Search with Learning in the Retail Gasoline Market
64 Pages Posted: 26 May 2021 Last revised: 24 Aug 2022
Date Written: August 20, 2022
This article estimates a model of optimal search where consumers learn the distribution of gasoline prices during their driving trips. Our model incorporates traffic information and leverages this ordered search environment to recover parameters of the search and learning process using only station-level price and market share data. We find that learning is a crucial component of search in this market. Consumers' prior beliefs regularly deviate from the true price distribution but are updated quickly following each new price observation. Counterfactuals reveal how these learning dynamics generate asymmetric search patterns commonly associated with asymmetric cost pass-through.
Keywords: consumer search, consumer learning, dynamic discrete choice model, asymmetric price adjustment, gasoline
JEL Classification: D83, L10, L13, L9
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