Korobilis, D. and Schröder, M. (2024) Monitoring multi-country macroeconomic risk: a quantile factor-augmented vector autoregressive (QFAVAR) approach. Journal of Econometrics, (doi: 10.1016/j.jeconom.2024.105730) (Early Online Publication)
![]() |
Text
324185.pdf - Published Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 4MB |
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.
Item Type: | Articles |
---|---|
Keywords: | quantile VAR, multivariate quantiles, MCMC, dynamic factor model. |
Status: | Early Online Publication |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Korompilis Magkas, Professor Dimitris |
Authors: | Korobilis, D., and Schröder, M. |
Subjects: | H Social Sciences > HA Statistics H Social Sciences > HB Economic Theory |
College/School: | College of Social Sciences > Adam Smith Business School > Economics |
Journal Name: | Journal of Econometrics |
Publisher: | Elsevier |
ISSN: | 0304-4076 |
ISSN (Online): | 1872-6895 |
Published Online: | 15 April 2024 |
Copyright Holders: | Copyright © 2024 The Author(s) |
First Published: | First published in Journal of Econometrics 2024 |
Publisher Policy: | Reproduced under a Creative Commons license |
Related URLs: |
University Staff: Request a correction | Enlighten Editors: Update this record