Transportation Finance, Congestion, and Equity: Some Policy Perspectives

Document Type

Journal Article

Publication Date


Subject Area

operations - traffic, land use - planning, ridership - demand, policy - equity, policy - congestion, economics - revenue, economics - finance, mode - mass transit, mode - subway/metro


Twin Cities Metropolitan Area (Minnesota), Travel models (Travel demand), Travel demand, Transportation policy, Transportation planning, Transit, Traffic congestion, Social justice, Social equity, Revenues, Public transit, Poverty, Poor people, Mass transit, Low income groups, Low income families, Local transit, Highway planning, Gridlock (Traffic), Finance, Fairness (Social equity), Equity (Justice), Equity (Finance)


Traffic congestion continues to be a major concern for policy makers and transportation professionals in most large U.S. metropolitan regions. While demand for travel continues to increase, traditional sources of revenue used to finance transportation at the state and local levels are yielding fewer resources (or at least slowing in their rate of growth). As a result, transportation decision makers continue to seek new sources of revenue to finance expansive highway and transit plans. While much effort is expended in seeking adequate revenue sources, little effort is given to determining the equity effects of these new revenue sources, much less the policies they are designed to support. This paper investigates one particular aspect of equity, vertical equity, in relation to transportation finance and policy. Through the use of sets of data (travel demand, financial, and operational) from Minnesota and specifically from the Twin Cities region as illustrations, the authors argue that current policies toward transportation finance and congestion do little to further the interests of low-income individuals and may in fact benefit others at their expense. The authors conclude with some recommendations aimed at redistributing more equitably the burden of financing transportation programs among users and nonusers.