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Crowdsourcing of economic forecast : combination of forecasts using Bayesian model averaging

Dongkoo Kim; Tae-hwan Rhee; Keunkwan Ryu; Changmock Shin
Economic forecasts are quite essential in our daily lives, which is why many research institutions periodically make and publish forecasts of main economic indicators. We ask (1) whether we can consistently have a better prediction when we combine multiple forecasts of the same variable and (2) if we can, what will be the optimal method of combination. We linearly combine multiple linear combinations of existing forecasts to form a new forecast (“combination of combinations”), and the weights are given by Bayesian model averaging. In the case of forecasts on Germany’s real GDP growth rate, this new forecast dominates any single forecast in terms of root-mean-square prediction errors.
Year of publication:
2015
Authors: Kim, Dongkoo ; Rhee, Tae-hwan ; Ryu, Keunkwan ; Shin, Changmock
Publisher: Essen : RWI
Subject: Combination of forecasts | Bayesian model averaging | Bayes-Statistik | Bayesian inference | Prognoseverfahren | Forecasting model | Wirtschaftsprognose | Economic forecast | Theorie | Theory | Frühindikator | Leading indicator
Extent:
Online-Ressource (28 S.)
graph. Darst.
Series:
Ruhr economic papers. - Essen : RWI, ISSN 1864-4872, ZDB-ID 2278825-6. - Vol. 546
Type of publication: Book / Working Paper
Type of publication (narrower categories): Arbeitspapier ; Working Paper ; Graue Literatur ; Non-commercial literature
Language: English
Notes:
Systemvoraussetzungen: Acrobat Reader
ISBN: 978-3-86788-624-6
Other identifiers:
10.4419/86788624 [DOI]
hdl:10419/108738 [Handle]
Classification: E32 - Business Fluctuations; Cycles ; E37 - Forecasting and Simulation
Source:
ECONIS - Online Catalogue of the ZBW
Persistent link: https://ebvufind01.dmz1.zbw.eu/10010496143
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