Vehicle miles traveled and the built environment: New evidence from panel data

Authors

  • Keith Ihlanfeldt Florida State University

DOI:

https://doi.org/10.5198/jtlu.2020.1647

Keywords:

Vehicle Miles Traveled, Urban Land Use, Global Warming

Abstract

There has been considerable interest in the impact that the built environment has on vehicle miles traveled (VMT). While this issue has been extensively researched, due to the heavy reliance on cross-sectional data, there remains uncertainty regarding how effective local land-use planning and regulation might be in reducing VMT. Based on a 13-year panel of Florida counties, models are estimated that relate VMT to new measures of the spatial distribution of alternative land uses within counties and county urban expansion. Identification of causal effects is established by including year and county fixed effects, along with an extensive set of control variables, and instrumenting those land uses that may be endogenous. Incremental annual changes in the spatial concentration of alternative land uses are found to affect VMT. The policy implication is that appropriate land-use policy can reduce VMT and should be considered part of the strategy for dealing with the problem of global warming.

References

Baum, C. F., Schaffer, M. E., & Stillman, S. (2003). Instrumental variables and GMM: Estimation and testing. The Stata Journal, 3(1), 1–31.

Boarnet, M. G. (2011). A broader context for land use and travel behavior, and a research agenda. Journal of the American Planning Association, 7(3), 197–213.

Boarnet, M. G., & Wang, X. (2019). Urban spatial structure and the potential for vehicle miles traveled reduction: The effects of accessibility to jobs within and beyond employment sub-centers. The Annals of Regional Science, 62(2), 381–404.

Brownstone, D., (2008). Key relationships between the built environment and VMT. Paper prepared for the Committee on the Relationships among Development Patterns, Vehicle Miles Traveled, and Energy Consumption, Transportation Research Board and the Division on Engineering and Physical Sciences. Irvine, CA: Department of Economics, University of California, Irvine.

Cambridge Systematics, Inc., & Kittelson and Associates. (2014). Source book calculations documentation. Tallahassee, FL: Florida DOT.

Cao, X., Mokhtarian, P. L., & Handy, S. L. (2009). Examining the impacts of residential self-selection on travel behavior: A focus on empirical findings. Transport Reviews, 29(3), 359–395. doi: 10.1080/01441640802539195

Cervero, R., & Murakami, J. (2010). Effects of built environments on vehicle miles traveled: Evidence from 370 US urbanized areas. Environment and Planning A, 42, 400–418.

Choo, S., Mokhtarian, P. L., & Salomon, I. (2005). Does telecommuting reduce vehicle-miles traveled? An aggregate time series analysis for the U.S. Transportation, 32, 37–64.

Clifton, K. J. (2017). Getting from here to there: Comment on “Does compact development make people drive less?” Journal of the American Planning Association, 83(2), 148–151. doi: 10.1080/01944363.2017.1290494

Clifton, K. J., & Handy, S. L. (2001a). Qualitative methods in travel behavior research. Paper presented at the International Conference on Transport Survey Quality and Innovation, August 5–10, Kruger National Park, South Africa.

Clifton, K. J., & Handy, S. L. (2001b). Local shopping as a strategy for reducing automobile travel. Transportation, 28(4), 317–346.

Diao, M., & Ferreira, J. Jr. (2014). Vehicle miles traveled and the built environment: Evidence from vehicle safety inspection data. Environment and Planning A, 46, 2991–3009.

Dill, J., McNeil, N., & Howland, S. (2019). Effects of peer-to-peer carsharing on vehicle owners’ travel behavior. Transportation Research Part C: Emerging Technologies, 101(April), 70–78.

Downs, A. (1962). The law of peak-hour expressway congestion. Traffic Quarterly, 16, 393–409.

Ewing, R., Bartholomew, K., Winkelman, S., Walters, J., & Chen, D. (2007). Growing cooler: The evidence on urban development and climate change. Washington, DC: Urban Land Institute.

Ewing, R., & Cervero, R. (2017). Does compact development make people drive less? Journal of the American Planning Association, 83(1), 7–18.

Ewing, R., & Cervero, R. (2010). Travel and the built environment: A meta-analysis. Journal of the American Planning Association, 76, 265–294.

Gimenez-Nadal, J. I., & Molina, J. A. (2016). Commuting time and household responsibilities: Evidence using Propensity Score Matching. Journal of Regional Science, 56(2), 332–359.

Handy, S., Cao, X., & Mokhtarian, P. (2005): Correlation or causality between the built environment and travel behavior? Evidence from Northern California. Transportation Research D, 10(6), 427–444.

Handy, S. (2017). Thoughts on the meaning of Mark Stevens’s meta-analysis. Journal of the American Planning Association, 83(1), 26–28.

Henao, A., & Marshall, W. E. (2019). The impact of ride-hailing on vehicle miles traveled. Transportation, 46(6), 2173–2194.

Ihlanfeldt, K. R. (2004). Exclusionary land-use regulations within suburban communities: A review of the evidence and policy prescriptions. Urban Studies, 41, 261–283.

Karagiannis, E., & Kovacevic, M. (2000). A method to calculate the jackknife variance estimator for the GINI coefficient. Oxford Bulletin of Economics and Statistics, 62, 119–122.

Krizek, K. (2003). Residential relocation and changes in urban travel: Does neighborhood-scale urban form matter? Journal of the American Planning Association, 69(3), 265–281.

Lindsey, M., Schofer, J. L., Durango-Cohen, P., & Gray, K. A. (2011). The effect of residential location on vehicle miles of travel, energy consumption and greenhouse gas emissions: Chicago case study. Transportation Research Part D, 16, 1–9.

McMullen, B. S., & Eckstein, N. (2012). Relationship between vehicle miles traveled and economic activity. Transportation Research Record: Journal of the Transportation Research Board, 2297, 21–28.

Miller E. J., & Ibrahim A. (1998). Urban form and vehicular travel: Some empirical findings. Transportation Research Record: Journal of the Transportation Research Board, 1617, 18–27.

Mills, E. S. (1979). Economic analysis of urban land-use controls. In P. M. Mieszkowski & M. R. Straszheim (Eds.), Current issues in urban economics (pp. 511–541). Baltimore, MD: John Hopkins University Press.

Næss, P. (2019). Meta-analyses of built environment effects on travel: No new platinum standard. Journal of Planning Education and Research. doi: 10.1177/0739456X19856425

Næss, P. (2015). Built environment, causality and travel. Transport Review, 35(3), 275–291.

Noland, R. B. (2001). Relationships between highway capacity and induced vehicle travel. Transportation Research Part A, 35, 47–72.

Rosenthal, S. S., & Strange, W. C. (2006). The micro-empirics of agglomeration economies. In R. J. Arnott, & D. P. McMillen (Eds.), A companion to urban economics (pp. 7–23). Hoboken, NJ: Blackwell Publishing.

Salon, D. (2014). Quantifying the effect of local government actions on VMT, Final Report. Prepared for the California Air Resources Board and the California Environmental Protection Agency. Davis, CA: Institute of Transportation Studies, University of California.

Sanderson, E. & Windmeijer, F. (2016). A weak instrument F-test in linear IV models with multiple endogenous variables. Journal of Econometrics, 190(2), 212–221. Retrieved from https://www.sciencedirect.com/science/article/pii/S0304407615001736.

Small, K., & Van Dender, K. (2005, September). The effect of improved fuel economy on vehicle miles traveled: Estimating the rebound effect using U.S. state data, 1966-2001. Berkeley, CA: UC Energy Institute, University of California, Berkeley.

Stevens, M. R. (2017a). Does compact development make people drive less? Journal of the American Planning Association, 83(1), 7–18.

Stevens, M. R. (2017b). Response to commentaries on “Does compact development make people drive less?”Journal of the American Planning Association, 83(2), 151–158.

Stock, J. H., & Yogo, M. (2005). Testing for weak instruments in linear IV regression. In D. W. K. Andrews & J. H. Stock (Eds.), Identification and inference for econometric models: Essays in honor of Thomas Rothenberg (pp. 80–108). Cambridge, UK: Cambridge University Press.

Teng, H., Qi, Y., & Martinelli, D. R. (2008). Parking difficulty and parking information system technologies and costs. Journal of Advanced Transportation, 42(2), 151–178. doi: 10.1002/atr.5670420204

Transportation Research Board. (2009). Special Report 298: Driving and the built environment: The effects of compact development on motorized travel, energy use, and CO2 emissions. Washington, DC: National Research Council.

United States Department of Transportation, Bureau of Transportation Statistics. (2019). Motor vehicle fuel consumption and travel. Retrieved from https://www.bts.gov/content/motor-vehicle-fuel-consumption-and-travel

United States Environmental Protection Agency. (2019). Estimating on-road greenhouse gas emissions. Retrieved from https://www.epa.gov/state-and-local-transportation/estimating-road-greenhouse-gas-emissions

van de Coevering, P., Maat, K., & van Wee, B. (2015). Multi-period research designs for identifying causal effects of built environment characteristics on travel behavior. Transport Reviews, 35(4), 512–532. doi: 10.1080/01441647.2015.1025455

Wolday, F., Cao, J., & Næss, P. (2018). Examining factors that keep residents with high transit preference away from transit-rich zones and associated behavior outcomes. Journal of Transport Geography, 66(January), 224–234.

Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.

Yang J. (2008). Policy implications of excess commuting: Examining the impacts of changes in US metropolitan spatial structure. Urban Studies, 45, 391–405.

Published

2020-01-28

How to Cite

Ihlanfeldt, K. (2020). Vehicle miles traveled and the built environment: New evidence from panel data. Journal of Transport and Land Use, 13(1), 23-48. https://doi.org/10.5198/jtlu.2020.1647

Issue

Section

Articles