Combining forecasts: What information do judges need to outperform the simple average?

Previous work has shown that combinations of separate forecasts produced by judgment are inferior to those produced by simple averaging. However, in t hat research judges were not informed of outcomes after producing each comb ined forecast. Our first experiment shows that when they are given this inf ormation, they learn to weight the separate forecasts appropriately. Howeve r, their judgments, though improved, are still not significantly better tha n the simple average because they contain a random error component. Bootstr apping can be used to remove this inconsistency and produce results that ou tperform the average. In our second and third experiments, we provided judg es with information about errors made by the individual forecasters. Result s show that providing information about their mean absolute percentage erro rs updated each period enables judges to combine their forecasts in a way t hat outperforms the simple average. (C) 1999 Elsevier Science B.V. All righ ts reserved.