Credibly identifying how the built environment shapes behaviour is empirically challenging, because people select residential locations based on differing constraints and preferences for site amenities. Our study overcomes these research barriers by leveraging San Francisco’s affordable housing lotteries, which randomly allow specific households to move to specific residences. Using administrative data, we demonstrate that lottery-winning households’ baseline preferences are uncorrelated with their allotted residential features such as public transportation accessibility, parking availability and bicycle infrastructure – meaning that neighbourhood attributes and a building’s parking supply are effectively assigned at random. Surveying the households, we find that these attributes significantly affect transportation mode choices. Most notably, we show that essentially random variation in on-site parking availability greatly changes households’ car ownership decisions and driving frequency, with substitution away from public transport. In contrast, we find that parking availability does not affect employment or job mobility. Overall, the evidence from our study robustly supports that local features of the built environment are important determinants of transportation behaviour.
AdairCEKoppBDistasioJ, et al. (2016) Housing quality in a randomized controlled trial of Housing First for homeless individuals with mental illness: Correlates and associations with outcomes. Journal of Urban Health93(4): 682–697.
BarnhardtSFieldEPandeR (2017) Moving to opportunity or isolation? Network effects of a randomized housing lottery in urban India. American Economic Journal: Applied Economics9(1): 1–32.
4.
Barrington-LeighCMillard-BallA (2020) Global trends toward urban street-network sprawl. Proceedings of the National Academy of Sciences117(4): 1941–1950.
5.
BhatCRGuoJY (2007) A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels. Transportation Research Part B: Methodological41(5): 506–526.
6.
BlumenbergEOngP (2001) Cars, buses, and jobs: Welfare participants and employment access in Los Angeles. Transportation Research Record: Journal of the Transportation Research Board1756(1): 22–31.
7.
BlumenbergEPierceG (2014) A driving factor in mobility? Transportation’s role in connecting subsidized housing and employment outcomes in the Moving to Opportunity (MTO) program. Journal of the American Planning Association80(1): 52–66.
8.
BowenDJQuintilianiLMBhosrekarSG, et al. (2018) Changing the housing environment to reduce obesity in public housing residents: A cluster randomized trial. BMC Public Health18(1): 883.
9.
CaoJ (2014) Residential self-selection in the relationships between the built environment and travel behavior: Introduction to the special issue. Journal of Transport and Land Use7(3): 1–3.
10.
CaoXChatmanD (2016) How will smart growth land-use policies affect travel? A theoretical discussion on the importance of residential sorting. Environment and Planning B: Planning and Design43(1): 58–73.
11.
CaoXJMokhtarianPLHandySL (2009) Examining the impacts of residential self-selection on travel behaviour: A focus on empirical findings. Transport Reviews29(3): 359–395.
12.
ChatmanDG (2014) Estimating the effect of land use and transportation planning on travel patterns: Three problems in controlling for residential self-selection. Journal of Transport and Land Use7(3): 47–56.
13.
ChettyRHendrenNKatzLF (2016) The effects of exposure to better neighborhoods on children: New evidence from the Moving to Opportunity experiment. The American Economic Review106(4): 855–902.
14.
ChristensenPSarmiento-BarbieriITimminsC (2020) Housing discrimination and pollution exposures in the United States. NBER Working Paper No. 26805. Cambridge, MA: National Bureau of Economic Research.
15.
EwingRCerveroR (2010) Travel and the built environment. Journal of the American Planning Association76(3): 265–294.
16.
FeinsJDShroderMD (2005) Moving to Opportunity: The demonstration’s design and its effects on mobility. Urban Studies42(8): 1275–1299.
17.
FranklinS (2019) The demand for government housing: Evidence from lotteries for 200,000 homes in Ethiopia. Working Paper, London School of Economics.
18.
GiulianoGNarayanD (2003) Another look at travel patterns and urban form: The US and Great Britain. Urban Studies40(11): 2295–2312.
19.
GlaeserEGyourkoJ (2018) The economic implications of housing supply. Journal of Economic Perspectives32(1): 3–30.
20.
GlaeserELKahnMERappaportJ (2008) Why do the poor live in cities? The role of public transportation. Journal of Urban Economics63(1): 1–24.
21.
GrahamBS (2018) Identifying and estimating neighborhood effects. Journal of Economic Literature56(2): 450–500.
22.
GrengsJ (2010) Job accessibility and the modal mismatch in Detroit. Journal of Transport Geography18(1): 42–54.
23.
GuoZ (2013) Home parking convenience, household car usage, and implications to residential parking policies. Transport Policy29: 97–106.
24.
HallCMRamY (2018) Walk score® and its potential contribution to the study of active transport and walkability: A critical and systematic review. Transportation Research Part D: Transport and Environment61: 310–324.
25.
HandyS (2018) Enough with the “D’s” already – Let’s get back to “A”. Transfers1: 1–3.
26.
KatzLFKlingJRLiebmanJB (2001) Moving to Opportunity in Boston: Early results of a randomized mobility experiment. The Quarterly Journal of Economics116(2): 607–654.
27.
KlingJRLiebmanJBKatzLF (2007) Experimental analysis of neighborhood effects. Econometrica75(1): 83–119.
28.
LeventhalTBrooks-GunnJ (2003) Moving to Opportunity: An experimental study of neighborhood effects on mental health. American Journal of Public Health93(9): 1576–1582.
29.
LevineJ (1998) Rethinking accessibility and jobs–housing balance. Journal of the American Planning Association64(2): 133–149.
30.
LevineJ (2005) Zoned Out. Regulation, Markets, and Choices in Transportation and Metropolitan Land Use. Washington, DC: RFF Press.
31.
LinTWangDGuanX (2017) The built environment, travel attitude, and travel behavior: Residential self-selection or residential determination?Journal of Transport Geography65: 111–122.
32.
LudwigJDuncanGJHirschfieldP (2001) Urban poverty and juvenile crime: Evidence from a randomized housing-mobility experiment. The Quarterly Journal of Economics116(2): 655–679.
33.
ManaughKEl-GeneidyA (2011) Validating walkability indices: How do different households respond to the walkability of their neighborhood?Transportation Research Part D: Transport and Environment16(4): 309–315.
34.
ManaughKEl-GeneidyA (2015) The importance of neighborhood type dissonance in understanding the effect of the built environment on travel behavior. Journal of Transport and Land Use8(2): 45–57.
35.
ManvilleM (2017) Bundled parking and vehicle ownership: Evidence from the American Housing Survey. Journal of Transport and Land Use10(1): 27–55.
36.
ManvilleMShoupD (2005) Parking, people, and cities. Journal of Urban Planning and Development131(4): 233–245.
37.
MarinescuIRathelotR (2018) Mismatch unemployment and the geography of job search. American Economic Journal: Macroeconomics10(3): 42–70.
38.
MokhtarianPLCaoX (2008) Examining the impacts of residential self-selection on travel behavior: A focus on methodologies. Transportation Research Part B: Methodological42(3): 204–228.
39.
NaessP (2014) Tempest in a teapot: The exaggerated problem of transport-related residential self-selection as a source of error in empirical studies. Journal of Transport and Land Use7(3): 57–79.
40.
NAHB (2019) Housing opportunity index. 3rd quarter, 2019. Technical report. Washington, DC: National Association of Home Builders.
41.
OsamaAAlbitarMSayedT, et al. (2020) Determining if walkability and bikeability indices reflect pedestrian and cyclist safety. Transportation Research Record: Journal of the Transportation Research Board2674(9): 767–775.
42.
PinjariARPendyalaRMBhatCR, et al. (2007) Modeling residential sorting effects to understand the impact of the built environment on commute mode choice. Transportation34: 557–573.
43.
SalonDBoarnetMGHandyS, et al. (2012) How do local actions affect VMT? A critical review of the empirical evidence. Transportation Research Part D: Transport and Environment17(7): 495–508.
44.
SampsonRJMorenoffJDGannon-RowleyT (2002) Assessing ‘neighborhood effects’: Social processes and new directions in research. Annual Review of Sociology28(1): 443–478.
45.
SanbonmatsuLLudwigJKatzLF, et al. (2011) Moving to Opportunity for fair housing demonstration program. Final impacts evaluation. Technical report. Washington, DC: Department of Housing and Urban Development.
46.
SanchezTW (1999) The connection between public transit and employment: The cases of Portland and Atlanta. Journal of the American Planning Association65(3): 284–296.
47.
SanchezTWShenQPengZ-R (2004) Transit mobility, jobs access and low-income labour participation in US metropolitan areas. Urban Studies41(7): 1313–1331.
48.
ShoupDC (2005) The High Cost of Free Parking. Washington, DC: Planners Press.
49.
StevensM (2017) Does compact development make people drive less?Journal of the American Planning Association83(1): 1–12.
50.
Van DijkW (2019) The socio-economic consequences of housing assistance. Working Paper, University of Chicago.
51.
Van WeeB (2009) Self-selection: A key to a better understanding of location choices, travel behaviour and transport externalities?Transport Reviews29(3): 279–292.
52.
WeinbergerR (2012) Death by a thousand curb-cuts: Evidence on the effect of minimum parking requirements on the choice to drive. Transport Policy20: 93–102.
53.
ZegrasPC (2010) The built environment and motor vehicle ownership and use: Evidence from Santiago de Chile. Urban Studies47(8): 1793–1817.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
