Chuliá, H., Garrón, I., & Uribe, J. M. (2024). Daily growth at risk: Financial or real drivers? The answer is not always the same. International Journal of Forecasting, 40(2), 762-776.
We propose daily Growth-at-Risk (GaR) for monitoring downside risks of the US economy, which use financial and real high frequency indicators. We show that the relative importance, in terms of forecasting power, of these indicators is time varying. Indeed, the optimal forecasting weights of our variables were clearly different during the Global Financial Crisis and the recent Covid-19 crisis, which reflects the dissimilar nature of the two crises. We introduce LASSO, and elastic-net-adaptive-sparse-group-LASSO into the family of mixed data sampling models used to estimate GaR and show that these methods outperform past candidates explored in the literature. Moreover, equity market volatility (VXO), credit spreads and the Aruoba-Diebold-Scotti business conditions index (ADS) are found to be relevant to forecast economic activity, especially during crisis episodes. Overall, our results show that daily information for both real and financial variables is key for producing accurate point and tail risk nowcasts of economic activity.
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