NEW INSIGHTS INTO THE VALUE OF TRANSIT: MODELING INFERENCES FROM DADE COUNTY
operations - traffic, ridership - commuting, ridership - disadvantage, place - asia, place - africa, place - cbd, mode - bus, mode - mass transit
Workforce, Work force, Whites, Wages, Value, Transportation disadvantaged persons, Transit, Traffic analysis zones, Racial factors, Race, Public transit, Miami-Dade County (Florida), Mass transit, Local transit, Least squares method, Labor force, Income, Hispanics, Ethnic groups, Employment, Downtowns, City centers, Central business districts, Caucasians, Automobile ownership, African Americans, Accessibility
Whether transit accessibility influences labor force participation and income of different racial and ethnic groups is examined. The methodology involves the use of two-stage least-squares analysis to control for possible reverse causality in two of the explanatory variables: transit accessibility and auto ownership. Earlier literature on spatial mismatch theory suggests that transit accessibility should make a difference in unemployment rates for African Americans confined to inner city ghettos. In contrast, more recent literature suggests that other variables, such as workplace discrimination, are far more significant explanatory variables. Because all of these studies used measures of transit accessibility that failed to show the ease with which residents of a geographic area could access jobs in the entire region, this study attempts to do so. The transit accessibility measure is first calculated for traffic analysis zones (TAZs) in Dade County, Florida, and it is then used as one of several explanatory variables in models of African American, Hispanic white, and non-Hispanic white labor force participation; median zonal household income; and automobile ownership in TAZs. This research finds that transit accessibility does not explain labor force participation of any of the groups, but it helps explain household income as well as auto ownership. Higher transit accessibility is concluded to either directly or indirectly increase wage rates significantly for auto-disadvantaged groups.
Thompson, G. (2001). NEW INSIGHTS INTO THE VALUE OF TRANSIT: MODELING INFERENCES FROM DADE COUNTY. Transportation Research Record, Vol. 1753, p. 52-58.