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Assessment of Bus Transit Equity in Two Metropolitan Areas (Full Text)

Authors: David Martinelli and Leonel Medellin

Abstract

The generalized cost of a transit user depends mostly on time and money spent per trip. On the other hand, time and distance determine most of the transit agency’s cost to provide service. These are important factors to consider in determining the equity performance of service provided to users of different demographic groups. The purpose of this study is to determine significant statistical differences in resources spent by bus users in two metropolitan areas. The study measures inequality among different socioeconomic groups of users in terms of travel time and money consumed per mile in using the service. Inequality is then compared between two case studies.

Transit subsidies represent a transfer of income from taxpayers to bus users. Past studies have found that benefits disproportionately accrue consumers of long distance trips –mostly higher-income, White, older, and male. Since transit policies seek to attract both, transit dependents and choice riders, the situation raises questions regarding these conflicting objectives.

This study gives a closer look to transit equity by including, not only distance, but also travel time as a way to include quality of service in terms of speed. This approach answers the question: “are faster trips charged cheaper?” Therefore, the analysis focuses on the monetary and temporal resources spent by users of different demographic background.

Information from household travel surveys performed by two metropolitan areas, Columbus and Seattle, is analyzed here. The data includes distance, travel time and fare paid per trip, besides demographic information, such as household income, household size, ethnicity, gender, and age. Statistical differences in resources spent are found by using the t-test approach and inequity is determined by means of the Gini coefficient and the Theil and Atkinson indices of inequality.

Statistical differences were actually found between demographic groups and inequality was measured. Results support previous findings, showing that lower income, minority, younger and female users pay more per mile of service. Furthermore, it was found that in addition to higher fares per mile, they also receive an inferior service in terms of speed.

The analysis points to the conclusion that faster trips are in fact charged at cheaper rates of fare per mile. Results found here however, are applicable only to the two metropolitan areas analyzed and during the time when surveys were taken. The approach though, can prove to be a useful method to compare transit equity between cities and to determine improvement of transit policies through time.