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Combining Forecasts: Multiple Regression versus a Bayesian Approach

✍ Scribed by Daniel T. Walz; Diane B. Walz

Book ID
109167170
Publisher
Decision Sciences Institute, Georgia State University
Year
1989
Tongue
English
Weight
728 KB
Volume
20
Category
Article
ISSN
0011-7315

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πŸ“œ SIMILAR VOLUMES

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## Abstract A general Bayesian approach to combining __n__ expert forecasts is developed. Under some moderate assumptions on the distributions of the expert errors, it leads to a consistent, monotonic, quasi‐linear average formula. This generalizes Bordley's results.

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The standard approach to combining n expert forecasts involves taking a weighted average. Granger and Ramanathan proposed introducing an intercept term and unnormalized weights. This paper deduces their proposal from Bayesian principles. We find that their formula is equivalent to taking a weighted