Combining multiple probability predictions using a simple logit model

Ville A. Satopää, Jonathan Baron, Dean P. Foster, Barbara A. Mellers, Philip E. Tetlock and Lyle H. Ungar

International Journal of Forecasting, 2014, vol. 30, issue 2, 344-356

Abstract: This paper begins by presenting a simple model of the way in which experts estimate probabilities. The model is then used to construct a likelihood-based aggregation formula for combining multiple probability forecasts. The resulting aggregator has a simple analytical form that depends on a single, easily-interpretable parameter. This makes it computationally simple, attractive for further development, and robust against overfitting. Based on a large-scale dataset in which over 1300 experts tried to predict 69 geopolitical events, our aggregator is found to be superior to several widely-used aggregation algorithms.

Keywords: Combining forecasts; Error correction models; Expert forecasts; Logit-normal models; Multinomial events; Probability forecasting (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:30:y:2014:i:2:p:344-356

DOI: 10.1016/j.ijforecast.2013.09.009

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