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Revisiting the relationship between traffic congestion and the economy: a longitudinal examination of U.S. metropolitan areas

  • Wesley E. Marshall
  • Eric Dumbaugh
Article

Abstract

Conventional transportation practices typically focus on alleviating traffic congestion affecting motorists during peak travel periods. One of the underlying assumptions is that traffic congestion, particularly during these peak periods, is harmful to a region’s economy. This paper seeks to answer a seemingly straightforward question: is the fear of the negative economic effects of traffic congestion justified, or is congestion merely a nuisance with little economic impact? This research analyzed 30 years of data for 89 US metropolitan statistical areas (MSAs) to evaluate the economic impacts of traffic congestion at the regional level. Employing a two-stage, least squares panel regression model, we controlled for endogeneity using instrumental variables and assessed the association between traffic congestion and per capita gross domestic product (GDP) as well as between traffic congestion and job growth for an 11-year time period. We then investigated the relationship between traffic congestion and per capita income for those same 11 years as well as for the thirty-year time period (1982–2011) when traffic congestion data were available. Controlling for the key variables found to be significant in the existing literature, our results suggest that the potential negative impact of traffic congestion on the economy does not deserve the attention it receives. Economic productivity is not significantly negatively impacted by high levels of traffic congestion. In fact, the results suggest a positive association between traffic congestion and per capita GDP as well as between traffic congestion and job growth at the MSA level. There was a statistically insignificant effect on per capita income. There may be valid reasons to continue the fight against congestion, but the idea that congestion will stifle the economy does not appear to be one of them.

Keywords

Traffic congestion Economy GDP VMT Cities 

Notes

Acknowledgements

The authors would like to thank Ed Gaviria for his help during our initial discussions surrounding this topic as well as his preliminary data collection efforts. Although we ended up developing our own instrumental variables for this analysis, we appreciate Dr. Matthias Sweet of Ryerson University for generously sharing those used in his impressive papers. Lastly, we would like to thank the anonymous reviewers for their detailed and insightful recommendations.

Compliance with ethical standards

Conflict of interest

All authors that they have no conflict of interest.

References

  1. Ahangari, H., Outlaw, J., Atkinson-Palombo, C., Garrick, N.W.: An Investigation into the Impact of Fluctuations in Gasoline Prices and Macroeconomic Conditions on Road safEty in Developed Countries. Transportation Reserach Board Annual Meeting, Washington DC (2014)Google Scholar
  2. Anas, A., Xu, R.: Congestion, land use, and job dispersion: A general equilibrium model. J. Urban Econ. 45, 451–473 (1999)CrossRefGoogle Scholar
  3. Andolfatto, D., Ferrall, C., Gomme, P.: Human Capital Theory and the Life-Cycle Pattern of Learning and Earning, Income and Wealth. In: University, S.F. (ed.) Burnaby, BC, Canada (2000)Google Scholar
  4. Arnott, R.: Congestion tolling with agglomeration externalities. J. Urban Econ. 62, 187–203 (2007)CrossRefGoogle Scholar
  5. ASCE: Infrastructure Report Card. American Society of Civil Engineers, Washington DC (2017)Google Scholar
  6. Baum-Snow, N.: Did highways cause suburbanization? Quart. J. Econ. 122, 775–805 (2007)CrossRefGoogle Scholar
  7. Bertini, R.: You Are the Traffic Jam: An Examination of Congestion Measures. Transportation Research Board, Washington DC (2006)Google Scholar
  8. Bilbao-Ubillos, J.: The costs of urban congestion: estimation of welfare losses arising from congestion on cross-town link roads. Transp. Res. A Policy Pract. 42, 1098–1108 (2008)CrossRefGoogle Scholar
  9. BLS: CPI Inflation Calculator [Online]. Bureau of Labor Statistics, U.S. Department of Labor, Washington DC. http://www.bls.gov/data/inflation_calculator.htm (2017). Accessed 25 Sept 2017
  10. Boarnet, M.G.: Infrastructure services and the productivity of public capital: The case of streets and highways. Natl. Tax J. 50, 39–57 (1997)Google Scholar
  11. Bobbitt-Zeher, D.: The gender income gap and the role of education. Sociol. Educ. 80, 1–22 (2007)CrossRefGoogle Scholar
  12. C-SPAN: House Transportation and Infrastructure Committee [Online]. Cable-Satellite Public Affairs Network. www.c-span.org/organization/?2118&congress=114 (2016). Accessed 9 Aug 2016
  13. Cervero, R.: Jobs-housing balance revisited—trends and impacts in the San Francisco Bay Area. J. Am. Plan. Assoc. 62, 492–511 (1996)CrossRefGoogle Scholar
  14. Cervero, R.: Induced travel demand: research design, empirical evidence, and normative policies. J. Plan. Lit. 17, 3–20 (2002)CrossRefGoogle Scholar
  15. Cervero, R., Duncan, M.: Which reduces vehicle travel more: jobs-housing balance or retail-housing mixing? J. Am. Plan. Assoc. 72, 475–490 (2006)CrossRefGoogle Scholar
  16. Cervero, R., Hansen, M.: Induced travel demand and induced road investment—a simultaneous equation analysis. J. Transp. Econ. Policy 36, 469–490 (2002)Google Scholar
  17. Chatman, D.G., Noland, R.B.: Transit Service, Physical Agglomeration and Productivity in US Metropolitan Areas. Urban Studies 51, 917–937 (2014)CrossRefGoogle Scholar
  18. Copeland, L.: Cities Afraid of Death by Congestion. USA Today, March 1 (2007)Google Scholar
  19. Crane, R., Chatman, D.G.: Traffic and sprawl : evidence from U.S. commuting from 1985–1997. Plan. Mark. 6, 14–22 (2003)Google Scholar
  20. Detotto, C., Otranto, E.: Does crime affect economic growth? Kyklos 63, 330–345 (2010)CrossRefGoogle Scholar
  21. DOJ & FBI: Uniform Crime Reporting Statistics [Online]. Clarksburg, WV: U.S. Department of Justice, Federal Bureau of Investigation. www.ucrdatatool.gov (2014)
  22. Downs, A.: Stuck in Traffic. Brookings Institute, Washington DC (1992)Google Scholar
  23. Downs, A.: Can Traffic Congestion Be Cured? [Online]. Washington DC. http://www.brookings.edu/research/opinions/2006/06/30transportation-downs (2006)
  24. Duranton, G., Turner, M.A.: The fundamental law of road congestion: evidence from US cities. Am. Econ. Rev. 101, 2616–2652 (2011)CrossRefGoogle Scholar
  25. Dutzik, T., Baxandall, P.: A new direction: our changing relationship with driving and the implications for America’s future. U.S. PIRG Education Fund, Washington DC (2013)Google Scholar
  26. Ewing, R. & Cervero, R.: Travel and the built environment—A synthesis. Land Development and Public Involvement in Transportation, pp. 87–114 (2001)Google Scholar
  27. Ewing, R., Pendall, R., Chen, D.: Measuring sprawl and its transportation impacts. Travel Demand Land Use 2003, 175–183 (2003)Google Scholar
  28. Federal Highway Administration.: Focus on Congestion Relief [Online]. U.S. Department of Transportation, Washington DC. http://www.fhwa.dot.gov/congestion/ (2013). Accessed 12 May 2014
  29. Fernald, J.G.: Roads to prosperity? Assessing the link between public capital and productivity. Am. Econ. Rev. 89, 619–638 (1999)CrossRefGoogle Scholar
  30. Frank, L.D., Pivo, G.: Impacts of mixed use and density on utilization of three modes of travel: single-occupant vehicle, transit, and walking. Transp. Res. Rec. 1466, 44–52 (1994)Google Scholar
  31. Glaeser, E., Kahn, M.E.: Working Paper No. 9733: Sprawl and Urban Growth. National Bureau of Economic Research, Cambridge (2003)Google Scholar
  32. Glaeser, E.L.: Cities, information, and economic growth. Cityscape 1, 9–47 (1994)Google Scholar
  33. Glaeser, E.L.: Are cities dying? J. Econ. Perspect. 12, 139–160 (1998)CrossRefGoogle Scholar
  34. Glaeser, E.L.: Triumph of the City: How Our Greatest Invention Makes Us Richer, Smarter, Greener, Healthier, and Happier. Penguin Press, New York (2011)Google Scholar
  35. Glaeser, E.L., Kallal, H.D., Scheinkman, J.A., Shleifer, A.: Growth in cities. J. Polit. Econ. 100, 1126–1152 (1992)CrossRefGoogle Scholar
  36. Glaeser, E.L., Kohlhase, J.E.: Cities, regions and the decline of transport costs. Pap. Reg. Sci. 83, 197–228 (2004)CrossRefGoogle Scholar
  37. Glaeser, E.L., Kolko, J., Saiz, A.: Consumer city. J. Econ. Geogr. 1, 27–50 (2001)CrossRefGoogle Scholar
  38. Gordon, P., Kumar, A., Richardson, H.W.: Congestion, changing metropolitan structure, and city size in the United-States. Int. Reg. Sci. Rev. 12, 45–56 (1989)CrossRefGoogle Scholar
  39. Graham, D.J.: Variable returns to agglomeration and the effect of road traffic congestion. J. Urban Econ. 62, 103–120 (2007)CrossRefGoogle Scholar
  40. Grant-Muller, S., Laird, J.: International Literature Review of the Costs of Road Traffic Congestion with the Main Focus on the Different Methods Used to Measure the Costs of Congestion. Institute for Transport Studies, University of Leeds, Leeds, Scotland (2007)Google Scholar
  41. Greene, W.H.: Econometric Analysis. Prentice Hall, Boston (2012)Google Scholar
  42. Harris, T.F., Ioannides, Y.M.: Productivity and Metropolitan Density. Tufts University, Medford, MA (2000)Google Scholar
  43. Hartgen, D.T., Fields, M.G., Layzell, A.L., San Jose, E.: How Employers View Traffic Congestion: Results of National Survey. Transportation Research Record, pp. 56–66 (2012)Google Scholar
  44. Highway Research Board: Urban Traffic Congestion. National Academy of Science, National Research Council, Washington DC (1954)Google Scholar
  45. Hymel, K.: Does traffic congestion reduce employment growth? J. Urban Econ. 65, 127–135 (2009)CrossRefGoogle Scholar
  46. Jorgensen, R.E.: Influence of expressways in diverting traffic from alternate routes and in generating new traffic. Highw. Res. Board Proc. 27, 322–330 (1947)Google Scholar
  47. Katchova, A.: Instrumental Variables [Online]. Econometrics Academy, Lexington, KY. https://sites.google.com/site/econometricsacademy/econometrics-models/instrumental-variables (2014). Accessed 25 Jan 2014
  48. Katz, B., Bradley, J.: The Metropolitan Revolution: How Cities and Metros are Fixing Our Broken Politics and Fragile Economy. Brookings Institution Press, Washington DC (2013)Google Scholar
  49. Klaer, J., Northrup, B.: Effects of GDP on Violent Crime. Georgia Tech, Atlanta (2014)Google Scholar
  50. Kriger, D., Miller, C., Baker, M., Joubert, F.: Costs of urban congestion in Canada—A model-based approach. Transp. Res. Record, 94–100 (2007)Google Scholar
  51. Levinson, D., Marshall, W., Axhausen, K.: Elements of Access. Network Design Lab, Sydney (2017)Google Scholar
  52. Levinson, D., Wu, Y.: The rational locator reexamined: are travel times still stable? Transportation 32, 187–202 (2005)CrossRefGoogle Scholar
  53. Levinson, D.M., Kumar, A.: The rational locator—why travel-times have remained stable. J. Am. Plan. Assoc. 60, 319–332 (1994)CrossRefGoogle Scholar
  54. Lewis, J.B., Devine, B., Pitcher, L., Martis, K.C.: Digital Boundary Definitions of United States Congressional Districts, 1789–2012 [Online]. UCLA. http://cdmaps.polisci.ucla.edu (2013). Accessed 10 Aug 2016
  55. Litman, T.: Congestion Costing Critique. Victoria Transport Policy Institute, Victoria (2014)Google Scholar
  56. Lomax, T., Turner, S., Shunk, G.: NCHRP Report 398: Quantifying Congestion. National Academy Press, Washington DC (1997)Google Scholar
  57. Manson, S., Schroeder, J., Riper, D.V., Ruggles, S.: PUMS National Historical Geographic Information System: Version 12.0. University of Minnesota, Minneapolis (2017)Google Scholar
  58. Manville, M., King, D.A., Smart, M.J.: The driving downturn: a preliminary assessment. J. Am. Plan. Assoc. 83, 14p (2017)Google Scholar
  59. Marrocu, E., Paci, R., Usai, S.: Productivity growth in the old and new europe: the role of agglomeration externalities. J. Reg. Sci. 53, 418–442 (2013)CrossRefGoogle Scholar
  60. Marshall, W.E., Garrick, N.W.: Effect of street network design on walking and biking. Transp. Res. Rec., 103–115 (2010)Google Scholar
  61. Marshall, W.E., Garrick, N.W.: Does street network design affect traffic safety? Accid. Anal. Prev. 43, 769–781 (2011)CrossRefGoogle Scholar
  62. Mathworks: Time Series Regression VIII: Lagged Variables and Estimator Bias [Online]. www.mathworks.com/help/econ/examples/time-series-regression-viii-lagged-variables-and-estimator-bias.html (2017)
  63. McDonald, N.C.: Active transportation to school—trends among US schoolchildren, 1969–2001. Am. J. Prev. Med. 32, 509–516 (2007)CrossRefGoogle Scholar
  64. Mondschein, A., Brumbaugh, S., Taylor, B.D.: Congestion and Accessibility: What’s the Relationship?. Institute of Transport Studies, Los Angeles (2010)Google Scholar
  65. Morris, E.: From horse power to horsepower. Access 30, 2–9 (2007)Google Scholar
  66. Murnane, R.J.: Educating urban children. National Bureau of Economic Research, Cambridge (2008)CrossRefGoogle Scholar
  67. NCHRP: Synthesis 311: performance measures of operational effectiveness for highway segments and systems. Transportation Research Board, Washington DC (2003)Google Scholar
  68. Noland, R., Quddus, M.: A spatially disaggregate analysis of road casualties in England. Accid. Anal. Prev. 36, 973–984 (2004)CrossRefGoogle Scholar
  69. Noland, R.B.: Relationships between highway capacity and induced vehicle travel. Transp. Res. A Policy Pract. 35, 47–72 (2001)CrossRefGoogle Scholar
  70. Noland, R.B.: Transport planning and environmental assessment: implications of induced travel effects. Int. J. Sustain. Transp. 1, 1–28 (2007)CrossRefGoogle Scholar
  71. Paci, R., Usai, S.: Externalities, Knowledge, Spillovers and the Spatial Distribution of Innovation. Cagliari, Solter (2000)Google Scholar
  72. Portes, A., Rumbaut, R.N.G.: Immigrant America: a portrait. University of California Press, Berkeley and Los Angeles, California (2014)Google Scholar
  73. Public Works Administration: National System of Interstate Highways. Public Works Administration, Washington DC (1947)Google Scholar
  74. Public Works Administration: Interstate and Defense Highways Map. Public Works Administration, Washington DC (1957)Google Scholar
  75. Rajamani, J., Bhat, C.R., Handy, S., Knaap, G., Song, Y.: Assessing impact of urban form measures on nonwork trip mode choice after controlling for demographic and level-of-service effects. Travel Demand Land Use 2003, 158–165 (2003)Google Scholar
  76. Rappaport, J.: Moving to nice weather. Reg. Sci. Urban Econ. 37, 375–398 (2007)CrossRefGoogle Scholar
  77. Redman, A., Sai, A.: Opportunities in an Urbanizing World. Credit Suisse Research Institute, Zurich (2012)Google Scholar
  78. Ribeiro, A., Antunes, A.P., Paez, A.: Road accessibility and cohesion in lagging regions: empirical evidence from Portugal based on spatial econometric models. J. Transp. Geogr. 18, 125–132 (2010)CrossRefGoogle Scholar
  79. Roads & Bridges.: Congestion: DC Tops TTI List of Most Congested Cities [Online]. Arlington Heights, IL. Available: www.roadsbridges.com/congestion-dc-tops-tti-list-most-congested-cities (2013). Accessed 25 Sept 2017
  80. Roddy, H.J.: Complete geography, American Book Company, New York, Cincinnati etc (1902)Google Scholar
  81. Roman, J. The Puzzling Relationship Between Crime and the Economy. Citylab (2013)Google Scholar
  82. Rose, H., Betts, J.R.: The effect of high school courses on earnings. Rev. Econ. Stat. 86, 497–513 (2004)CrossRefGoogle Scholar
  83. Safirova, E., Gillingham, K., Houde, S.: Measuring marginal congestion costs of urban transportation: Do networks matter? Transp. Res. A Policy Pract. 41, 734–749 (2007)CrossRefGoogle Scholar
  84. Schrank, D., Eisele, B., Lomax, T.: Urban Mobility Report. Texas A&M Transportation Institute, College Station (2012)Google Scholar
  85. Schrank, D., Eisele, B., Lomax, T., Bak, J.: Urban Mobility Scorecard. Texas A&M Transportation Institute, College Station (2015)Google Scholar
  86. Sciara, G.-C.: Planning for unplanned pork. J. Am. Plan. Assoc. 78, 17p (2012)CrossRefGoogle Scholar
  87. Staley, S.: Traffic Congestion and the Economic Decline of Cities [Online]. Reason Foundation. http://reason.org/news/show/traffic-congestion-and-the-economic (2012). Accessed 6 April 2014
  88. Sundquist, E., Mccahill, C.: For the first time in a decade, U.S. per capita highway travel ticks up. State Smart Transportation Initiative, Madison (2015)Google Scholar
  89. Sweet, M.: Does traffic congestion slow the economy? J. Plan. Lit. 26, 391–404 (2011)CrossRefGoogle Scholar
  90. Sweet, M.: Do firms flee traffic congestion? J. Transp. Geogr. 35, 10p (2014a)CrossRefGoogle Scholar
  91. Sweet, M.: Traffic congestion’s economic impacts: evidence from US metropolitan regions. Urban Stud. 51, 2088–2110 (2014b)CrossRefGoogle Scholar
  92. The Economist.: Falling together: The relationship between crime and GDP in America [Online]. London, England. www.economist.com/blogs/dailychart/2011/09/us-crime-and-gdp (2011). Accessed 25 Sept 2017
  93. The Prism Climate Group: Climate Obsertations [Online]. Corvallis, OR: Oregon State University. http://prism.oregonstate.edu/normals (2014). Accessed 15 Feb 2014
  94. Tsai, Y.H.: Quantifying urban form: compactness versus ‘Sprawl’. Urban Stud. 42, 141–161 (2005)CrossRefGoogle Scholar
  95. U. S. Census: Geographic Areas Reference Manual. U.S. Department of Commerce, Washington DC (1994)Google Scholar
  96. U.S. Census: 2010 Census Urban Area FAQs [Online]. Washington, DC. https://www.census.gov/geo/reference/ua/uafaq.html (2010). Accessed 7 March 2014
  97. Weisbrod, G., Vary, D., Treyz, G.: NCHRP Report 463: Economic Implications of Congestion. National Academy Press, Washington DC (2001)Google Scholar
  98. Weisbrod, G., Vary, D., Treyz, G.: Measuring economic costs of urban traffic congestion to business. Transp. Finance Econ. Econ. Dev. 2003, 98–106 (2003)Google Scholar
  99. Wheaton, W.C.: Commuting, congestion, and employment dispersal in cities with mixed land use. J. Urban Econ. 55, 417–438 (2004)CrossRefGoogle Scholar
  100. Woudsma, C., Jensen, J.F., Kanaroglou, P., Maoh, H.: Logistics land use and the city: a spatial-temporal modeling approach. Transp. Res. E-Logist. Transp. Rev. 44, 277–297 (2008)CrossRefGoogle Scholar
  101. Wright, E.O.: Race, class, and income inequality. Am. J. Sociol. 83, 1368–1397 (1978)CrossRefGoogle Scholar
  102. Zhu, P.Y., Brown, J.R.: Donor states and donee states: investigating geographic redistribution of the US federal-aid highway program 1974-2008. Transportation 40, 203–227 (2013)CrossRefGoogle Scholar
  103. Zolnik, E.J.: The effects of sprawl on private-vehicle commuting distances and times. Environ. Plan. B-Plan. Des. 38, 1071–1084 (2011)CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Department of Civil EngineeringUniversity of Colorado DenverDenverUSA
  2. 2.School of Urban and Regional PlanningFlorida Atlantic UniversityBoca RatonUSA

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