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<p>This paper examines the determinants of gasoline price dispersion across approximately 120,000 US gas stations using daily price and station-level data over 93 days. Within a structural framework, we decompose observed gasoline price variation into temporal, spatial, and station-specific components. Extending the analysis period from 30 to 90 days shows that the contribution of time fixed effects, a proxy for nationwide/temporal effects (including crude oil prices and national-level structural breaks), rise from 0.32% to 8.64%, underscoring the importance of aggregate shocks. Using the full sample, refinery-level heterogeneity explains about 48% of price dispersion. Terminal-level heterogeneity, a novel aspect in the literature, contributes roughly 2.5%. State taxes account for around 9.5%, and county-level factors such as demographics, operational costs, insurance, and environmental regulation explain up to 18%. In comparison, ZIP-code fixed effects can absorb as much as 68% when compared to county fixed effects. Station-level attributes, including customer ratings, number of ratings, amenities, land prices, and local competition, explain up to 4% of overall gasoline price dispersion.</p>

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Decomposing retail gasoline price dispersion: temporal, spatial, and station-specific contributions from crude oil to consumer preferences

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  • 出版模式：

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  • 发表日期：

    2026年8月3日

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  • Yun Wang

摘要

This paper examines the determinants of gasoline price dispersion across approximately 120,000 US gas stations using daily price and station-level data over 93 days. Within a structural framework, we decompose observed gasoline price variation into temporal, spatial, and station-specific components. Extending the analysis period from 30 to 90 days shows that the contribution of time fixed effects, a proxy for nationwide/temporal effects (including crude oil prices and national-level structural breaks), rise from 0.32% to 8.64%, underscoring the importance of aggregate shocks. Using the full sample, refinery-level heterogeneity explains about 48% of price dispersion. Terminal-level heterogeneity, a novel aspect in the literature, contributes roughly 2.5%. State taxes account for around 9.5%, and county-level factors such as demographics, operational costs, insurance, and environmental regulation explain up to 18%. In comparison, ZIP-code fixed effects can absorb as much as 68% when compared to county fixed effects. Station-level attributes, including customer ratings, number of ratings, amenities, land prices, and local competition, explain up to 4% of overall gasoline price dispersion.