 Monitoring multi-country macroeconomic risk: A quantile factor-augmented vector autoregressive (QFAVAR) approachDimitris Korobilis and Maximilian Schröder Journal of Econometrics, 2025, vol. 249, issue PC Abstract: A multi-country quantile factor-augmented vector autoregression is proposed to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors enables a parsimonious summary of these two heterogeneities by accounting for dependencies in the cross-sectional dimension as well as across different quantiles of macroeconomic data. Using monthly euro area data, the strong empirical performance of the new model in gauging the impact of global shocks on country-level macroeconomic risks is demonstrated. The short-term tail forecasts of QFAVAR outperform those of FAVARs with symmetric Gaussian errors as well as univariate and multivariate specifications featuring stochastic volatility. Modeling individual quantiles enables scenario analysis of macroeconomic risks, a unique feature absent in FAVARs with stochastic volatility or flexible error distributions. Keywords: Quantile VAR; Multivariate quantiles; MCMC; Dynamic factor model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:249:y:2025:i:pc:s0304407624000769 DOI: 10.1016/j.jeconom.2024.105730 Access Statistics for this article Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson More articles in Journal of Econometrics from Elsevier |
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