Search with Learning in the Retail Gasoline Market

64 Pages Posted: 26 May 2021 Last revised: 24 Aug 2022

See all articles by Xiaosong (Andy) Wu

Xiaosong (Andy) Wu

University of Melbourne

Matthew S. Lewis

Clemson University - John E. Walker Department of Economics

Frank Wolak

National Bureau of Economic Research (NBER)

Date Written: August 20, 2022

Abstract

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

Suggested Citation

Wu, Xiaosong and Lewis, Matthew S. and Wolak, Frank A., Search with Learning in the Retail Gasoline Market (August 20, 2022). Available at SSRN: https://ssrn.com/abstract=3853373 or http://dx.doi.org/10.2139/ssrn.3853373

Xiaosong Wu (Contact Author)

University of Melbourne

Level 4
111 Barry Street
Melbourne, 3010
Australia

Matthew S. Lewis

Clemson University - John E. Walker Department of Economics ( email )

Clemson, SC 29634
United States

Frank A. Wolak

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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