An empirical analysis of the spatial variability of fuel prices in the United States

Antonin Bergeaud and Juste Raimbault

Transportation Research Part A: Policy and Practice, 2020, vol. 132, issue C, 131-143

Abstract: In this paper, we use a newly constructed dataset to study the geographic distribution of fuel price across the US at a very high resolution. We study the influence of socio-economic variables through different and complementary statistical methods. We highlight an optimal spatial range roughly corresponding to stationarity scale, and significant influence of variables such as median income, wage with a non-simple spatial behavior that confirms the importance of geographical particularities. On the other hand, multi-level modeling reveals a strong influence of the state in the level of price but also of some local characteristics including population density. Through the combination of such methods, we unveil the superposition of a governance process with a local socio-economical spatial process. The influence of population density on prices is furthermore consistent with a minimal theoretical model of competition between gas stations, that we introduce and solve numerically. We discuss developments and applications, including the elaboration of locally parametrized car-regulation policies.

Keywords: Fuel price; Data crawling; Spatial analysis; Geographically weighted regression; Multi-level modeling (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Working Paper: An empirical analysis of the spatial variability of fuel prices in the United States (2020)
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DOI: 10.1016/j.tra.2019.10.016

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