Impact Methodologies

Distribution of Impacts

Overview

It is frequently of interest to assess how the range of benefits and impacts of transportation alternatives are distributed across population groups. The distribution of impacts can take various forms and can be measured in different ways. The Civil Rights Act of 1964 provides a legal imperative to avoid discrimination based on race, income, or national origin. Impacts may also be compared across other population groupings, for example, by geography, age, or mobility limitation. An analysis of the distribution of transportation impacts may also compare overall benefits to overall costs and other impacts by population group.

In transportation planning, the distribution of impacts is often a concern for three major types of impacts:

• Transportation benefits, including mobility and accessibility;

• Transportation costs, including who pays for the services (through user fees, taxes, etc.), and how do the costs paid compare to the benefits received; and

• Externalities, including air pollution, noise, and neighborhood disruption.

The development of acceptable and agreed-upon measures of distribution is not always simple. Some complicating factors include:

• Because of the aggregate nature of common data sources on population characteristics (such as the census), neighborhood-level population characteristics must generally be used as a proxy for specific groups being examined. For example, if concern is expressed over impacts on minority populations, the impacts are measured for neighborhoods that exceed a certain percentage minority population, rather than for specific minority persons or households.

• The definition of unacceptable inequities or "disproportionate" impacts is not always clear. For example, if in evaluating a transportation alternative a low-income group is made better off in absolute terms, but worse off relative to other income groups, is the alternative favorable or unfavorable from a distributional standpoint?

• Some factors that affect impact distribution are difficult to forecast, complicating the evaluation of future distributional implications. For example, it is difficult to forecast the geographic location of population according to race, income, etc., characteristics. An additional complicating factor is that locational decisions may be affected by transportation investments. For example, positive externalities (i.e., good transit or highway access) can lead to higher property values and a migration of higher-income people to the area served.

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