GEMCAT: A GEneral Multivariate Methodology for Estimating Catastrophe Models

Behavioral Science, 32:2 p.121

Posted: 27 May 2016

See all articles by Terence A. Oliva

Terence A. Oliva

Independent

Wayne S. DeSarbo

Pennsylvania State University

Diana L. Day

University of Pennsylvania - The Wharton School

Kamel Jedidi

Columbia Business School - Marketing

Date Written: April 1987

Abstract

This paper presents a methodology for empirically estimating any specified univariate or multivariate catastrophe theory model. As such, the paper is appropriate for those interested in modeling virtually all levels of living systems and subsystems which can be described by catastrophe theory models, as well as those interested in testing cross-level hypotheses about such systems and subsystems. The lack of such flexible estimation procedures has limited the potential application of catastrophe modeling in the social and behavioral sciences. More specifically, a methodology called GEMCAT is presented, using the cusp model for expositional convenience, which allows the traditional canonical catastrophe model variables to be described as latent constructs of univariate or multivariate observable variable sets. A Monte Carlo analysis is presented demonstrating the performance of the methodology under various conditions. Furthermore, it is shown how this method is superior to the common practice of generating univariate composites (e.g., by summing, averaging, etc.) which has been traditionally used because of either computational convenience or the lack of such a methodology.

Keywords: all levels of systems, all subsystems, catastrophe theory, controlled random search, nonlinear estimation, cusp catastrophe model, cross-level hypotheses

Suggested Citation

Oliva, Terence A. and DeSarbo, Wayne S. and Day, Diana L. and Jedidi, Kamel, GEMCAT: A GEneral Multivariate Methodology for Estimating Catastrophe Models (April 1987). Behavioral Science, 32:2 p.121. Available at SSRN: https://ssrn.com/abstract=2784466

Terence A. Oliva

Independent

No Address Available

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

Diana L. Day

University of Pennsylvania - The Wharton School ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

Kamel Jedidi

Columbia Business School - Marketing ( email )

New York, NY 10027
United States

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