Aggregating Subjective Forecasts: Some Empirical Results

Abstract

The impact on forecast accuracy of aggregating the subjective forecasts of up to 13 individuals was examined for five forecast weighting methods—equal weighting, two ex post methods that took advantage of prior information about the individuals' relative accuracy, and two ex ante methods based on objective and subjective assessments of relative accuracy. The individuals were executives, managers and sales personnel employed by Time. Inc., and the variable forecasted was the number of advertising pages sold annually by Time magazine over a 14-year period. The results show that both the average forecast error and the variance of the error decrease as additional individuals' forecasts are included in the aggregate. Only two to five individuals' forecasts must be included to achieve much of the total improvement available from combining all 13 forecasts. Three of the differential weighting methods produced more accurate forecasts than equal weighting, but the magnitude of the improvement was small. Implications for realistic forecasting situations are discussed, as are conditions under which the use of aggregates seems attractive.