Backtesting Global Growth-at-Risk

58 Pages Posted: 10 Oct 2019 Last revised: 26 Nov 2019

See all articles by Christian T. Brownlees

Christian T. Brownlees

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences; Barcelona Graduate School of Economics (Barcelona GSE)

Andre B.M. Souza

Universitat Pompeu Fabra - Department of Economics and Business; Barcelona Graduate School of Economics (Barcelona GSE)

Date Written: September 29, 2019

Abstract

We conduct an out-of-sample backtesting exercise of multivariate Growth-at-Risk (GaR) predictions for 24 OECD countries. We consider forecasting methods based on quantile regression (QR) and GARCH models. We find evidence of predictability up to one year ahead, and the forecasts based on GARCH models dominate those based on QR. Our empirical evidence supports the view that the time-varying dynamics of the lower quantiles of GDP growth cannot be distinguished from those implied by time-varying volatility.

Keywords: Growth-at-Risk, Backtesting, Quantile Regression, GARCH

JEL Classification: C22, C23, C52, C53, C58

Suggested Citation

Brownlees, Christian T. and Souza, Andre B.M., Backtesting Global Growth-at-Risk (September 29, 2019). Available at SSRN: https://ssrn.com/abstract=3461214 or http://dx.doi.org/10.2139/ssrn.3461214

Christian T. Brownlees

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences ( email )

Ramon Trias Fargas 25-27
Barcelona, 08005
Spain

HOME PAGE: http://84.89.132.1/~cbrownlees/

Barcelona Graduate School of Economics (Barcelona GSE) ( email )

Ramon Trias Fargas 25-27
Barcelona, Catalonia 08014
Spain

Andre B.M. Souza (Contact Author)

Universitat Pompeu Fabra - Department of Economics and Business ( email )

Barcelona
Spain

HOME PAGE: http://andrebmsouza.com

Barcelona Graduate School of Economics (Barcelona GSE) ( email )

Ramon Trias Fargas, 25-27
Barcelona, Barcelona 08005
Spain

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