PosterPDF Available

Commuting Sustainably: Do Smart Growth Policies Affect Transportation?



One of the goals of urban planning ’smart growth’ policies is providing a variety of transportation options and promoting the use of carpooling, public transportation, bicycling, and walking, all of which are considered more sustainable than driving alone. This paper examines the relationship between sustainable transportation and the presence of state­-level smart growth policies using a difference­-in-­differences analysis with data from the U.S. Census Bureau’s American Community Survey. Given that Maryland enacted state-­level smart growth policies in 2009 and 2010, this paper compares the Baltimore metropolitan area to the Denver metropolitan area, which has no state-­level smart growth policies but some demographic similarities to the Baltimore metropolitan area. This analysis finds a 2.2 percentage point increase in sustainable transportation use in Baltimore attributable to the smart growth policies in Maryland that were passed in 2009 and 2010.
Riordan Frost, PhD Candidate
Department of Public Administration & Policy, American University
Commuting Sustainably
The role of state smart growth policies in transportation
2013. “2008-2012 American Community Survey 5-Year Estimates — Tables S1903, S1501, B01003.” US Census Bureau.
2013. "About Smart Growth." US Environmental Protection Agency.
2013. “Fast Facts: U.S. Transportation Sector Greenhouse Gas Emissions 1990-2011.” US Environmental Protection Agency.
2014. "2013 American Community Survey — Table S0801." US Census Bureau.
2014. "Smart Growth Planning Topics." Maryland Department of Planning.
2015. "What is "smart growth?" Smart Growth America.
Anthony, Jerry. 2004. "Do State Growth Management Regulations Reduce Sprawl?" Urban Affairs Review 39 (3): 376-397.
DeLoach, Stephen B, and Thomas K Tiemann. 2012. "Not driving alone? American commuting in the twenty-first century." Transportation 39 (3): 521-537. doi: 10.1007/s11116-011-9374-5.
Ferguson, Erik. 1997. "The rise and fall of the American carpool: 1970–1990." Transportation 24 (4): 349-376. doi: 10.1023/A:1004928012320.
Glaeser, Edward L., Matthew E. Kahn, and Jordan Rappaport. 2008. "Why do the poor live in cities? The role of public transportation." Journal of Urban Economics 63 (1): 1-24. doi: 10.1016/j.jue.2006.12.004.
Ingram, Gregory, Armando Carbonell, Yu-Hung Hong, and Anthony Flint, eds. 2009. Smart Growth Policies: an evaluation of programs and outcomes. Cambridge, MA: Lincoln Institute of Land Policy.
Jun, Myung-Jin. 2008. "Are Portland's Smart Growth Policies Related to Reduced Automobile Dependence?" Journal of Planning Education and Research 28 (1): 100-107. doi: 10.1177/0739456x08319240.
Kahn, Matthew E., and Eric A. Morris. 2009. "Walking the Walk: The Association Between Community Environmentalism and Green Travel Behavior." Journal of the American Planning Association 75 (4): 389-405.
Literature Review
What affects how we get around?
The cost of each mode: driving alone decreases when fuel costs rise, and sustainable modes all decrease
when fuel costs fall (Ferguson 1997; DeLoach & Tiemann 2012)
Income: low-income commuters carpool and take public transportation more, due to the lower user cost
(Ferguson 1997; Glaeser et al. 2008)
Environmentalism: environmental views and sustainable mode choices are positively correlated on the
community-level (Kahn & Morris 2009)
What is the role of state smart growth policies?
State policies succeed in the areas states prioritize (Ingram et al. 2009)
Maryland prioritizes environmental protection, Oregon prioritizes transportation, New Jersey
prioritizes affordable housing
The Oregon planning law establishing the Portland urban growth boundary was not found to affect rates
of driving alone (Jun 2008)
States with growth management policies appear to experience lower density declines (Anthony 2004)
Research Question
Do state smart growth policies positively affect sustainable transportation rates?
Sustainable transportation: public transit, carpooling, bicycling, and walking
Empirical Approach
Using difference-in-differences analysis to compare sustainable transportation rates in Colorado and
Maryland before and several years after the 2009 and 2010 Maryland smart growth policies
This method compensates for non-random treatment and attempts to determine causal effects
To ensure there is no bias from pre-existing trends, event study analysis is conducted (see Fig. 4)
Two approaches: differencing and logistic regression
(Sustainable transportation)it = ƛ(β0 + β1(sg)ij + β2(year)jt + β3(yearjt*sgij) + β4(education)ijt + β5(ln(income)ijt)
+ β6(gender)ijt + β7(race)ijt + β8(rent/own)ijt)
Driving alone is the most widely used, but least efficient mode of personal transportation
Driving contributes to congestion, local air pollution, and infrastructure burden — and
greenhouse gas emissions (see Fig. 1 & 2)
Alternative’ modes are encouraged by government and business programs for their societal
benefits and company benefits (e.g. less parking demand)
Here, these modes — public transit, walking, bicycling, and carpooling — are combined
into a new variable: ‘sustainable transportation
There are only 11 states with comprehensive smart growth policies
What is smart growth?
“Building urban, suburban and rural communities with
housing and transportation choices near jobs, shops and
schools” (Smart Growth America 2015)
A bundle of principles including mixing land uses, creating a
range of housing opportunities, providing a variety of
transportation choices, and preserving open space (EPA 2014)
Finding: there is approximately a 2 percentage point difference between the sustainable transportation rates in
Baltimore and Denver, attributable to the state smart growth policies of Maryland
A two percentage point difference is a 10% increase in current sustainable transportation rates
This change results in substantial GHG mitigation (see Fig. 1 & 2)
Limitations: more than one policy passed in Maryland; no uniform policy across states for comparison; !
no non-commuting data available
Next steps: look at other metropolitan areas; examine other smart growth goals (e.g. mixed uses, affordable
housing, and open space); use synthetic controls instead of difference-in-differences
Sustainable Transportation
Baltimore MSA Denver MSA
Figure 2: Cars and light-duty trucks’ share of
transportation GHGs in 2011 (Source: EPA 2013)
Medium and
Heavy-Duty Trucks
Passenger Cars &
Light-Duty Trucks
Ships & Boats
Figure 1: Transportations share of US GHGs
in 2011 (Source: EPA 2013)
Figure 3: 2013 commuting by mode in the US (excluding work-at-home and misc.)
(Source: US Census Bureau 2014; own work)
Drive alone
Public transit
How do we get to work?
Table 2: Difference-in-differences
Transportation %
Pre (2008)
Post (2013)
Denver (control)
Baltimore (treatment)
American Community Survey data from the Integrated Public Use Microdata Series (IPUMS-USA)
Denver and Baltimore metropolitan areas chosen due to similar demographics and the fact that
Maryland has state smart growth policies and Colorado does not
Metropolitan areas chosen to include the transportation behaviors of urban and suburban residents
Pooled cross-sectional sample: N = 47,000
Baltimore-Towson, MD
Denver-Aurora-Broomfield, CO
Population (2012)
Median HH Income (2012)
% College Educated (2012)
Table 1: Similarities between Baltimore and Denver MSAs (Source: Census Bureau 2013)
Table 3: Logistic regression DD - average partial effects
*** p<0.01, ** p<0.05, * p<0.1
Smart growth
Year * smart growth
Education (ref: college)
Gender (ref: female)
Race (ref: white)
Rent/own (ref: renter)
ResearchGate has not been able to resolve any citations for this publication.
Full-text available
This paper investigates recent commuting trends by American workers. Unlike most studies of commuting that rely on data from the American Community Survey this study utilizes the American Time Use Survey to detail the complex commuting patterns of modern-day workers. Changes in the price of gasoline in recent years suggest that the incidence of “driving alone” should be on the decline. Indeed, results show that the sensitivity of modal commuting with respect to changes in gasoline prices appears to be relatively large. We estimate the gasoline-price elasticity of driving alone to be 0.057 and the gasoline-price elasticity of carpooling to be 0.502. Additional factors also affect commuting, including socio-economic characteristics and social desires. However, it is changes in gasoline prices that appear to account for nearly all of the recent variation in the mode chosen for commuting.
Full-text available
Problem: Reducing gasoline consumption could sharply curtail greenhouse gas emissions. Ongoing research seeks to document factors associated with green travel behavior, like walking and transit use.Purpose: We seek to determine whether green beliefs and values are associated with green travel behavior. We measure whether residents of communities with environmentalist attributes drive less, consume less gasoline, and are more likely to commute by private vehicle. We explore several channels through which green beliefs and values may affect travel behavior and vice versa.Methods: We drew our demographic, transportation, and built environment data from the 2000 Census of Population and Housing including the Public Use Microdata Sample and the 2001 National Household Travel Survey, and constructed our indicators of green ideology using voting records, political party membership, and data on hybrid auto ownership. We estimated ordinary least squares regression and linear probability models using both individual households and small areas as units of analysis.Results and conclusions: We find green ideology is associated with green travel behavior. People with green values are more likely than others to be located in communities with high population densities and proximity to city centers and rail transit stations, which are attributes conducive to environmentally friendly travel. We also find that residents of green communities engage in more sustainable travel than residents of other communities, even controlling for demographics and the effects of the built environment. Green ideology may cause green travel behavior because greens derive utility from conservation or because greens locate in, or create, areas with characteristics that promote sustainable travel. We also discuss the possibility that green travel behavior may cause green beliefs.Takeaway for practice: If greens self-select into dense, central, and transit-friendly areas, the demand for these characteristics may rise if green consciousness does. Alternatively, if these characteristics cause green consciousness, their promotion promises to increase green behavior. The implications of our finding that residents of green communities engage in more sustainable travel patterns than others depends on the causal mechanism at work. If greens conserve because they derive utility from it, then environmental education and persuasion may bring about more sustainable travel. Alternatively, if green travel behavior causes green beliefs, it is possible that attracting more travelers to alternate modes and reducing vehicle miles traveled may increase environmental consciousness, which may in turn promote other types of pro-environment behavior.Research support: None.
Full-text available
Recent declines in carpooling among American commuters are analyzed using data derived from the US Census of Population, the Nationwide Personal Transportation Study, and the American Home Survey. The most important factors associated with recent declines in carpooling to and from work in the US include increasing household vehicle availability, falling real marginal fuel costs, and higher average educational attainments among commuters. Age, sex, family income, household lifecycle characteristics, urban form, racial diversity and relative poverty appear to have had smaller effects on observed changes in carpooling for the work trip.
This study evaluates how successful smart growth policies in Portland, best known for its smart growth policies such as the urban growth boundary, extensive public transit service, and transit-oriented developments along the transit corridors, are in achieving one of their policy objectives, a reduction of automobile dependence. Empirical evidence reveals that more diversified land use in neighborhoods, more extensive provision of public transit service, and decreasing accessibility to freeway interchanges were associated with fewer choices of driving alone, while making settlements compact via the urban growth boundary and transit-oriented developments has no clear relationship with reducing the choice to drive alone. Empirical analyses also suggest that provision of public transit service and mixed land use implemented at residential zones (origins) were more effective in reducing automobile dependence than those implemented at places of work (destinations).
Thirteen states in the United States have adopted state growth management legislation that aims to preserve environmentally sensitive areas, improve the quality of urban areas, and reduce urban sprawl. Although there is a considerable amount of literature describing such policies, there is very little that examines the effectiveness of such policies. The author researched the efficacy of state growth management laws in controlling urban sprawl by examining the change in urban densities in 49 states over a 15-year period. He found that growth-managed states generally expe- rienced a lesser density decline than states without growth management. However, regression analysis revealed that state growth management programs did not have a statistically significant effect in checking sprawl. The author concludes with several suggestions for modifying state reg- ulations to curb sprawl more effectively.
More than 19 percent of people in American central cities are poor. In suburbs, just 7.5 percent of people live in poverty. The income elasticity of demand for land is too low for urban poverty to come from wealthy individuals' wanting to live where land is cheap (the traditional explanation of urban poverty). A significant income elasticity for land exists only because the rich eschew apartment living, and that elasticity is still too low to explain the poor's urbanization. The urbanization of poverty comes mainly from better access to public transportation in central cities.
Smart Growth Policies: an evaluation of programs and outcomes
  • Gregory Ingram
  • Armando Carbonell
Ingram, Gregory, Armando Carbonell, Yu-Hung Hong, and Anthony Flint, eds. 2009. Smart Growth Policies: an evaluation of programs and outcomes. Cambridge, MA: Lincoln Institute of Land Policy.
Fast Facts: U.S. Transportation Sector Greenhouse Gas Emissions
2013. "2008-2012 American Community Survey 5-Year Estimates -Tables S1903, S1501, B01003." US Census Bureau. 2013. "About Smart Growth." US Environmental Protection Agency. 2013. "Fast Facts: U.S. Transportation Sector Greenhouse Gas Emissions 1990-2011." US Environmental Protection Agency. 2014. "2013 American Community Survey -Table S0801." US Census Bureau. 2014. "Smart Growth Planning Topics." Maryland Department of Planning. 2015. "What is "smart growth?" Smart Growth America.