Consumer and Competitor Reactions: Evidence from a Field Experiment

Abstract

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

Empirical Studies of Gasoline Retailing: A Guide to the Literature

“…Attempts to formally estimate the dynamic pricing strategies of individual gasoline retailers have been limited, perhaps because of data requirement. Barron et al. (2008) use a unique opportunity to impose exogenous price changes on stations of a firm in certain Californian areas to estimate the reactions of competitors.…”

“…5 5 In another example of firm co‐operation, Barron et al. (2008) were given the opportunity to impose exogenous price changes on stations of a major retailer in certain California cities over a 3‐month period. …”

Bigger Is Better: Market Size, Demand Elasticity, and Innovation*

“…The empirical evidence is far more supportive of Hotelling–Lancaster than of Spence–Dixit–Stiglitz. Barron et al (2008) compute price elasticities in U.S. gasoline markets and find that larger markets are associated with more elastic demand; Hummels and Lugovskyy (2008) document that import demand in larger markets is more responsive to changes in trade costs; Tybout (2003), in reviewing the literature on trade liberalization, concludes that markups fall with import competition; Campbell and Hopenhayn (2005) report a positive relationship between market size and firm size for a number of retail industries across U.S. cities; and Hummels and Klenow (2005) find that the number of varities increases less than proportionally with the size of the market across a wide variety of industries and countries 7 . Although others, such as Hummels and Klenow (2005) and Hummels and Lugovskyy (2008), have made the point that the Hotelling–Lancaster construct is more consistent with certain empirical regularities, we are the first to consider its relevance for technological innovation.…”

Market Power in Retail Gasoline Markets

“…When it comes to local competition, studies have found ambiguous relations between station density and price. On the one hand, Barron et al (2004), Barron et al (2008) and Clemenz and Gugler (2006) show that higher station density tends to lower average prices, suggesting that a higher number of sellers raises local competition. This is in line with our findings, which 5 See Bresnahan (1989) for a discussion of this model.…”