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Quadratic Scoring Rules and Density Forecast Histograms
| Content Provider | Semantic Scholar |
|---|---|
| Author | Boero, Gianna Smith, Jeremy Wallis, Kenneth Frank |
| Copyright Year | 2009 |
| Abstract | This paper provides a practical evaluation of some leading density forecast scoring rules in the context of forecast surveys. We analyse the density forecasts of UK inflation obtained from the Bank of England’s Survey of External Forecasters, considering both the survey average forecasts published in the quarterly Inflation Report, and the individual survey responses recently made available by the Bank. The density forecasts are collected in histogram format, and the ranked probability score (RPS) is seen to have clear advantages. Missing observations are a feature of forecast surveys, and we propose an adjustment to the RPS, based on the Yates decomposition, to improve its comparative measurement of forecaster performance in the face of differential non-response. As an alternative combined density forecast, a trimmed mean scores better than the published survey average. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=ESAM09&paper_id=118 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
