Journal of Banking & Finance Vol. 72 2016
Disagreement versus uncertainty: Evidence from distribution forecasts
open access
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.
- DOI
- 10.1016/j.jbankfin.2015.05.007
- Volume
- 72
- Pages
- S172-S186
- Language
- en
- Sources
- crossref openalex bibtex:phds-export.bib