Crowdsourcing of Economic Forecast – Combination of Forecasts Using Bayesian Model Averaging

Dongkoo Kim, Tae-hwan Rhee, Keunkwan Ryu and Changmock Shin

No 546, Ruhr Economic Papers from RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen

Abstract: 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.

Keywords: Combination of forecasts; Bayesian model averaging (search for similar items in EconPapers)
JEL-codes: E32 E37 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-for and nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:rwirep:546

DOI: 10.4419/86788624

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