Correct or combine? Mechanically integrating judgmental forecasts with statistical methods
A laboratory experiment and two field studies were used to compare the accuracy of three methods that allow judgmental forecasts to be integrated with statistical methods. In all three studies the judgmental forecaster had exclusive access to contextual (or non time-series) information. The three methods compared were: (i) statistical correction of judgmental biases using Theil's optimal linear correction; (ii) combination of judgmental forecasts and statistical time-series forecasts using a simple average and (iii) correction of judgmental biases followed by combination. There was little evidence in any of the studies that it was worth going to the effort of combining judgmental forecasts with a statistical time-series forecast - simply correcting judgmental biases was usually sufficient to obtain any improvements in accuracy. The improvements obtained through correction in the laboratory experiment were achieved despite its effectiveness being weakened by variations in biases between periods.