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Variable selection in macroeconomic stress test: a Bayesian quantile regression approach
Dao, Mai Nguyen, Lam
Dao, Mai
Nguyen, Lam
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2024-10-29
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Article
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Keywords
Bayesian inference,C1,C32,E47,Growth-at-risk,Macro stress testing,Quantile regression,Shrinkage priors,Systemic risk
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Citation
Dao, M., Nguyen, L. Variable selection in macroeconomic stress test: a Bayesian quantile regression approach. Empir Econ (2024). https://doi.org/10.1007/s00181-024-02668-y
Abstract
The key assumption in stress test scenarios is that selected risk factors are useful in predicting banks’ tail risks under severe economic conditions. We argue that high-dimensional Bayesian quantile regression models with shrinkage priors are ideal for identifying those factors. We illustrate our methods by identifying key drivers for banks with different asset sizes from a high-dimensional database. We found that leverage indicators, asset prices, and labor market measures are the best predictors of banks’ performance. The usefulness of our methods is further demonstrated by a forecast comparison between the selected variables and those used in the regulatory stress tests. © The Author(s) 2024.
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Springer Science and Business Media Deutschland GmbH
Journal
Empirical Economics
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03777332