The Driving Downturn: A Preliminary Assessment

Abstract

Problem, research strategy, and findings: We examine why American driving fell between 2004 and 2013, weighing two explanations: that Americans voluntarily moved away from driving (“peak car”), and that economic hardship reduced driving. We analyze aggregate data on travel, incomes, debt, public opinion, and Internet access. These data lack the precision of microdata, but unlike microdata are available annually for years before, during, and after driving’s decline. We find substantial evidence for the economic explanation. During the downturn the cost of driving rose while median incomes fell. The economy grew overall, but did so unequally. Mass driving requires a mass middle class, but economic gains accrued largely to the most affluent. We find less evidence for “peak car.” If Americans voluntarily drove less, they would likely use other modes more. However, despite heavy investment in bicycle infrastructure and public transportation in the 2000s, demand for these modes remained flat while 
driving fell.

Takeaway for practice: If Americans were voluntarily abandoning automobiles for other modes, planners could reduce investments in automobile infrastructure and increase investments in alternative mobility. Driving’s decline, however, was not accompanied by a transit surge or substantial shift to other modes. The lesson of the driving downturn is that people drive less when driving’s price rises. Planners obviously do not want incomes 
to fall, but they should consider policies that increase driving’s price. Planners might also rethink the current direction 
of U.S. transit policy; transit use did not rise even when driving fell at an unprecedented pace.

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Supplemental Material

Supplemental data for this article can be accessed at the publisher’s website.

Notes

1. Our study is similar to the international studies of falling VMT carried out by Bastian and Borjesson (2015) and Bastian, Borjesson, and Eliasson (2016).

2.  Like many telephone surveys, the NHTS also has a low response rate (Meyer, Mok, & Sullivan, 2015; U.S. Department of Transportation, 2011).

3.  The Consumer Expenditure Survey provides further evidence on this nonlinearity. In 2012, households earning more than $150,000 per year spent more than three times as much on transportation ($19,000) as households earning less than $70,000 ($6,100). Little of this difference, however, stemmed from expenses relating to miles driven. Rather, the affluent households spent three times as much buying and maintaining vehicles (i.e., they bought nicer cars), and more than seven times as much on air travel. The affluent spent only twice as much on gas, the factor that most closely reflects distances driven (U.S. Bureau of Labor Statistics, 2014).

4.  If anything, the walk share fell slightly, from 71% to 70% (Schroeder & Wilbur, 2013).

5.  These survey data are mixed. Some surveys show Millennials wanting to live in cities and drive less (Global Strategy Group, 2014); others suggest the opposite (Demand Institute, 2014; Lachmann & Brett, 2015). Census data suggest that Millennials tend to live in suburbs (Kolko, 2015).

6.  Calculated from HPMS data via the Texas Transportation Institute, and from the NTD.

7.  This relationship can be measured another way, which still suggests that PMT growth is not larger where driving fell. In UAs where PMT per capita grew and VMT per capita fell, PMT per capita grew 3%. In UAs where PMT per capita grew and VMT per capita did not fall, PMT per capita grew 67%.

8.  Smart (2014) suggests that increased support for transit stemmed partly from gas price volatility.

9.  Transit ridership does outpace population growth if the trend starts in 1996. This starting point is somewhat misleading, however, since the early 1990s saw inordinately low transit ridership. Starting a trend in 1990 or 2000 shows per capita ridership as unchanged.

Additional information

Notes on contributors

Michael Manville  

Michael Manville ([email protected]) is an assistant professor of urban planning at the UCLA Luskin School of Public Affairs.

David A. King

David A. King ([email protected]) is an assistant professor in the School of Geographical Sciences and Urban Planning at Arizona State University.

Michael J. Smart  

Michael J. Smart ([email protected]) is an assistant professor in the Bloustein School of Planning and Public Policy at Rutgers University.