We propose a maximum likelihood framework for estimating finite mixtures of multivariate regression and simultaneous equation models with multiple endogenous variables. The proposed “semi‐parametric” approach posits that the sample of endogenous observations arises from a finite mixture of...

We propose Multivariate Tobit models with a factor structure on the covariance matrix. Such models are particularly useful in the exploratory analysis of multivariate censored data and the identification of latent variables from behavioral data. The factor structure provides a parsimonious...

Paul Green, writing with Carmone and Wachpress (1976), was among the first scholars to introduce latent variable models to marketing by utilizing the CANDECOMP procedure (Carroll 1980) on contingency tables. A year later, Green, Carmone, and Wachpress (1977) introduced logit and log-linear...