Testing Models of Consumer Search Using Data on Web Browsing Behavior

Babur De los Santos (), Ali Hortacsu and Matthijs Wildenbeest

No 09-23, Working Papers from NET Institute

Abstract: Using a large data set on consumers' web browsing and purchasing behavior we contrast 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 non-sequential search model to estimate the price elasticities and markups of online book retailers.

Keywords: search costs; sequential search; fixed-sample search; non-sequential search; online browsing; online book industry; consumer search (search for similar items in EconPapers)
JEL-codes: D80 D83 L10 L11 L80 L81 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2009-08, Revised 2009-08
New Economics Papers: this item is included in nep-ict and nep-mkt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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