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

• Published in: Transportation research. Part A, Policy and practice Policy and practice, 2020-02, Vol.132, p.131-143
• Main Authors: Bergeaud, Antonin, Raimbault, Juste
• Format: Article
• Language: English
• Subjects: Adaptation and Self-Organizing Systems; Biodiversity and Ecology; Cellular Automata and Lattice Gases; Chaotic Dynamics; Computational Finance; Computer Science; Data crawling; Discrete Mathematics; Environmental Sciences; Fuel price; Geographically weighted regression; Geography; Humanities and Social Sciences; Machine Learning; Multi-level modeling; Multiagent Systems; Nonlinear Sciences; Quantitative Finance; Spatial analysis; Statistics
• ISSN: 0965-8564; 1879-2375
• DOI: 10.1016/j.tra.2019.10.016

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.