Backtesting global Growth-at-Risk
2020; Elsevier BV; Volume: 118; Linguagem: Inglês
10.1016/j.jmoneco.2020.11.003
ISSN1873-1295
AutoresChristian T. Brownlees, André B.M. Souza,
Tópico(s)Global Financial Crisis and Policies
ResumoWe 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.
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