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An Empirical Study of Pricing Strategies in an Online Market with High-Frequency Price Information

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An Empirical Study of Pricing Strategies in an Online Market with High-Frequency Price Information

Sara Fisher Ellison M.I.T.

Christopher M. Snyder Dartmouth College

June 2010

Abstract: We study competition among a score of firms participating in an online market for a commodity-type memory module. Firms were able to adjust prices continuously and prices determined how the firms were ranked and listed (lowest price listed first), with better ranks contributing to firms' sales. Using a year's worth of hourly data, we document the pricing dynamics, cycles, and other patterns in this market. We then characterize empirically the factors which drive price changes, noting clear evidence of firm heterogeneity in the choice of pricing strategy. Finally, we develop a framework for simulating counterfactual market settings, using the simulations to examine counterfactuals involving different mixes of firms according to pricing strategies.

JEL Codes: L11, C73, D21, L81

Contact Information: Ellison: Department of Economics, M.I.T., 50 Memorial Drive, Cambridge, MA 02142; tel. (617) 253-3821; fax. (617) 253-1330; email sellison@mit.edu. Snyder: Department of Economics, Dartmouth College, 301 Rockefeller Hall, Hanover, NH 03755; tel. (603) 646-0642, fax. (603) 646-2122, email chris.snyder@dartmouth.edu.

Acknowledgments: The authors are grateful to Hongkai Zhang for superb research assistance and to Glenn Ellison for a number of useful conversations.

1. Introduction
There is a vast and rich theoretical literature on the dynamics of repeated games. One conclusion of this literature is that many different market outcomes are possible. Full collusion, collusion on a focal price, cyclical markup patterns, and prices exactly tracking costs, are among the possibilities. This lack of a clear theoretical prediction suggests an important role for empirical

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