Mind the Basel gap

Funding Information: We thank three anonymous referees, Katja Ahoniemi, Adriana Cornea-Madeira, Mikael Juselius, Ilkka Kiema, and seminar and conference participants at Aalto University, Aarhus University, De Nederlandsche Bank, the American Economic Association 2020, the Finnish Economic Association 2020, the International Conference on Computational and Financial Econometrics 2021, and the RiskLab/BoF/ESRB Conference on Systemic Risk Analytics 2019 for useful comments, and Henri Peltonen for excellent research assistance. This work was supported by the Finnish foundation for the advancement of securities markets under grant 202000039. Funding Information: We thank three anonymous referees, Katja Ahoniemi, Adriana Cornea-Madeira, Mikael Juselius, Ilkka Kiema, and seminar and conference participants at Aalto University, Aarhus University, De Nederlandsche Bank, the American Economic Association 2020, the Finnish Economic Association 2020, the International Conference on Computational and Financial Econometrics 2021, and the RiskLab/BoF/ESRB Conference on Systemic Risk Analytics 2019 for useful comments, and Henri Peltonen for excellent research assistance. This work was supported by the Finnish foundation for the advancement of securities markets under grant 202000039 . Publisher Copyright: © 2022 The Author(s)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.Peer reviewe