Early Warning with Calibrated and Sharper Probabilistic Forecasts
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 mis-specification. 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.
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- Lawrence, Michael & Goodwin, Paul & O'Connor, Marcus & Onkal, Dilek, 2006. "Judgmental forecasting: A review of progress over the last 25 years," International Journal of Forecasting, Elsevier, vol. 22(3), pages 493-518.
- David Hendry & Michael P. Clements, 2001.
"Pooling of Forecasts,"
2002-W9, Economics Group, Nuffield College, University of Oxford.
- Clements, Michael P. & Smith, Jeremy, 2001. "Evaluating forecasts from SETAR models of exchange rates," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 133-148, February.
- Tilmann Gneiting, 2008. "Editorial: Probabilistic forecasting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 319-321.
- Tilmann Gneiting & Fadoua Balabdaoui & Adrian E. Raftery, 2007. "Probabilistic forecasts, calibration and sharpness," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 243-268.
- Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
- Hall, Stephen G. & Mitchell, James, 2007. "Combining density forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 1-13.
- Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
- Greis, Noel P. & Gilstein, C. Zachary, 1991. "Empirical Bayes methods for telecommunications forecasting," International Journal of Forecasting, Elsevier, vol. 7(2), pages 183-197, August.
- Kapetanios, George & Labhard, Vincent & Price, Simon, 2008.
"Forecast combination and the Bank of England's suite of statistical forecasting models,"
Elsevier, vol. 25(4), pages 772-792, July.
- George Kapetanios & Vincent Labhard & Simon Price, 2007. "Forecast combination and the Bank of England’s suite of statistical forecasting models," Bank of England working papers 323, Bank of England.
- Luca Benati, 2004.
"Evolving post-World War II UK economic performance,"
Bank of England working papers
232, Bank of England.
- Luca Benati, 2003. "Evolving Post-World War II U.K. Economic Performance," Computing in Economics and Finance 2003 171, Society for Computational Economics.
- Kenneth F. Wallis, 2005. "Combining Density and Interval Forecasts: A Modest Proposal," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 983-994, December.
- Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
- Soumik Pal, 2009. "A note on a conjectured sharpness principle for probabilistic forecasting with calibration," Biometrika, Biometrika Trust, vol. 96(4), pages 1019-1023.
- Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
- Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
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