin:v:79:y:2022:i:c:s1042443122000841
    DOI: 10.1016/j.intfin.2022.101605
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    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. Ebrahimi Kahou, Mahdi & Lehar, Alfred, 2017. "Macroprudential policy: A review," Journal of Financial Stability, Elsevier, vol. 29(C), pages 92-105.
    3. Luc Laeven & Fabian Valencia, 2020. "Systemic Banking Crises Database II," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 68(2), pages 307-361, June.
    4. 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.
    5. Candelon, Bertrand & Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2014. "Currency crisis early warning systems: Why they should be dynamic," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1016-1029.
    6. 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.
    7. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    8. 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.
    9. 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.).
    10. 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.
    11. Peter C. B. Phillips & Sainan Jin, 2021. "Business Cycles, Trend Elimination, And The Hp Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 469-520, May.
    12. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.
    13. Rafael Repullo & Jesús Saurina, 2011. "The Countercyclical Capital Buffer of Basel III: A Critical Assessment," Working Papers wp2011_1102, CEMFI, revised Jun 2011.
    14. Choi, In, 2001. "Unit root tests for panel data," Journal of International Money and Finance, Elsevier, vol. 20(2), pages 249-272, April.
    15. 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.
    16. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    17. Stijn Claessens, 2015. "An Overview of Macroprudential Policy Tools," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 397-422, December.
    18. 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.
    19. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    20. Mise, Emi & Kim, Tae-Hwan & Newbold, Paul, 2005. "On suboptimality of the Hodrick-Prescott filter at time series endpoints," Journal of Macroeconomics, Elsevier, vol. 27(1), pages 53-67, March.
    21. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    22. 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.
    23. 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.
    24. 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.
    25. Mathias Drehmann & Claudio Borio & Leonardo Gambacorta & Gabriel Jiminez & Carlos Trucharte, 2010. "Countercyclical capital buffers: exploring options," BIS Working Papers 317, Bank for International Settlements.
    26. Adriana Cornea-Madeira, 2017. "The Explicit Formula for the Hodrick-Prescott Filter in a Finite Sample," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 314-318, May.
    27. Robert M. de Jong & Neslihan Sakarya, 2016. "The Econometrics of the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 98(2), pages 310-317, May.
    28. Gabriele Galati & Richhild Moessner, 2018. "What Do We Know About the Effects of Macroprudential Policy?," Economica, London School of Economics and Political Science, vol. 85(340), pages 735-770, October.
    29. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
    30. Stefano Costa & Federico Sallusti & Claudio Vicarelli & Davide Zurlo, 2019. "Over the ROC methodology: Productivity, economic size and firms’ export thresholds," Review of International Economics, Wiley Blackwell, vol. 27(3), pages 955-980, August.
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    More about this item

    Keywords

    Credit gap; One-sided Hodrick–Prescott filter; Systemic risk;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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

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