Early Warning with Calibrated and Sharper Probabilistic Forecasts
Article first published online: 26 MAR 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Journal of Forecasting
Volume 32, Issue 5, pages 452–468, August 2013
How to Cite
Machete, R. L. (2013), Early Warning with Calibrated and Sharper Probabilistic Forecasts. J. Forecast., 32: 452–468. doi: 10.1002/for.2242
- Issue published online: 23 JUL 2013
- Article first published online: 26 MAR 2012
- Manuscript Accepted: 29 DEC 2011
- Manuscript Revised: 7 OCT 2011
- Manuscript Received: 15 JUL 2010
- density forecasts;
- combining forecasts;
- scoring rule
Given a nonlinear model, a probabilistic forecast may be obtained by Monte Carlo simulations. At a given forecast horizon, Monte Carlo simulations yield sets of discrete forecasts, which can be converted to density forecasts. The resulting density forecasts will inevitably be downgraded by model misspecification. In order to enhance the quality of the density forecasts, one can mix them with the unconditional density. This paper examines the value of combining conditional density forecasts with the unconditional density. The findings have positive implications for issuing early warnings in different disciplines including economics and meteorology, but UK inflation forecasts are considered as an example. Copyright © 2012 John Wiley & Sons, Ltd.