Backtesting Global Growth-at-Risk
69 Pages Posted: 10 Oct 2019 Last revised: 2 Nov 2020
Date Written: September 29, 2019
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.
Keywords: Growth-at-Risk, Backtesting, Quantile Regression, GARCH
JEL Classification: C22, C23, C52, C53, C58
Suggested Citation: Suggested Citation