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dc.contributor.authorDe los Santos, Babur - Indiana University-
dc.contributor.authorHortacsu, Ali- University of Chicago and NBER-
dc.contributor.authorWildenbeest, Matthijs R. - Indiana University-
dc.description.abstractUsing a large data set on web browsing and purchasing behavior we test to what extent consumers are searching in accordance to various classical search models. We find that the benchmark model of sequential search with a known distributions of prices can be rejected based on the recall patterns we observe in the data. Moreover, we show that even if consumers are initially unaware of the price distribution and have to learn the price distribution, observed search behavior for given consumers over time is more consistent with non-sequential search than sequential search with learning. Our findings suggest non-sequential search provides a more accurate description of observed consumer search behavior. We then utilize the nonsequential search model to estimate the price elasticities and markups of online book retailers.en
dc.relation.ispartofseriesNet Institute Working Paper;09-23-
dc.subjectconsumer search, electronic commerce, consumer behavioren
dc.titleTesting Models of Consumer Search using Data on Web Browsing andPurchasing Behavioren
Appears in Collections:NET Institute Working Papers Series

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