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Backtesting Global Growth-at-Risk

2019; RELX Group (Netherlands); Linguagem: Inglês

10.2139/ssrn.3461214

1556-5068

Christian T. Brownlees, André B.M. Souza,

Economic Policies and Impacts

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.