Aggregating Subjective Forecasts: Some Empirical Results
研究了如何汇总最多13人的主观预测以提高准确性，比较了等权、事后加权和事前加权等五种方法，发现仅需2-5人即可获得大部分改进，但加权方法提升幅度有限。
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.