Krueger, Fabian and Nolte, Ingmar (2016) Disagreement versus uncertainty : evidence from distribution forecasts. Journal of Banking and Finance, 72 (Suppl.). pp. 172-186. ISSN 0378-4266
Krueger_Nolte2015_full.pdf - Accepted Version
Available under License Creative Commons Attribution.
Download (2MB)
Abstract
We use a cross-section of economic survey forecasts to predict the distribution of US macro variables in real time. This generalizes the existing literature, which uses disagreement (i.e., the cross-sectional variance of survey forecasts) to predict uncertainty (i.e., the conditional variance of future macroeconomic quantities). Our results show that cross-sectional information can be helpful for distribution forecasting, but this information needs to be modeled in a statistically efficient way in order to avoid overfitting. A simple one-parameter model which exploits time variation in the cross-section of survey point forecasts is found to perform well in practice.