When modeling demand for differentiated products, it is vital to adequately capture consumer taste heterogeneity, But there is no clearly preferred approach. Here, we compare the performance of six alternative models. Currently, the most popular are mixed logit (MIXL), particularly the version with normal mixing (N-MIXL), and latent class (LC), which assumes discrete consumer types. Recently, several alternative models have been developed. The 'generalized multinomial logit' (G-MNL) extends N-MIXL by allowing for heterogeneity in the logit scale coefficient. Scale heterogeneity logit (S-MNL) is a special case of G-MNL with scale heterogeneity only. The 'mixed-mixed' logit (MM-MNL) assumes a discrete mixture-of-normals heterogeneity distribution. Finally, one can modify N-MIXL by imposing theoretical sign constraints on vertical attributes. We call this 'T-MIXL'. We find that none of these models dominates the others, but G-MNL, MM-MNL and T-MIXL typically outperform the popular N-MIXL and LC models.
