Rj. Brodie et A. Bonfrer, CONDITIONS WHEN MARKET SHARE MODELS ARE USEFUL FOR FORECASTING - FURTHER EMPIRICAL RESULTS, International journal of forecasting, 10(2), 1994, pp. 277-285
The increased availability of data ard access to computers has meant t
hat econometric methods are readily available to model and forecast ma
rket share. However, controversy exists over their usefulness. For exa
mple R. Brodie and C.A. de Kluyver's (International Journal of Forecas
ting, 1987, 3, 423-437) review of empirical studies revealed that the
predictive accuracy of causal market share models was not consistently
better than that of a naive model. In contrast, V. Kumar and T.B. Hea
th (International Journal of Forecasting, 1990, 6, 163-174) found that
causal models consistently outperformed the naive model when using ag
gregated weekly scanner data which allowed for more observations. This
paper reports the results of a replication and extension study which
confirms Kumar and Heath's findings. However, the increased accuracy f
rom using the causal model is diminished considerably when the more re
alistic situation of forecasting competitive action is included. The p
aper concludes by outlining a research agenda aimed at further clarify
ing the conditions when market share models are useful for forecasting
.