The Fuse

Could Small Changes in Land Use Cause Large Shifts in Vehicle Ownership?

by Hart Schwartz | February 09, 2018

Household vehicle ownership increases substantially from cities to suburbs to rural areas.

Land-use patterns are complex. Diverse forces such as culture, economics, psychology, history, policy, and other factors act in parallel upon the same parcels of land, producing diverse land types that are not easy to describe. However, breaking out land-use into three simple types according to Census geographical classifications—cities, suburbs, and rural—reveals that household vehicle ownership increases substantially from cities to suburbs to rural areas.


The data in the above chart gives rise to the following question: Which key variables are associated with such wide shifts in vehicle ownership per land-use? Research shows that the following geographic and economic variables are closely correlated with vehicle ownership differences by land-use type:

  • Population Density (population per square mile)
  • Housing Density (occupied housing units per square mile)
  • Household Income (annual median)

Population density, housing density, and median household income help to translate “soft” intangibles of urban design into a “hard” impact on numerical indicators. Because people make decisions at the margin, how large do changes in these variables need to be in order for large changes in vehicle ownership levels to occur? Given that the Census Bureau predicts an increase in population of roughly 100 million people between 2015 and 2060, it is important to have a cohesive framework to evaluate how changes in land development may impact vehicle ownership levels over time.

This article will present statistical correlations between population density, housing density, household income, and vehicle ownership per land-use, followed by an assessment of impact on vehicle ownership decisions.

Density: Inverse correspondence with vehicle ownership     

Density takes on two standard measurable forms—population and housing. Each statistic shows an inverse correspondence with vehicle ownership. For population density, the more people that live in a given area, the less vehicle ownership is in that area; for housing density, the more occupied housing units that are in a given area, the less vehicle ownership there is. This negative correlation is most likely because less land per person (i.e. higher population density)  and less distance between households (i.e. higher housing density) imply shorter travel distances and less need for personal vehicles in order to carry out daily tasks. The most recent density data comes from the 2010 decennial census and can be seen in the following charts:


Household income: Direct correspondence with vehicle ownership 

Household income shows a direct correspondence with vehicle ownership. That is, suburban and rural areas both have higher median incomes and higher vehicle ownership rates, on average, than cities, matching the higher rates of vehicle ownership in suburbs and rural areas.

Suburban and rural areas both have higher median incomes and higher vehicle ownership rates, on average, than cities, matching the higher rates of vehicle ownership in suburbs and rural areas.

As households become wealthier, they can afford to live in the more spread-out suburban areas, and thus they can afford to purchase vehicles to account for the longer distances and lower densities. In rural areas, incomes are higher than cities, though not by as great a difference as in suburbs. Even so, higher rural household incomes coincide with far lower density to incentivize a very high level of household vehicle ownership.


Can Vehicle Ownership Levels Change? Analysis “at the margin”

The correlations between the three variables above (population density, housing density, household income) and vehicle ownership, according to land-use type, can be sharpened further by breaking out vehicle ownership levels more specifically in each land-use type. Economics teaches that decisions happen at the margin. Initial costs are fixed but marginal costs are variable. People weigh the last additional benefits and costs more closely. The following graph strongly suggests an analysis “at the margin”:


Because this chart provides highly specific visibility of the proportions of vehicles per household, it becomes possible to concretely imagine what a marginal reduction in vehicle ownership might look like, according to each specific land-use type. For instance:

  • City: Can more than 15 percent of city households be persuaded to go without a vehicle?
  • Suburbs: Do 24 percent of suburban households really need three or more vehicles?
  • Rural: Do 11 percent of rural households really need to have four or more vehicles?

To put these questions in further perspective, it is worth noting how much of the U.S. population lives within each land-use type:


Looking at the population numbers reveals the extent to which marginal changes in household vehicle ownership could affect national patterns. What if small changes in population density, housing density, or household income lead to a decision to drop the last marginal vehicle? How many people would this affect, and in which locations?

Suburbs and cities together comprise metropolitan areas, including over 85 percent of U.S. population in 2016. As metropolitan areas are the locale where most future U.S. population growth will likely take place, the dance between low-density suburban and high-density urban settlement becomes an important juncture that can possibly stimulate marginal changes in vehicle ownership. If future population growth occurs in suburbs of lower-density and higher income, then vehicle ownership will likely remain higher, whereas if future population growth gathers in higher density, lower income cities, vehicle ownership will likely be lower. There is the additional question of whether, within suburbs themselves, long-running trends towards “urbanization of the suburbs” can provoke changes toward higher density, lower-income suburbs. Such a trend may result in lower vehicle ownership in future decades in America’s metropolitan areas.

Comparing cities with rural areas, on the other hand, reveals a starker contrast. In rural areas, trends are likely to remain constant, because the immense distances and very low densities necessitate higher numbers of vehicles. In stark contrast to rural areas, cities constitute the place where people are the most likely to give up their vehicles, due to higher densities leading to availability of other options such as public transit, walking, biking, or ride-sharing.

Conclusion: Variables to track

The future of U.S. land-use patterns could have a significant impact upon vehicle ownership. Translating complex configurations of land-use into concrete variables trackable by policymakers could prove very useful in monitoring the development of the situation. Can incremental adjustments in population density, housing density, or household income cause millions of households to give up their last marginal vehicle? What is the impact of whether these changes in density or income occur in a city, suburb, or rural area? These variables will be key factors in assessing vehicle ownership trends and the future of transportation.