Structural Modeling in Marketing: Review and Assessment

Pradeep Chintagunta, Tulin Erdem (), Peter Rossi () and Michel Wedel ()
Additional contact information
Michel Wedel: Robert H. Smith School of Business, 3303 Van Munching Hall, University of Maryland, College Park, Maryland 20742-1815

Marketing Science, 2006, vol. 25, issue 6, 604-616

Abstract: The recent marketing literature reflects a growing interest in structural models, stemming from (1) the desire to test a variety of behavioral theories with market data, and (2) recent developments that facilitate estimation of and inference for these models. Whether one should always go through the effort of developing such tightly parameterized models with the associated computational burden of estimating them and whether it pays off to make strict behavioral assumptions in terms of better decisions remain open questions. To shed some light on these issues, we provide examples of structural approaches to consumer choice and demand as well as examples where the goal is to study the nature of competition in the marketplace. From that review comes our discussion of issues in the development and application of structural models, including their estimation, testing, and validation, their applicability in the practice of marketing, and their usefulness for normative as well as descriptive purposes.

Keywords: structural models; heterogeneity; competition; endogeneity; dynamic demand models (search for similar items in EconPapers)
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (72)

Downloads: (external link)
http://dx.doi.org/10.1287/mksc.1050.0161 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormksc:v:25:y:2006:i:6:p:604-616

Access Statistics for this article

More articles in Marketing Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().