Does Accessibility Affect Retail Prices and Competition? An Empirical Application


This paper attempts to link the concepts of accessibility and the firm’s conduct in the regional retail market in Spain. We use a database that includes sale price, service station location, level of traffic and type of road. We show that accessibility has two main effects on final prices. The accessibility of own-brand gas stations increased their prices while the accessibility of rival gas stations causes price reductions. If we include the value of time, then no rational consumer should travel further than his nearest petrol station in search of lower prices. Finally, our paper shows that service stations can establish a dominant position if consumers do not have access to other retailers within a 17-min radius.

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Fig. 1


  1. 1.

    Handy (2002) explicitly states that in most U.S. transport plans There are constant references to the accessibility issue and its improvement defined as a major objective.

  2. 2.

    See Handy and Niemeier (1997); Baradaran and Ramjerdi (2001); El-Geneidy and Levinson (2006).

  3. 3.

    For example, how the access facility generates opportunities for individuals in terms of improving their employment prospects (see van Wee et al. 2001; Srour et al. 2002; Franklin and Waddell 2003). For price variation of goods such as housing, see El-Geneidy and Levinson (2006); and for the possibilities when locating new sales outlets, see Ritsema van Eck and de Jong (1999).

  4. 4.

    Nevertheless, we do not estimate the number of consumers who will be excluded if monopolization occurs, and similar. Due that, it is only a motivation, not an issue of the paper.

  5. 5.

    The negative relationship between the proximity of competitors and the price level is not unique to the gasoline market. A good example is provided by the article by Mazzeo (2002) on the market for road motels in the United States.

  6. 6.

    See Perdiguero and Borrell (2007) for a more detailed view of the sector’s liberalization process and its current situation in Spain. Alternatively, see Perdiguero and Jiménez (2009) for a differentiated regional analysis.

  7. 7.

    All the following data excluding prices were supplied by Catalist (, which is a company dedicated to the sale of information on the petrol sector. Annex I gives a more in-depth explanation of some of the variables. The subsequent analysis was carried out by the programming of computer codes, using the Matlab statistical program and the SAS package; these permitted us to manage a broad database.

  8. 8.

    It should be borne in mind that service stations in Spain are obliged to display their prices on panels at their entrances; they must also make their prices available to the Ministry of Industry, Trade and Tourism, which publish them daily on its webpage.

  9. 9.

    As we indicate in the introductory paragraph of this Section 3, we are assuming that most people live near their jobs. This assumption induces us not to take into account commuters, i.e., people who live far away from their jobs. In this case, the transport cost would be reduced and the analysis in Eq. (3) would not be effective.

  10. 10.

    For a more detailed explanation of the components that make up the price of petrol, see Miras (2007).


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This paper has benefited from helpful comments and suggestions by Juan Carlos Martín, Javier Campos and two anonymous referees. We are also grateful for the database assistance by Héctor Rodríguez and Adrià Botey. This research has received financial help from the Spanish Ministry of Science and Technology (ECO 2009-06946/ECON). A previous version of this paper has been published as Working Paper no. 456 in the Fundación de las Cajas de Ahorros (FUNCAS) collection. The usual disclaimer applies.

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Correspondence to Juan Luis Jiménez.


Annex I

Definition of variables (from Catalist)

Primary traffic

This is an estimate of the 24-h average two-way traffic flow on the primary street to the nearest thousand. Guidelines for the various definitions used are:

  • Poor: Traffic levels are less than 5,000 vehicles per day.

  • Medium: Traffic levels are between 5,000 and 15,000 vehicles per day.

  • Good: Traffic levels are between 15,000 and 25,000 vehicles per day.

  • Very good: Traffic levels are in excess of 25,000 vehicles per day.

Site location

Rural: Countryside background or low-density residential and industrial use, as well as locations on long-distance commuter routes that experience consistent traffic flows, e.g. a site on a quiet stretch of trunk road.

Industry/office: Low residential back-up and much evidence of commercial units e.g. industrial/office/retail. Applicable to business infrastructures such as port areas, manufacturing, distribution centres, shopping centres etc.

Residential: Tends to be located away from the commercial and industrial areas and surrounded by much private housing.

Urban transient: Characterized by high traffic volumes spread evenly throughout the day. Bypasses and ring roads are included in this class.


Annex II

Map I

Probabilities of obtaining petrol stations with lower prices

Note: White points are petrol stations with high probability (more than 0.5). Low grey are those petrol stations with medium probability. Medium grey are those with low probability. The black ones are petrol stations with a probability equal to 0.

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Jiménez, J.L., Perdiguero, J. Does Accessibility Affect Retail Prices and Competition? An Empirical Application. Netw Spat Econ 11, 677–699 (2011).

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  • Accessibility
  • Location
  • Petrol stations
  • Oligopoly

JEL Classification

  • R40
  • L13
  • L81