Journal Articles

Semi-nonparametric Estimation of Consumer Search Costs

2013, Journal of Applied Econometrics

José Luis Moraga-González, Zsolt Sándor, Matthijs R. Wildenbeest


This paper studies the estimation of the distribution of non-sequential search costs. We show that the search cost distribution is identified by combining data from multiple markets with common search technology but varying consumer valuations, firms' costs, and numbers of competitors. To exploit such data optimally, we provide a new method based on semi-nonparametric (SNP) estimation. We apply our method to a dataset of online prices for memory chips and find that the search cost density is essentially bimodal such that a large fraction of consumers searches very little, whereas a smaller fraction searches a relatively large number of stores.


Moraga-González, José Luis, Zsolt Sándor, and Matthijs R. Wildenbeest (2013), "Semi-nonparametric Estimation of Consumer Search Costs," Journal of Applied Econometrics,Vol. 28, No. 7, pp. 1205-1223.


consumer search, oligopoly, search costs, semi-nonparametric estimation

Kelley School of Business

Faculty & Research