Consumer search and dynamic price dispersion: an application to gasoline markets

Abstract

This article studies the role of imperfect information in explaining price dispersion. We use a new panel data set on the U.S. retail gasoline industry and propose a new test of temporal price dispersion to establish the importance of consumer search. We show that price rankings vary significantly over time; however, they are more stable among stations at the same street intersection. We establish the equilibrium relationships between price dispersion and key variables from consumer search models. Price dispersion increases with the number of firms in the market, decreases with the production cost, and increases with search costs.

Understanding gasoline price dispersion

“…In sum, we believe that we have the best available modeling approach given the data and empirical evidence in the literature. 7 This is also the expression one can get with a modeling strategy which endows each individual with 1…”

The impact of process innovation on prices: Evidence from automated fuel retailing in The Netherlands

“…We drop these sites because our difference-8 Data from the same source have been used in Soetevent et al (2014) and Heijnen et al (2015). 9 Data collected by the Oil Price Information Service (OPIS) have been widely used in applied papers on pricing and price strategies, examples include Taylor and Hosken (2007); Doyle and Samphantharak (2008), Chandra andTappata (2011), Myers et al (2011), Lewis (2012Lewis ( , 2014 and Tappata and Yan (2013) 11 See e.g. European Union (1999), where it is argued in the Exxon/Mobil case that 'in some countries, it is possible to consider fuel retailing on motorways as a separate product market' (point 436).…”

Price dispersion, chain heterogeneity, and search in online grocery markets

“…Second, when some consumers are perfectly informed about market prices while others are not, price dispersion could arise as a mixed-strategy equilibrium outcome (Stigler 1961;Varian 1980). 1 In this case, stores' relative positions in the price distribution change over time-which makes it more difficult for consumers to identify the lowest-price store (Chandra and Tappata 2011). These two accounts are not mutually exclusive and may, when taken together, explain observed price dispersion.…”

“…On the one hand, there are studies measuring price dispersion for a single product category; examples include orange juice (Berck et al 2008), gasoline (Barron et al 2004;Chandra and Tappata 2011), books and CDs (Brynjolfsson and Smith 2000;Brynjolfsson et al 2010), spare parts for cars (Delgado and Waterson 2003), computer and electronic products (Baye et al 2004a, b;Ellison and Ellison 2009), and airline tickets (Bachis and Piga 2011;Orlov 2011). 5 On the other hand, some studies compare price dispersion across different products with the goal of establishing empirical regularities that could help to identify the sources of price dispersion.…”