Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/194017 
Authors: 
Year of Publication: 
2017
Series/Report no.: 
DEP (Socioeconomics) Discussion Papers - Macroeconomics and Finance Series No. 2/2017
Publisher: 
Hamburg University, Department Socioeconomics, Hamburg
Abstract: 
This paper evaluates the predictive out-of-sample forecasting properties of six different economic uncertainty variables for both growth in aggregate M2 and growth in household-sector M2 in the U.S. using data between 1971m1 and 2014m12. The core contention is that economic uncertainty improves both forecast accuracy as well as direction-of-change forecasts of real money stock growth. We estimate linear ARDL models using the iterated rolling-window forecasting scheme combined with two different indicator selection procedures. Forecast accuracy is evaluated by RMSE and the Diebold-Mariano test. Direction-of-change forecasts are assessed by means of the Kuipers Score and the Pesaran-Timmermann test. The results indicate an increased relevance of certain economic uncertainty measures for forecasting growth in both real aggregate as well as real household-sector M2 since 2000.
Subjects: 
money demand
uncertainty
risk
multi-step forecasts
forecast comparison
JEL: 
C22
E41
E47
Document Type: 
Working Paper

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