arXiv 24 Oct 2022 · Econometrics · publishedThe Annals of Applied Statistics (2024) · 2 citations (OpenAlex)
arXiv:2210.13562 · PDF · DOI · OpenAlex · Extracted main text
The fixed-event forecasting setup is common in economic policy. It involves a sequence of forecasts of the same (`fixed') predictand, so that the difficulty of the forecasting problem decreases over time. Fixed-event point forecasts are typically published without a quantitative measure of uncertainty. To construct such a measure, we consider forecast postprocessing techniques tailored to the fixed-event case. We develop regression methods that impose constraints motivated by the problem at hand, and use these methods to construct prediction intervals for gross domestic product (GDP) growth in Germany and the US.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Patton, A. J. and A. Timmermann (2011) Predictability of output growth and inflation: A multi-horizon survey approach | 1.000 | 12 | 3 | 100% |
| 2 | Diebold, F. X. and R. S. Mariano (1995) Comparing predictive accuracy | 0.874 | 8 | 2 | 100% |
| 3 | Patton, A. J. and A. Timmermann (2012) Forecast rationality tests based on multi-horizon bounds | 0.843 | 3 | 3 | 100% |
| 4 | Henzi, A (2023) Consistent estimation of distribution functions under increasing concave and convex stochastic ordering | 0.811 | 4 | 2 | 100% |
| 5 | Lazarus, E., D. J. Lewis, J. H. Stock, and M. W. Watson (2018) HAR inference: Recommendations for practice | 0.737 | 3 | 2 | 100% |
| 6 | Bracher, J., D. Wolffram, J. Deuschel, K. Görgen, J. Ketterer, A. Ul… (2021) A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave | 0.644 | 2 | 2 | 100% |
| 7 | Gneiting, T. and A. E. Raftery (2005) Weather forecasting with ensemble methods | 0.644 | 2 | 2 | 100% |
| 8 | Gneiting, T. and A. E. Raftery (2007) Strictly proper scoring rules, prediction, and estimation | 0.644 | 2 | 2 | 100% |
| 9 | Gneiting, T. and R. Ranjan (2013) Combining predictive distributions | 0.644 | 2 | 2 | 100% |
| 10 | Lichtendahl Jr, K. C., Y. Grushka-Cockayne, and R. L. Winkler (2013) Is it better to average probabilities or quantiles? | 0.644 | 2 | 2 | 100% |
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