Forecaster diversity and the benefits of combining forecasts

Article Abstract:

Integrating several randomly selected unbiased forecasts will generally result in improved forecast accuracy. However, in practice, there is always the chance that the user will select a combination of forecasts that is less effective than a single randomly chosen forecast. A study is conducted to address this issue. In particular, it seeks to quantify the benefits from combining forecasts and to determine whether additional benefits can be generated if a nonrandom method for choosing individual forecasts is employed. The data used for the study consist of published forecasts by a group of 22 American economic forecasters, as well as the results of a survey of their forecasting strategies. A tool for quantifying the benefits of combining forecasts is developed.

Forecasting

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A comparison of two elicitation methods for a prior distribution for a binomial parameter

Article Abstract:

Two methods of elicitation of the hyperparameters of a binomial sampling model's conjugate beta distribution are compared. A new method using imaginary results devices is proposed which is less sensitive to elicitation errors than Chanoler's and Duncan's posterior mode method. A simulation is conducted using an explicit model for elicitation errors.

Management science, Functions, Beta, Beta functions

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