Multi-Index Binary Response Analysis of Large Data Sets

16 Pages Posted: 12 Feb 2014

See all articles by Prasad A. Naik

Prasad A. Naik

University of California, Davis

Michel Wedel

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

Wagner A. Kamakura

Rice University

Date Written: February 7, 2014

Abstract

We propose a multi-index binary response model for analyzing large databases (i.e., with many regressors). We combine many regressors into factors (or indexes) and then estimate the link function via parametric or nonparametric methods. Neither the estimation of factors nor the determination of the number of factors requires ex ante knowledge of the link between the response and regressors. Furthermore, applying perturbation theory, we furnish a new asymptotic result to facilitate significance tests of factor loadings. We illustrate this approach with an empirical application in which we reduced dimensionality from 124 regressors to 4 factors.

Keywords: Customer relationship marketing, Discrete choice, Factor model, Inverse regression, Semiparametric estimation, Sliced average variance estimation

Suggested Citation

Naik, Prasad A. and Wedel, Michel and Kamakura, Wagner A., Multi-Index Binary Response Analysis of Large Data Sets (February 7, 2014). Journal of Business and Economic Statistics, Forthcoming; Robert H. Smith School Research Paper. Available at SSRN: https://ssrn.com/abstract=2392583

Prasad A. Naik (Contact Author)

University of California, Davis ( email )

One Shields Avenue
Davis, CA 95616
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

Wagner A. Kamakura

Rice University ( email )

6100 South Main Street
P.O. Box 1892
Houston, TX 77005-1892
United States
(713) 348-6307 (Phone)

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