Abstract

An Expectation-Maximization (EM) algorithm in a maximum likelihood framework is developed to estimate finite mixtures of multivariate regression and simultaneous equation models with multiple endogenous variables. A dataset with cross-sectional observations for a diverse sample of businesses illustrates the semiparametric approach.

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Citation

Jedidi, Kamel, Venkat Ramaswamy, Wayne DeSarbo, and Michel Wedel. "On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models." Structural Equation Modeling 3 (1996): 266-89.

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