TY - JOUR
T1 - Backtesting global growth-at-risk
AU - B.M. Souza, A.
AU - Brownlees, Christian
PY - 2021/3/1
Y1 - 2021/3/1
N2 - We conduct an out-of-sample backtesting exercise of Growth-at-Risk (GaR) predictions for 24 OECD countries. We consider forecasts constructed from quantile regression and GARCH models. The quantile regression forecasts are based on a set of recently proposed measures of downside risks to GDP, including the national financial conditions index. The backtesting results show that quantile regression and GARCH forecasts have a similar performance. If anything, our evidence suggests that standard volatility models such as the GARCH(1,1) are more accurate.
AB - We conduct an out-of-sample backtesting exercise of Growth-at-Risk (GaR) predictions for 24 OECD countries. We consider forecasts constructed from quantile regression and GARCH models. The quantile regression forecasts are based on a set of recently proposed measures of downside risks to GDP, including the national financial conditions index. The backtesting results show that quantile regression and GARCH forecasts have a similar performance. If anything, our evidence suggests that standard volatility models such as the GARCH(1,1) are more accurate.
U2 - 10.1016/j.jmoneco.2020.11.003
DO - 10.1016/j.jmoneco.2020.11.003
M3 - Article
SN - 0304-3932
SP - 312
EP - 330
JO - Journal of Monetary Economics
JF - Journal of Monetary Economics
ER -