Variable selection in macroeconomic stress test: a Bayesian quantile regression approach

Mai Dao () and Lam Nguyen ()
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Mai Dao: Wichita State University
Lam Nguyen: Economic Scenario Design Team, Citigroup

Empirical Economics, 2025, vol. 68, issue 3, No 5, 1113-1169

Abstract: 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.

Keywords: Bayesian inference; Quantile regression; Shrinkage priors; Macro stress testing; Systemic risk; Growth-at-risk (search for similar items in EconPapers)
JEL-codes: C1 C32 E47 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00181-024-02668-y

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