The Annals of Regional Science

, Volume 62, Issue 2, pp 381–404 | Cite as

Urban spatial structure and the potential for vehicle miles traveled reduction: the effects of accessibility to jobs within and beyond employment sub-centers

  • Marlon G. Boarnet
  • Xize WangEmail author
Original Paper


This research examines the relationship between urban polycentric spatial structure and driving. We identified 46 employment sub-centers in the Los Angeles Combined Statistical Area and calculated access to jobs that are within and beyond these sub-centers. To address potential endogeneity problems, we use access to historically important places and transportation infrastructure in the early twentieth century as instrumental variables for job accessibility indices. Our Two-stage Tobit models show that access to jobs is negatively associated with household vehicle miles traveled in this region. Among various accessibility measures, access to jobs outside sub-centers has the largest elasticity (− 0.155). We examine the location of places in the top quintile of access to non-centered jobs and find that those locations are often inner ring suburban developments, near the core of the urban area and not far from sub-centers, suggesting that strategies of infill development that fill in the gaps between sub-centers, rather than focusing on already accessible downtowns and large sub-centers, may be the best land use approach to reduce VMT.

JEL Classification

C34 R14 R42 



This study was funded by California Department of Transportation through the METRANS Transportation Center in task order 005-A01. The authors thank the Editor and the anonymous referees for their helpful comments.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Baum-Snow N (2007) Did highways cause suburbanization? Q J Econ 122:775–805CrossRefGoogle Scholar
  2. Boarnet MG (2011) A broader context for land use and travel behavior, and a research agenda. J Am Plan Assoc 77:197–213CrossRefGoogle Scholar
  3. Boarnet MG, Sarmiento S (1998) Can land-use policy really affects travel behaviour? A study of the link between non-work travel and land-use characteristics. Urban Stud 35:1155–1169CrossRefGoogle Scholar
  4. Boarnet MG, Houston D, Ferguson G, Spears S (2011) Land use and vehicle miles of travel in the climate change debate: getting smarter than your average bear. In: Hong Y-H, Ingram G (eds) Climate change and land policies. Lincoln Institute of Land Policy, Cambridge, pp 151–187Google Scholar
  5. Boarnet MG, Wang X, Houston D (2017) Can new light rail reduce personal vehicle carbon emissions? A before-after, experimental-control evaluation in Los Angeles. J Reg Sci 57:523–539CrossRefGoogle Scholar
  6. Brooks L, Lutz BF (2014) Vestiges of transit: urban persistence at a micro sale, working paper.
  7. Brownstone D (2008) Key relationships between the built environment and VMT. Department of Economics, University of California, IrvineGoogle Scholar
  8. Cao X, Mokhtarian PL, Handy SL (2009) Examining the impacts of residential self-selection on travel behaviour: a focus on empirical findings. Transp Rev 29:359–395CrossRefGoogle Scholar
  9. Cervero R, Duncan M (2006) Which reduces vehicle travel more: jobs-housing balance or retail-housing mixing? J Am Plan Assoc 72:475–490. CrossRefGoogle Scholar
  10. City of Los Angeles Transportation Engineering Board (1939) A transit program for the Los Angeles Metropolitan AreaGoogle Scholar
  11. Duranton G, Puga D (2004) Micro-foundations of urban agglomeration economies. Handb Reg Urban Econ 4:2063–2117CrossRefGoogle Scholar
  12. Duranton G, Turner MA (2018) Urban form and driving: evidence from US cities. J Urban Econ 108:170–191Google Scholar
  13. Electric Railway Historical Association of Southern California (2017) Accessed 25 Nov 2017
  14. Ewing R, Cervero R (2010) Travel and the built environment—a meta-analysis. J Am Plan Assoc 76:265–294CrossRefGoogle Scholar
  15. Giuliano G, Small KA (1991) Subcenters in the Los Angeles region. Reg Sci Urban Econ 21:163–182. CrossRefGoogle Scholar
  16. Giuliano G, Redfearn C, Agarwal A, Li C, Zhuang D (2007) Employment concentrations in Los Angeles, 1980–2000. Environ Plan A 39:2935–2957CrossRefGoogle Scholar
  17. Giuliano G, Hou Y, Kang S, Shin E-J (2015) Accessibility location, and employment center growth. METRANS Transportation Center, Los AngelesGoogle Scholar
  18. Glaeser EL, Kahn ME (2001) Decentralized employment and the transformation of the American city. National Bureau of Economic ResearchGoogle Scholar
  19. Greenstone M, Hornbeck R, Moretti E (2010) Identifying agglomeration spillovers: evidence from winners and losers of large plant openings. J Polit Econ 118:536–598CrossRefGoogle Scholar
  20. Handy S, Cao X, Mokhtarian PL (2006) Self-selection in the relationship between the built environment and walking: empirical evidence from Northern California. J Am Plan Assoc 72:55–74CrossRefGoogle Scholar
  21. Haynes KE, Fotheringham AS (1984) Gravity and spatial interaction models. SAGE Publications, Thousand OaksGoogle Scholar
  22. Intergovernmental Panel on Climate Change (2013) Summary for policy makers. In: Stocker TF et al. (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change, Cambridge University Press, CambridgeGoogle Scholar
  23. McDonald JF, McMillen DP (1990) Employment subcenters and land values in a polycentric urban area: the case of Chicago. Environ Plan A 22:1561–1574CrossRefGoogle Scholar
  24. McMillen DP (2001) Nonparametric employment subcenter identification. J Urban Econ 50:448–473. CrossRefGoogle Scholar
  25. Nelson LJ (2017) What will Los Angeles transportation be like when the Olympics arrive in 2028?. Los Angeles, CAGoogle Scholar
  26. Oster E (2017) Unobservable selection and coefficient stability: theory and evidence. J Bus Econ Stat.
  27. Puga D (2010) The magnitude and causes of agglomeration economies. J Reg Sci 50:203–219CrossRefGoogle Scholar
  28. Redfearn CL (2007) The topography of metropolitan employment: identifying centers of employment in a polycentric urban area. J Urban Econ 61:519–541CrossRefGoogle Scholar
  29. Redfearn CL (2009) Persistence in urban form: the long-run durability of employment centers in metropolitan areas. Reg Sci Urban Econ 39:224–232CrossRefGoogle Scholar
  30. Salon D, Boarnet MG, Handy S, Spears S, Tal G (2012) How do local actions affect VMT? A critical review of the empirical evidence. Transp Res Part D Transp Environ 17:495–508. CrossRefGoogle Scholar
  31. Southern California Association of Governments (2016) The 2016–2040 regional transportation plan/sustainable communities strategy, Los Angeles, CAGoogle Scholar
  32. Travel and Hotel Bureau (1906) Map of the city of Los Angeles: showing railway systems. Accessed 4 Feb 2018
  33. Walker J (2006) Images of rail: Pacific electric red cars charleston. ArcadiaPub, ColumbiaGoogle Scholar
  34. Walls and Associates (2008) National establishment time-series (NETS) database: database description, Oakland, CAGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Urban Planning and Spatial Analysis, Sol Price School of Public PolicyUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Institute of Urban and Regional DevelopmentUniversity of California, BerkeleyBerkeleyUSA

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