A consumer’s decision to engage in search depends on the beliefs the consumer has about an unknown product characteristic such as price. In this paper, we elicit the distribution of price beliefs and explicitly study their role in a consumer’s decision to search. We design an incentive-aligned online study where subjects search over the price of a homogeneous good, and provide prior price beliefs and updated beliefs after each search. Based on data collected from a nationally representative panel, we find substantial heterogeneity in prior price beliefs and that subjects update beliefs in response to search outcomes, which motivates our focus on sequential search. While departure from both rational expectations and Bayesian updating (assumptions routinely made in the literature) bias estimates of search costs, assuming rational expectations instead of accounting for heterogeneous prior beliefs has a more significant impact on the bias. Focusing on the role of prior beliefs, we explore the impact of mean and standard deviation of belief distribution at both – individual and aggregate level. While not accounting for individual-level uncertainty in price beliefs does not bias search cost estimates, it is critical to account for the heterogeneity in expected prices at the aggregate level to get consistent estimates of search costs. Finally, we use the search cost estimates to show how different assumptions about prior beliefs influence search elasticities and retail pricing.
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