The Probit Choice Model under Sequential Search with an Application to Online Retailing

43 Pages Posted: 26 Oct 2013 Last revised: 5 May 2016

Jun B. Kim

HKUST Business School

Paulo Albuquerque

INSEAD

Bart J. Bronnenberg

Tilburg University, CentER

Date Written: May 4, 2016

Abstract

We develop a probit choice model under optimal sequential search and apply it to the study of aggregate demand of consumer durable goods. In our joint model of search and choice, we derive a semi-closed form expression for the probability of choice that obeys the full set of restrictions imposed by optimal sequential search. Our joint model leads to a partial simulation-based estimation that avoids high-dimensional integrations in the evaluation of choice probabilities and that is particularly attractive when search sets are large. We illustrate the advantages of our approach using aggregate search and choice data from the camcorder product category at Amazon.com. We show that the joint use of search and choice data provides better performance in terms of inferences and predictions than using search data alone and leads to realistic estimates of consumer substitution patterns.

Keywords: Optimal sequential search, discrete choice, consumer heterogeneity, aggregate demand models, information economics, market structure

JEL Classification: D83, M31

Suggested Citation

Kim, Jun B. and Albuquerque, Paulo and Bronnenberg, Bart J., The Probit Choice Model under Sequential Search with an Application to Online Retailing (May 4, 2016). Simon School Working Paper No. FR 13-29. Available at SSRN: https://ssrn.com/abstract=2345265 or http://dx.doi.org/10.2139/ssrn.2345265

Jun B. Kim (Contact Author)

HKUST Business School ( email )

HKUST
Clearwater Bay
Kowloon
Hong Kong

Paulo Albuquerque

INSEAD ( email )

Boulevard de Constance
Fontainebleau, 77305
France

HOME PAGE: http://www.insead.edu/facultyresearch/faculty/profiles/palbuquerque/

Bart J. Bronnenberg

Tilburg University, CentER ( email )

Warandelaan 2
Tilburg, 5037 AB
Netherlands
+31 13 466 8939 (Phone)
+31 13 466 8354 (Fax)

Paper statistics

Downloads
213
Rank
118,297
Abstract Views
830