Monitoring multicountry macroeconomic risk

Dimitris Korobilis and Maximilian Schröder

No 2023/9, Working Paper from Norges Bank

Abstract: We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a parsimonious way. We develop two algorithms for posterior inference that feature varying level of trade-off between estimation precision and computational speed. Using monthly data for the euro area, we establish the good empirical properties of the QFAVAR as a tool for assessing the e ects of global shocks on country-level macroeconomic risks. In particular, QFAVAR short-run tail forecasts are more accurate compared to a FAVAR with symmetric Gaussian errors, as well as univariate quantile autoregressions that ignore comovements among quantiles of macroeconomic variables. We also illustrate how quantile impulse response functions and quantile connectedness measures, resulting from the new model, can be used to implemennt joint risk scenario analysis.

Keywords: quantile VAR; MCMC; variational Bayes; dynamic factor model. (search for similar items in EconPapers)
JEL-codes: C11 C32 E31 E32 E37 E66 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2023-06-15
New Economics Papers: this item is included in nep-rmg
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Citations: View citations in EconPapers (1)

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https://hdl.handle.net/11250/3073380

Related works:
Working Paper: Monitoring multicountry macroeconomic risk (2023)
Working Paper: Monitoring multicountry macroeconomic risk (2023)
Working Paper: Monitoring multicountry macroeconomic risk (2023)
Working Paper: Monitoring multicountry macroeconomic risk (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:bno:worpap:2023_9

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