Backtesting global Growth-at-Risk

Christian Brownlees and André B.M. Souza

Journal of Monetary Economics, 2021, vol. 118, issue C, 312-330

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: C22 C23 C52 C53 C58 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (39)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:moneco:v:118:y:2021:i:c:p:312-330

DOI: 10.1016/j.jmoneco.2020.11.003

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