Focusing on the interdependence of product categories we analyze multicategory buying decisions of households by a finite mixture of multivariate Tobit-2 models with two response variables: purchase incidence and expenditure. Mixture components can be interpreted as household segments. Correlations for purchases of different categories turn out to be much more important than correlations among expenditures as well as correlations among purchases and expenditures of different categories. About 18% of all pairwise purchase correlations are significant. We compare the best-performing large-scale model with 28 categories to four small-scale models each with seven categories. In our empirical study the large-scale model clearly attains a better forecasting performance. The small-scale models provide several biased correlations and miss about 50% of the significant correlations which the large scale model detects. Copyright © 2013 John Wiley & Sons, Ltd.