Bayesian Composite Qualitative Forecasting: Hog Prices Again

A new method for forming composite qualitative forecasts is presented. A set of qualitative forecasts is evaluated using auxiliary logit models to predict the probability of each forecast's correctness. Individual model forecasts are then combined on the basis of normalized values of these probabilities. This method is demonstrated with three sets of forecasts on the direction of change in hog prices (up or down). The application shows that without any information on the manner in which the individual forecasts are generated this method can form a composite forecast that is superior according to a variety of metrics for evaluating qualitative forecasts. Copyright 1998, Oxford University Press.