In response to a price change by a single seller, it is common for the density of sellers in the market to influence both the quantity response of consumers and the price response of other sellers. Using field experiment data collected around a series of exogenously imposed price changes we find that an individual retailer with a larger number of competitors faces a more-responsive demand. This finding is fundamental to a predicted inverse relationship between market prices and the number of competitors. We also examine the reaction of rival stations to exogenous price changes, and find that the magnitude of a competitor's response is inversely related to the density of stations in the market. © 2007 Elsevier B.V. All rights reserved. In changing a price, a seller must confront two key questions: What will be the reaction of consumers to a price change and what will be the reaction of competitors? A common feature of many models that consider price-setting is that answers to both questions depend on the number of competitors in the market. This paper draws on a field experiment that was conducted in three urban areas of California to see whether the number of competitors does indeed determine the extent of the reaction by a seller's potential customers as well as the extent of the reaction by competitors. The experiment set for short time intervals retail prices at 54 company-operated gasoline stations of a major retailer. In particular, prices at two alternating subsets of stations were changed and then fixed at these new levels for one-week periods over a three-month period. The result was to create exogenous deviations in the prices at "treatment" stations from what they otherwise would have been. During this period, information on the daily volumes of gasoline sold at the treatment stations was collected, as well as the daily prices at competitor stations within two miles of each of the 54 treatment stations.1 Barron et al. (2004) considered the effect of the number of sellers ("seller density") on aggregate price levels and on price dispersion across markets using single-day