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Why Are Urban Travel Times So Stable?

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  • Alex Anas

Abstract

type="main"> Personal travel time in U.S. urban areas has been stable, clashing with the assertion that urban sprawl greatly lengthens travel. Average commute time rises by 7.7 percent with each cross-sectional doubling of Metropolitan Statistical Area (MSA) jobs. Using the RELU-TRAN structural computable general equilibrium model of the Chicago MSA, we simulate the equilibrium effects of a 24 percent population increase projected from 2000 to 2030 by the Chicago Metropolitan Agency for Planning. If no new road capacity is added, then congestion per mile increases. Although the urbanized land area increases by 19 percent, indicating sprawl, the vehicle miles traveled (VMT) per car-trip decreases by 1.31 percent and the VMT per car-trip to work decreases by 2.78 percent. Car travel time increases by only 6.25 percent and commuting time by only 4.54 percent, from 30.3 minutes in 2000 to 31.7 in 2030 or 3.4 seconds per year. We further explore the effects of new road capacity, gasoline prices, public transit speed, fuel economy gains, limits on suburban construction, and importantly, the cross-elasticity of public transit use with respect to car times. The availability of public transportation, economizing on nonwork travel, and land use adjustments that increase job-residence proximity keep times stable.

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  • Alex Anas, 2015. "Why Are Urban Travel Times So Stable?," Journal of Regional Science, Wiley Blackwell, vol. 55(2), pages 230-261, March.
    • Handle: RePEc:bla:jregsc:v:55:y:2015:i:2:p:230-261
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    File URL: http://hdl.handle.net/10.1111/jors.12142
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    2. Marc Barthelemy, 2016. "A global take on congestion in urban areas," Environment and Planning B, , vol. 43(5), pages 800-804, September.
    3. David Martín-Barroso & Juan A. Núñez-Serrano & Francisco J. Velázquez, 2015. "The Effect Of Accessibility On Productivity In Spanish Manufacturing Firms," Journal of Regional Science, Wiley Blackwell, vol. 55(5), pages 708-735, November.
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    5. Martín-Barroso, David & Núñez-Serrano, Juan A. & Turrión, Jaime & Velázquez, Francisco J., 2022. "Are workers' commutes sensitive to changes in the labour market situation?," Journal of Transport Geography, Elsevier, vol. 101(C).
    6. Robson, Edward N. & Wijayaratna, Kasun P. & Dixit, Vinayak V., 2018. "A review of computable general equilibrium models for transport and their applications in appraisal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 31-53.
    7. Jinwon Kim & Jucheol Moon, 2022. "Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data," Working Papers 2201, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    8. Anas, Alex, 2024. "“Downs's Law” under the lens of theory: Roads lower congestion and increase distance traveled," Journal of Urban Economics, Elsevier, vol. 139(C).
    9. Larson, William & Yezer, Anthony & Zhao, Weihua, 2022. "Urban planning policies and the cost of living in large cities," Regional Science and Urban Economics, Elsevier, vol. 96(C).
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