Macroeconomic Uncertainty and Forecasting Macroeconomic Aggregates

Magnus Reif

No 265, ifo Working Paper Series from ifo Institute - Leibniz Institute for Economic Research at the University of Munich

Abstract: Can information on macroeconomic uncertainty improve the forecast accuracy for key macroeconomic time series for the US? Since previous studies have demonstrated that the link between the real economy and uncertainty is subject to nonlinearities, I assess the predictive power of macroeconomic uncertainty in both linear and nonlinear Bayesian VARs. For the latter I use a threshold VAR that allows for regimedependent dynamics conditional on the level of the uncertainty measure. I find that the predictive power of macroeconomic uncertainty in the linear VAR is negligible. In contrast, using information on macroeconomic uncertainty in a threshold VAR can significantly improve the accuracy of short-term point and density forecasts, especially in the presence of high uncertainty.

JEL-codes: C11 C53 C55 E32 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-for and nep-mac
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Macroeconomic uncertainty and forecasting macroeconomic aggregates (2021)
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