This blog post is in response to the Reason Foundation’s paper titled Transit Utilization and Traffic Congestion: Is There a Connection?.
Despite the mounting evidence, the Reason Foundation’s paper calls in question the work of economists and policy makers, as well as the experience of business owners from around the nation.
The Reason Foundation’s paper fails to recognize that our transportation network requires both an effective highway system, and high quality public transportation in order to provide the proximity to opportunity that both business owners and workers desire.
For instance, a recent American Public Transportation Association study titled The Role of Transit in Support of High Growth Clusters in the U.S. shows that nearly a half million jobs will be at risk due to traffic congestion. Municipal Planning Organizations from around the country, when interviewed for the study, noted that it is impractical in the vast majority of cases to build enough highway lane miles to accommodate anticipated job growth. They believe that high quality public transportation will be a necessary ingredient for their economies to continue to grow.
Statistical Biases Present
The Reason Foundation’s analysis is hampered by a number of statistical biases. Undergraduate and graduate students are both taught to assess their statistical work for a number biases and fallacies. Reason’s work fails to take note of the basics of statistical study. Just a few are noted below.
Biased Sample, Selective Reporting
1. Vehicle Miles Traveled is a measure of the amount of travel, not the success of accessing a destination. High quality public transportation, along with public transit supportive land use actually will reduce distance between activity nodes, improving the success of trips in reaching destinations in a timely manner.
2. The study’s use of the travel time index as the key methodology, shows the intensity of congestion instead of exposure to congestion. In cities with high quality public transportation, smaller proportions of the population are exposed to long, intense, congested commutes. Residents in these cities therefore have lower per capita congestion costs and lower out of pocket transportation expenses.
Failure to Show Causality, Yet Data Presented as Causal
3. Reason is measuring what has occurred – congestion on the highway side, to what has occurred with public transit travel. The correct comparison is to measure what would have occurred without public transit or with less or more public transit. Comparing something to itself is invalid. This is why drug tests have placebos.
4. Several good, peer-reviewed studies show that high quality public transit (convenient, comfortable, integrated and relatively fast) reduces congestion delay on parallel roadways. Therefore, public transit can in fact reduce congestion for highway users.
Additional Causal Fallacies: Complex Cause
5. The failure to control for city size, employment rates, and the frequency of public transportation service makes any attempt to draw causality fallacious. In fact, the Reason Foundation tries to measure public transit where high-frequency public transit does not exist or where public transit does not exist at all. Imagine measuring highways or road capacity where no roads existed or low quality roads were built. It would result in an inaccurate assessment of the performance of our road system.
Resources for Review
For those that seek to better understand the true nature of traffic congestion and public transportation’s ability to impact the nation’s commutes, they should refer to these resources:
Md Aftabuzzaman, Graham Currie and Majid Sarvi (2010), “Evaluating the Congestion Relief Impacts of Public Transport in Monetary Terms,” Journal of Public Transportation, Vol. 13, No. 1, pp. 1-24; http://www.nctr.usf.edu/jpt/pdf/JPT13-1.pdf. Also see, “Exploring The Underlying Dimensions Of Elements Affecting Traffic Congestion Relief Impact Of Transit,” Cities, Vol. 28, Is. 1 (www.sciencedirect.com/science/journal/02642751), February 2011, Pages 36-44.
Michael L. Anderson (2013), Subways, Strikes, and Slowdowns: The Impacts of Public Transit on Traffic Congestion, Working Paper No. 18757, National Bureau of Economic Research (www.nber.org); at http://www.nber.org/papers/w18757.
Sutapa Bhattacharjee and Andrew R. Goetz (2012), “Impact Of Light Rail On Traffic Congestion In Denver,” Journal of Transport Geography; abstract at www.sciencedirect.com/science/article/pii/S0966692312000129.
Changchoo Kim, Yong-Seuk Park and Sunhee Sang (2008), Spatial and Temporal Analysis of Urban Traffic Volume, 2008 ESRI International User Conference; at http://gis.esri.com/library/userconf/proc08/papers/papers/pap_1613.pdf.
J. Richard Kuzmyak (2012), Land Use and Traffic Congestion, Report 618, Arizona DOT (www.azdot.gov); at http://www.azdot.gov/TPD/ATRC/publications/project_reports/PDF/AZ618.pdf.
Todd Litman (2004), “Impacts of Rail Transit on the Performance of a Transportation System,” Transportation Research Record 1930, Transportation Research Board (www.trb.org), pp. 23-29.
Shih-Che Lo and Randolph W. Hall (2006), “Effects of the Los Angeles Transit Strike On Highway Congestion,” Transportation Research A, Vol. 40, No. 10 (www.elsevier.com/locate/tra), December 2006, pp. 903-917.
Todd Litman (2012), Smart Congestion Relief: Comprehensive Analysis Of Traffic Congestion Costs and Congestion Reduction Benefits, Paper P12-5310, Transportation Research Board Annual Meeting, Victoria Transport Policy Institute (www.vtpi.org); at http://www.vtpi.org/cong_relief.pdf.