A0215
Title: Uncertainty as a predictor of economic activity
Authors: Martina Hengge - International Monetary Fund (United States) [presenting]
Abstract: Are empirical measures of uncertainty informative about risks to future economic activity? Quantile regression analysis and density predictions are used on United States data to show that the relationship between macroeconomic uncertainty and future GDP growth is nonlinear and asymmetric. The left tail of the distribution of future GDP growth is highly responsive to fluctuations in macroeconomic uncertainty, whereas the right tail is relatively stable. As such, macroeconomic uncertainty predicts downside risks to growth but is less informative about upside risks. When combined with an index of financial conditions, a previously proposed predictor of downside risks to growth, macroeconomic uncertainty carries a larger weight in the optimal predictive density. These results hold for a larger sample of countries and underline the importance of differentiating between measures of uncertainty when predicting risks to growth.
