An empirical comparison of cross-impact models for forecasting sales
This paper compares a set of four cross-impact models: (1) additive, (2) likelihood multiplier, (3) R-space, and (4) a model constructed by the author. This is done by examining a forecasting problem encountered by an industrial firm. The forecasting problem was to study the market trend in order to decide whether to expand the production capacity of a ceramics plant. In spite of their different theoretical premises, the models yielded similar results. However, only the R-space model produced results that differed from the others. The paper also suggests a method that should avoid some internal contradictions of the cross-impact models.