Backtesting global Growth-at-Risk

• 成果类型: Article
• 署名作者: Brownlees, Christian; Souza, Andre B. M.
• 署名单位: Pompeu Fabra University; Barcelona School of Economics
• 刊物名称: JOURNAL OF MONETARY ECONOMICS
• ISSN/ISSBN: 0304-3932
• DOI: 10.1016/j.jmoneco.2020.11.003
• 发表日期: 2021
• 页码: 312-330
• 关键词: Growth-at-Risk; Backtesting; quantile regression; GARCH

摘要

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. (c) 2020 Elsevier B.V. All rights reserved.