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Scoring rules and survey density forecasts

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Boero, Gianna, Smith, Jeremy and Wallis, Kenneth Frank (2011) Scoring rules and survey density forecasts. International Journal of Forecasting, Volume 27 (Number 2). pp. 379-393. doi:10.1016/j.ijforecast.2010.04.003 ISSN 0169-2070.

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Official URL: http://dx.doi.org/10.1016/j.ijforecast.2010.04.003

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Abstract

This article 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 Bank's quarterly Inflation Report, and the individual survey responses recently made available to researchers by the Bank. The density forecasts are collected in histogram format, and the ranked probability score (RPS) is shown to have clear advantages over other scoring rules. Missing observations are a feature of forecast surveys, and we introduce 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. The new measure, denoted RPS*, is recommended to analysts of forecast surveys. (C) 2010 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Item Type: Journal Article
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences > Economics
Library of Congress Subject Headings (LCSH): Economic forecasting -- Econometric models, Inflation (Finance) -- Great Britain -- Forecasting -- Econometric models, Probabilities, Missing observations (Statistics)
Journal or Publication Title: International Journal of Forecasting
Publisher: Elsevier
ISSN: 0169-2070
Official Date: April 2011
Dates:
DateEvent
April 2011Published
Volume: Volume 27
Number: Number 2
Page Range: pp. 379-393
DOI: 10.1016/j.ijforecast.2010.04.003
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access

Data sourced from Thomson Reuters' Web of Knowledge

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