Search with Learning

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

No 2012-03, Working Papers from Indiana University, Kelley School of Business, Department of Business Economics and Public Policy

Abstract: This paper provides a method to estimate search costs in an environment in which consumers are uncertain about the price distribution. Consumers learn about the price distribution by Bayesian updating their prior beliefs. The model provides bounds on the search costs that can rationalize observed search and purchasing behavior. Using individual-specific data on web browsing and purchasing behavior for electronics sold online we show how to use these bounds to estimate search costs. Estimated search costs are sizable and are found to relate to consumer characteristics in intuitive ways. The model outperforms a standard sequential search model in which the price distribution is known to consumers.

Keywords: consumer search; learning; electronic commerce (search for similar items in EconPapers)
JEL-codes: D43 D83 L13 (search for similar items in EconPapers)
Date: 2012-08
New Economics Papers: this item is included in nep-com and nep-mkt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:iuk:wpaper:2012-03

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