On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models

Structural Equation Modeling, Volume 3, Issue 3, pp. 266-289

Posted: 8 Jun 2016

See all articles by Kamel Jedidi

Kamel Jedidi

Columbia Business School - Marketing

Venkatram Ramaswamy

University of Michigan, Stephen M. Ross School of Business

Wayne S. DeSarbo

Pennsylvania State University

Michel Wedel

University of Maryland - Robert H. Smith School of Business, Marketing Department; University of Groningen - Faculty of Economics and Business

Date Written: 1996

Abstract

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 components (or latent‐classes) of unknown proportions with multiple structural relations implied by the specified model for each latent‐class. We devise an Expectation‐Maximization algorithm in a maximum likelihood framework to simultaneously estimate the class proportions, the class‐specific structural parameters, and posterior probabilities of membership of each observation into each latent‐class. The appropriate number of classes can be chosen using various information‐theoretic heuristics. A data set entailing cross‐sectional observations for a diverse sample of businesses is used to illustrate the proposed approach.

Suggested Citation

Jedidi, Kamel and Ramaswamy, Venkatram and DeSarbo, Wayne S. and Wedel, Michel, On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models (1996). Structural Equation Modeling, Volume 3, Issue 3, pp. 266-289. Available at SSRN: https://ssrn.com/abstract=2791147

Kamel Jedidi

Columbia Business School - Marketing ( email )

New York, NY 10027
United States

Venkatram Ramaswamy

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109-1234
United States
734-763-5932 (Phone)
734-936-0279 (Fax)

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

Michel Wedel

University of Maryland - Robert H. Smith School of Business, Marketing Department ( email )

College Park, MD 20742
United States
301.405.2162 (Phone)
301.405.0146 (Fax)

HOME PAGE: http://www.rhsmith.umd.edu/marketing/faculty/wedel.html

University of Groningen - Faculty of Economics and Business ( email )

Postbus 72
9700 AB Groningen
Netherlands

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