Does Accessibility Affect Retail Prices and Competition? An Empirical Application

Abstract

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

Notes

  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 (www.catalist.com), 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).

References

  1. Atkinson B, Eckert A, West DS (2009) Price matching and the domino effect in a retail gasoline market. Econ Inq 47(3):568–588

    Article  Google Scholar 

  2. Baradaran S, Ramjerdi F (2001) Performance of accessibility measures in Europe. J Transp Stat 4(2/3):31–48

    Google Scholar 

  3. Barron JM, Taylor BA, Umbeck JR (2004) Number of sellers, average prices, and price dispersion. Int J Ind Organ 22:1041–1066

    Article  Google Scholar 

  4. Berry S (1994) Estimating discrete-choice models of product differentiation. Rand J Econ 25(2):242–262

    Article  Google Scholar 

  5. Berry S, Levinshon J, Pakes A (1995) Automobile prices in market equilibrium. Econometrica 63(4):841–890

    Article  Google Scholar 

  6. Borenstein S (1991) Selling costs and switching costs: explaining retail gasoline margins. Rand J Econ 22(3):354–369

    Article  Google Scholar 

  7. Borrell JR, Perdiguero J (2007) La Competència en la distribució de gasolina a Catalunya. Tribunal Català de Defensa de la Competència (TCDC), Barcelona

  8. Bromiley P, Papenhausen C, Borchert P (2002) Why do gas prices vary, or towards understanding the micro-structure of competition. Manage Decis Econ 23:171–186

    Article  Google Scholar 

  9. Caixa L (2007) Anuario Económico de España 2007. Servicio de Estudios de La Caixa, Barcelona

    Google Scholar 

  10. Campos J, de Rus G (2002) Dotación de infraestructuras y política europea de transporte. Papeles de Economía Española 91:169–181

    Google Scholar 

  11. Comisión Nacional de Competencia (2009) Informe sobre la competencia en el sector de carburantes de automoción. Comisión Nacional de Competencia, Madrid

    Google Scholar 

  12. El-Geneidy AM, Levinson DM (2006) Access to destinations: development of accessibility measures, Report 2006-16, Minnesota Department of Transportation

  13. Franklin J, Waddell P (2003) A hedonic regression of home prices in King County, Washington using activity-specific accessibility measures. Paper presented at the Transportation Research Board 82nd Annual Meeting, Washington DC

  14. Handy SL (2002) Accessibility—vs mobility—enhancing strategies for addressing automobile dependence in the US. Paper presented at the Transportation Research Board 82nd Annual Meeting, Washington DC

  15. Handy SL, Niemeier DA (1997) Measuring accessibility: an exploration of issues and alternatives. Environ Plann A 29(7):1175–1194

    Article  Google Scholar 

  16. HEATCO, Developing Harmonised European Approaches for Transport Costing and Project Assessment (2006): Deliverable 5: Proposal for Harmonised Guidelines. European Commission

  17. Hotelling H (1929) Stability in competition. Econ J 39:41–57

    Article  Google Scholar 

  18. Ivaldi M, Verboven F (2005) Quantifying the effects from horizontal mergers in European competition policy. Int J Ind Organ 23(9–10):669–691

    Article  Google Scholar 

  19. Kaufman PR, MacDonald JM, Lutz SM, Smallwood DM (1997) Do the poor pay more for food? Item selection and price differences affect low-income household food costs. Agric Econ Rep Number 759. Economic Research Service, United States Department of Agriculture

  20. MacDonald J, Nelson PE (1991) Do the poor still pay more? Food price variations in large metropolitan areas. J Urban Econ 30:344–359

    Article  Google Scholar 

  21. Mazzeo MJ (2002) Competitive outcomes in product-differentiated oligopoly. Rev Econ Stat 84:716–728

    Article  Google Scholar 

  22. Miras P (2007) Los mercados de productos petrolíferos: Una panorámica. Econ Ind 365:69–78

    Google Scholar 

  23. Pakes A, Berry S, Levinshon J (1993) Applications and limitations of some recent advances in empirical industrial organization: price indexes and the analysis of environmental change. Am Econ Rev 83(2):241–246

    Google Scholar 

  24. Perdiguero J, Borrell JR (2007) La difícil conducción de la competencia por el sector de las gasolinas en España. Econ Ind 365:113–125

    Google Scholar 

  25. Perdiguero J, Jiménez JL (2009) ¿Competencia o colusión en el mercado de gasolina?: una aproximación a través del parámetro de conducta. Rev de Econ Apl XVII(50):27–45

    Google Scholar 

  26. Pinske J, Slade ME, Brett C (2002) Spatial price competition: a semiparametric approach. Econometrica 70(3):1111–1153

    Article  Google Scholar 

  27. Ritsema van Eck JR, de Jong T (1999) Accessibility analysis and spatial competition effects in the context of GIS-supported service location planning. Comput Environ Urban Syst 23:75–89

    Article  Google Scholar 

  28. Salop S (1979) Monopolistic competition with outside goods. Bell J Econ 10:141–156

    Article  Google Scholar 

  29. Spiller PT, Huang CF (1986) On the extent of the market: wholesale gasoline in the northeastern United States. J Ind Econ XXXV:131–145

    Article  Google Scholar 

  30. Srour I, Kockelman K, Dunn T (2002) Accessibility indices: connection to residential land prices and location choices. Transp Res Rec 1805:25–34

    Article  Google Scholar 

  31. Staiger D, Stock JH (1997) Instrumental variables regression with weak instruments. Econometrica 65(3):557–586

    Article  Google Scholar 

  32. Stewart H, Davis D (2005) Price dispersion and accessibility: a case study of fast food. South Econ J 4(71):784–799

    Article  Google Scholar 

  33. Stigler G (1961) The economics of information. J Polit Econ 69:213–225

    Article  Google Scholar 

  34. van Wee B, Hagoort M, Annema JA (2001) Accessibility measures with competition. J Transp Geogr 9:199–208

    Article  Google Scholar 

  35. Vickerman RW (1974) Accessibility, attraction and potential: a review of some concepts and their use in determining mobility. Environ Plann A 6:675–691

    Article  Google Scholar 

  36. Wachs M, Kumagai T (1973) Physical accessibility as a social indicator. Socio-econ Plann Sci 7:327–456

    Article  Google Scholar 

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Acknowledgements

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.

Appendices

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.

Motorway.

Annex II

Map I
figure2

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). https://doi.org/10.1007/s11067-010-9144-5

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Keywords

  • Accessibility
  • Location
  • Petrol stations
  • Oligopoly

JEL Classification

  • R40
  • L13
  • L81