We thank Matt Lewis, Howard Marvel, James Peck, and the seminar participants at the Third Summer Workshop on Industrial Organization and Management Strategy (2006, Beijing), the Midwest Economic Theory Meetings (Fall 2006, Purdue), and the 5th Annual International Industrial Organization Conference (May 2007, Savannah) for valuable comments and suggestions. We also benefited from insightful comments and suggestions from two anonymous referees. All remaining errors are our own.
Search with learning: understanding asymmetric price adjustments
Article first published online: 28 JUN 2008
© 2008, RAND
The RAND Journal of Economics
Volume 39, Issue 2, pages 547–564, Summer 2008
How to Cite
Yang, H. and Ye, L. (2008), Search with learning: understanding asymmetric price adjustments. The RAND Journal of Economics, 39: 547–564. doi: 10.1111/j.0741-6261.2008.00027.x
- Issue published online: 16 SEP 2008
- Article first published online: 28 JUN 2008
In many retail markets, prices rise faster than they fall. We develop a model of search with learning to explain this phenomenon of asymmetric price adjustments. By extending our static game analysis to the dynamic setting, we demonstrate that asymmetric price adjustments arise naturally. When a positive cost shock occurs, all the searchers immediately learn the true state; the search intensity, and hence the prices, fully adjust in the next period. When a negative cost shock occurs, it takes longer for nonsearchers to learn the true state, and the search intensity increases gradually, leading to slow falling of prices.