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Spatial variability in retail gasoline markets

Asia-Pacific Journal of Regional Science volume 3, pages 581–603 (2019)Cite this article

Abstract

Retail gasoline prices continue to be of much interest to the public, with significant economic implications. Of course, pricing too has considerable influence on human behavioral patterns of movement, particularly travel. While national and state gasoline prices may vary, they are largely tied to fairly predictable factors, including the price of crude oil, weather, political stability, and refinery production capabilities, among others. However, local and regional gasoline prices can vary considerably. Capabilities for better understanding and predicting variation in gasoline retail prices are both informative and necessary, particularly with respect to spatial factors. This paper explores characteristics related to gasoline price differences across a region. Of particular interest is assessing price gouging behavior, especially the targeting of disadvantaged groups. A spatial analytic framework that incorporates exploratory spatial data analysis, remote sensing, geographic information systems and spatial statistics is proposed to investigate the impact of local market conditions on regional retail prices of gasoline.

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Notes

  1. A similar definition of price gouging can be found in The Federal Price Gouging Prevention Act (H.R.1252), which was passed by the US House in May, 2007, but killed in the Senate.

  2. In Michigan, the UDAP Statute MCL 445.903(1)(z) is not specifically targeted at disaster-triggered gouging. Instead, it prohibits charging a price in gross excess of the price for which similar products or services are sold. Likewise, in Maine, 10 M.R.S.A. §1105 (profiteering) 5 MRSA §207 (UTPA) forbids unjust or unreasonable profits in the sale, exchange or handling of necessities.

  3. Twelve different distance thresholds are tested for the six distance-based variables, which leads to nearly three million different regression models to assess. The most significant explanatory variables were adopted in the spatial regression analysis. While other variable combinations might become significant in the spatial regression context, computational complexity is prohibitive in this case for evaluating all potential model combinations.

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Acknowledgements

An initial version of this paper was presented at the 2018 Western Regional Science Association conference held in Pasadena, CA. The first author would also like to thank her UCSB Master's committee members, Richard Church and Stuart Sweeney, for input and comments on this research.

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  1. Department of Geography, University of California of Santa Barbara, Santa Barbara, CA, 93106, USA

    Jing Xu & Alan T. Murray

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  1. Jing Xu
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  2. Alan T. Murray
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Correspondence to Alan T. Murray.

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Xu, J., Murray, A.T. Spatial variability in retail gasoline markets. Asia-Pac J Reg Sci 3, 581–603 (2019). https://doi.org/10.1007/s41685-019-00104-z

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Keywords

  • Pricing behavior
  • Retail
  • Regression
  • GIS
  • Spatial analytics