CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS
Version of Record online: 24 SEP 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Journal of Applied Econometrics
Volume 29, Issue 5, pages 736–757, August 2014
How to Cite
2014), CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS, Journal of Applied Econometrics, 29, pages 736–757, doi: 10.1002/jae.2352and (
- Issue online: 29 JUL 2014
- Version of Record online: 24 SEP 2013
- Manuscript Revised: 1 JUL 2013
- Manuscript Received: 21 NOV 2011
Decision makers often observe point forecasts of the same variable computed, for instance, by commercial banks, IMF and the World Bank, but the econometric models used by such institutions are frequently unknown. This paper shows how to use the information available on point forecasts to compute optimal density forecasts. Our idea builds upon the combination of point forecasts under general loss functions and unknown forecast error distributions. We use real-time data to forecast the density of US inflation. The results indicate that the proposed method materially improves the real-time accuracy of density forecasts vis-à-vis those from the (unknown) individual econometric models. Copyright © 2013 John Wiley & Sons, Ltd.