Combining interval forecasts

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Anil Gaba, Ilia Tsetlin, Robert L. Winkler

2017 Decision Analysis Vol. 14 Issue 1 Article Cited by 49 Quartile

Abstract

When combining forecasts, a simple average of the forecasts performs well, often better than more sophisticated methods. In a prescriptive spirit, we consider some other parsimonious, easy-to-use heuristics for combining interval forecasts and compare their performance with the benchmark provided by the simple average, using simulations from a model we develop and data sets with forecasts made by professionals in their domain of expertise. We find that the empirical results closely match the results from our model, thus providing some validation for the theoretical model. The relative performance of the heuristics is influenced by the degree of overconfidence in and dependence among the individual forecasts, and different heuristics come out on top under different circumstances. The results provide some good, easy-to-use alternatives to the simple average with an indication of the conditions under which each might be preferable, enabling us to conclude with some prescriptive advice. © 2017 INFORMS.

Affiliations

INSEAD, Singapore, 138676, Singapore; Fuqua School of Business, Duke University, Durham, 27708, NC, United States

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