Commuting, Transportation Spending and Urban Sprawl
Roy L. Coxon
April 29, 2015
Dr. Hatten

My overall topic for my research project is Commuting, Transportation Spending and Urban Sprawl. The purpose of this project is to design a research study to determine and clarify what effect urban sprawl has on private-vehicle commuting costs and household expenditures. Let us first look at the definition of sprawl. There is no universally accepted definition although there have numerous attempts to institute a unified definition of this multifaceted concept. Sprawl is defined as low-density development with residential, shopping and office areas that are isolated, a lack of thriving centers and limited choices in travel routes (Ewing, 2002). Sprawl is ever-present and its effects are impacting the quality of life in every region of America, in our large cities and small towns.
The contextual factors (historical) of sprawl go back to 1937 when Earle Draper first created the term “sprawl” in 1937 (Nechyba, 2004). To document the presence of urban sprawl and urban population levels is to look within urban areas at the evolving relationship between suburbs and central cities. The conversion of a primarily rural population in 1790 became increasingly centered in cities over the course of the 19th and early 20th centuries. Only about 5 percent of the U.S. population lived in urban areas in 1790 as that figure tripled by 1850 and surpassed 50 percent by 1920. The 2000 Census Bureau showed that 79 percent of all Americans lived in areas designated at “urban” (Nechyba, 2004). The 19th and early part of the 20th century can be characterized by the fact that the Industrial Revolution converted an agrarian economy into one that became increasingly dominated by cities. The remainder of the 20th century witnessed the accelerated growth of suburbs within urban areas. The 1950 Census began documenting data about the rise of suburbs when the Census Bureau first defined “urbanized areas” to include only those areas that truly represent built-up urban or suburban blocks (as opposed to “metropolitan statistical areas) and divided populations within these areas into suburban and central city populations (Nechyba, 2004).
The car is certainly the most important transportation technology to impact the city over the last two centuries. Since 1950, car ownership had continued to expand. In 1950, the majority of households owned one automobile (52 percent), but only 7 percent owned two cars or more (Glaeser, 2004). In a study of households in 2008 with at least one vehicle, Experian Automotive found that households with three or more cars are the single largest group among American car owners. The United States is still very much in love with the automobile with a national average of 2.28 vehicles per household (Auto Spies, 2008).
There is also the failure to account for the social costs of freeway congestion (Brueckner, 2000). This cost is generated when the commuter drives on congested roadways to work. This cost is due to the extra congestion caused by the commuter’s presence on the road. Slight increases in traffic on a crowded roadway can lead to a substantial drop in traffic speed. Raising the time cost of travel and cost of gasoline for all commuters is caused by this lower speed which prolongs the trip. Thus, on congested roads, the true social cost of commuting for an individual includes the costs imposed on other commuters through that extra congestion.
Thus, my research proposal question is: how are household expenditures affected by urban sprawl in the commuting process? The potential significance and hypothesis of my research is that there is justification indicating a positive relationship between urban sprawl and commuting (Zolnik, 2012). When looked over a period of time, the data show a trend of increasing commuting expenses to the American household. This is relevant to the target population of the American family as commuting costs are highest in sprawling places than less sprawling; within the family budget, this expense looms large. Transportation costs do not get the same level of attention because for most Americans transportation is an expense second only to housing. Thus, I will be addressing the following questions which I feel are important. My first question is: why is private-vehicle commuting more costly in sprawling areas? I claim that private-vehicle commuting is more costly in sprawling is that strict segregation of land uses is one of the characteristics of sprawl. Housing subdivisions are typically often separated by many miles – from shopping, offices, civic centers and schools – in these sprawling regions. This separation of uses is what requires every trip to be made by car, thus resulting in a “jobs-housing imbalance” in which workers cannot find housing close to their place of work (McCann, 2000). It is evident that people in more compact, connected metro areas have more transportation options based on the Sprawl Index and the Consumer Expenditure Survey. Transportation costs are lower in more compact areas is that these areas have a wider range of options for how to get around – nearly all of which cost less than driving or are even free than sprawling areas. My second question is: why do sprawl increases make driving a necessity? The reason as to why sprawl increases makes driving a necessity is that households have little choice but to own and operate a number of automobiles when there are greater distances between destinations and a lack of transportation choice. Evidence clearly shows that sprawl is necessitated by distance which means higher spending on gasoline and maintenance of vehicles (Newman, 1999). Also sprawl means more trips are made car because long distances often make automobiles the only practical way to travel. The third and final question is that while transportation and commuting expenses is a major expense for most American households, does the cost of getting around vary depending on where you live? I claim that cost of getting around does vary depending where you live as community expenditure patterns on different geographical scales were compared doing different analyses (McCann, 2000). The comparisons included the following: transportation expenses in U.S. metro areas to metro areas in other countries. Then we compared different U.S. metro areas to one another, thus became the core of the analysis. A final look was at selected U.S. metro areas and compared transportation expenses from neighborhood to neighborhood. Results were remarkable. Data collected by Peter Newman and Jeffrey Kenilworthy points out those residents of American metro areas spend more on transportation than their colleagues in Europe (Newman, 1999). Analyzing the most recent U.S. Bureau of Labor Statistics Consumer Expenditure Survey (Labor, U.D., 2008) of 28 major metro areas shows that households devote the highest portion of their household budget to transportation in Houston, Atlanta, Dallas-Fort Worth, and Miami. Checking the validity and most accurate way to compare regions, the share of total expenditures committed to transportation was used to rank the most expensive places for personal transportation (McCann, 2000). I will be using a quantitative study as the methodology in my experiment utilizing a specified instrument - the “sprawl index” as a quantitative measure for the design of my research (Ewing, 2002). A sprawl index is based on four factors that can be measured and analyzed. Sprawl is measured using 22 variables that represent different aspects of development patterns. In this experiment, sprawl is operationalized by combining many variables into a few factors representing residential density, land use mix, degree of centering, and street accessibility. This consolidation of variables is accomplished with principal component analysis. These four factors are then related to vehicle ownership, commute mode choice, commute time, vehicle miles traveled per capita, traffic delay per capita, traffic fatalities per capita, and 8-h ozone level (America, 2013). These associations are made with multiple regression analysis. The research I was looking at did not go into great detail to explain.
Seven variables are contributed to the Residential Density factor which is measured by combining six major variables: a) total density of urban and suburban census tracts; b) percent of people living in low-density suburban areas; c) percent of the population living in medium- to high-density areas; d) urban density within total built-upon land; e) relative concentration of density around the center of the Metro Statistical Area (MSA); and f) employment density. Land Use Mix is the second factor and measured through a combination of the following variables: the balance of jobs to total population and mix of job types within one mile of census block groups, plus the WalkScore of the center of each census tract. The third factor of Sprawl is Activity Centering. This is a key factor as it defines an area which is the proportion of people and businesses located near each other. This factor is measured by looking at the range of population and employment size in different block groups. MSAs with greater variation (i.e., a wider difference between blocks with a high population and a low one) have greater centering. This factor also includes a measure of how quickly population density declines from the center of the MSA and the population of jobs and people within the MSAs central business district and other employment centers. The last factor of Sprawl is Street accessibility (America, 2013). It is measured by combining a number of variables regarding the MSA’s street network. The variables are average length of street blocks; average block size; percent of blocks that are urban in size; density of street intersections; and percent of four-way or more intersections, which serves as a measure of street connectivity. Scoring is done when these four factors are combined in equal weight and controlled for population to calculate each area’s Sprawl Index score (America, 2013). Residential density, for example, includes the proportion of residents living in very spread-out suburban areas, the portion of residents living very close together in town centers, as well as simple overall density and other measures. Based on its performance, each metro area earned a score in each of the four factors, indicating where it falls on the gamut relative to other regions.
Why is the design of this research so important? When regions grow and develop, target groups such as the American household, local and federal governments, realtors, policymakers, urban planners, employees, have many important decisions to make. Will people be able to walk, ride a bicycle or take public transportation through the community, or will driving be the only realistic way for people to get around. Everyone experiences the outcomes from these decisions (America, 2013). How much will American households pay for transportation and housing, how much workers spend commuting home, the economic opportunities in communities are all linked to how neighborhoods and surrounding areas are built. Intending to curb sprawl by the groups I previously mentioned, it is the most comprehensive study and experiment to define, measure and evaluate metropolitan sprawl and its impact.
Before deciding on the design of my research, I seriously thought about doing a qualitative research as my methodology. I thought the research would not provide representative data. Social scientists, although having been interested in understanding travel behavior for a long time, have predominately employed quantitative research methods. Qualitative techniques do not generate statistically significant results; they are ideally suited for exploratory research such as identifying influential factors of travel behavior (Golledge, 1997). Survey techniques, focus groups, personal interviews, and participant-observation methods provide more detailed answers to current questions and issues regarding transportation and travel behavior. Thus, it should not be seen as a replacement to quantitative methods (Carr, 2008).
In conclusion, the preceding information that I have provided, clearly shows how sprawling metro areas with limited transportation choices cost families money. As costs of transportation rise, family budgets are increasingly squeezed. The sad part is that public investment and development patterns have created communities where families have little choice but to rely on private vehicles to reach jobs, stores, doctor’s offices, and life’s other daily errands. Picking up a gallon of milk or a loaf of bread today at your local convenient store can cost you to burn a gallon of gas. Family expenditures on transportation have grown significantly as land patterns have become more sprawling. This means transportation choices have become fewer. It is no wonder that transportation in some Metro statistical areas is the number one expense. There are still other issues that should be considered – out-of-pocket expenses of vehicle operation as well as the “time cost” of commuting (Brueckner, 2000). The “time cost” of commuting measures the dollar value to the commuter of time consumes while in transit. These two aspects represent the “private cost” of commuting, the cost that the commuter himself endures. Time costs are generated when the commuter drives on congested roadways to go to work. The extra congestion is caused by the commuter’s presence on the road is the cost; thus, congestion arises because increases in traffic on a crowded roadway leading to a substantial drop in traffic speed. Transportation (commuting) emerges large within the family budget. I can attest to the fact that some of my friends experience this problem.
A final note in relating to sprawl is that there could be simple and inexpensive strategies in curbing sprawl. One is incorporating social services into public transportation centers. This will ease the transportation burden by opening up public child care facilities at transportation centers. This makes it easier for working mothers and fathers to commute by bus or rail, dropping their kids off at daycare. This can lessen the need to own a private vehicle, thus freeing up more money. Policies could provide incentives to force developers create affordable traditional neighborhoods which are walkable and served by transit, can also help.

References
America, S. G. (2013). Measuring Sprawl 2014. Salt Lake City: Metropolitan Research Center.
Brueckner, J. K. (2000). Urban Sprawl: Diagnosis and Remedies. International Regional Science Review, 160-171.
Carr, K. (2008). Qualitative Research to Assess Interest in Public Transportation for Work Commute. National Center for Transit Research.
Ewing, R. &. (2002). Measuring sprawl and its impact. Retrieved from Smart Growth America: http://www.smartgrowthamerica.org/documents/MeasuringSprawl.PDF
Glaeser, E. (2004). Sprawl and Urban Growth. Handbook of Regional and Urban Economics, 2481-2527.
Gollege, R. G., & Stimson, R. J. (1997). Spatial behavior: A geographical perspective. New York: Guilford Publications, Inc.
Labor, U. D. (2008). Consumer Expenditure Survey, Metropolitan Statistical Area Tables 2001-2002. Retrieved from United States Bureau of Labor Statistics: http://bls.gov/cex/csxma.htm
McCann, B. (2000). Driven to spend. Washington, DC.: Surface Transportation Policy Project.
Nechyba, T. J. (2004). Urban Sprawl. Journal of Economic Perspectives, 177-200.
Newman, P., & Kenilworthy, J. (1999). Sustainability and cities: Overcoming automobile dependence. Washington, DC: Island Press.
Study Finds Americans Own 2.28 Vehicles Per Household. (2008, February 12). Retrieved from Auto Spies: http://www.autospies.com/news/Study-Finds-Americans-Own-2-28-Vehicles-Per-Household-26437/