Public transit subsidy represents a transfer of income from taxpayers to transit users. Such transfers raise questions regarding their effects, particularly equity. Our research focuses on social equity, and concerns the distribution of transit subsidies among socio-economic groups. Accordingly, this paper examines the ways that transit subsidy equity can be measured, and reviews the previous studies on this topic in detail. We propose a more precise method for measuring the subsidy of individual transit trips than has been employed in previous research. Using service consumption and travel survey data from the Los Angeles County MTA and a set of multi-factor cost allocation models developed in an earlier phase of this research, we examine the distribution of transit subsidies among various demographic groups,

We find that the distribution of transit costs and benefits among transit users is regressive with respect to income, more regressive than was found in most of the research conducted two or more decades ago. On average, consumers of short-distance local bus service – who are disproportionately low-income, African-American or Latino, younger, and female – require substantially less subsidy per trip than consumers of long-distance express of rail service – who are disproportionately higher-income, Anglo or Asian, older, and male. While low-income residents generally benefit from the public transit subsidy, this analysis finds that the benefits of subsidies disproportionately accrue to those least in need of public assistance. These findings raise questions regarding the conflicting objectives of transit policies which seek to deploy services to attract both transit dependents and choice riders.

The implementation of new transit lines is some times dogged by concerns that such lines may increase crime rates in station neighborhoods. Affluent communities have often complained that transit lines transport crime to the suburbs. This study focuses on the Green Line transit system in Los Angeles and examines its effects on crime in the adjacent areas. The Green Line light rail system passes through some high-crime inner city neighborhoods and terminates at its western end in affluent suburban communities. The study examines neighborhood level and municipality-wide crime trends for five years before and five years after the inception of the line. A piecewise regression model is developed to evaluate the impact of the opening of the line in the station neighborhoods. GIS analysis is also utilized to identify spatial shifts in crime hot spots for municipalities abutting the Green Line. At the end, the study establishes that the transit line has not had significant impacts on crime trends or crime dislocation in the station neighborhoods, and has not transported crime from the inner city to the suburbs.

The report identifies the motivations behind and objectives of specific road pricing initiatives, and to explore why such policies are becoming an increasingly popular approach to transportation finance and management. Over the past 15 years, electronic road pricing projects have appeared in a variety of forms across the globe – from the Interstate 15 High-occupancy toll (HOT) Lanes in San Diego County, to the congestion cordon pricing scheme in central London, to the German weight-distance truck toll system, to the Oregon mileage-based user fees pilot program. While the stated objectives of these projects are typically straightforward, the underlying motivations behind the turn to electronic road pricing are nuanced and varied. Accordingly, this report explores the forces behind this gathering shift in transportation policy toward electronic pricing through a series of case studies from around the globe. The information was gathered primarily through a detailed review of primary, secondary, and, when available, tertiary source documents.

In each of the case studies examined for this report, we find that the status quo – that is the old system of transportation planning and finance – is in crisis. Whether the problem is insufficient revenue or choking congestion, transportation planners and policymakers around the world are struggling to keep pace with the rise in motor vehicle traffic, and the problems that such growth engenders. As with many other policy areas, technology is facilitating the development of innovative approaches to facilitating the transition from theory to reality. With respect to transportation planning and finance, we conclude that we are at a unique juncture, as the full range of possibilities for the potential of road pricing is only now being fully realized.

The cost of producing public-transit service is not uniform but varies by trip type (e.g., local or express), trip length, time of travel, and direction of travel, among other factors. However, the models employed by public-transit operators to estimate costs typically do not account for this variation. The exclusion of cost variability in most transit-cost-allocation models has long been noted in the literature, particularly with respect to time-of-day variations in costs. This analysis addresses many of the limitations of cost-allocation models typically used in practice by developing a set of models that account for marginal variations in vehicle-passenger capacity, capital costs, and time-of-day costs. FY 1994 capital and operating data are used for the Los Angeles Metropolitan Transportation Authority (MTA). This analysis is unique in that it combines a number of previously and separately proposed improvements to cost-allocation models. In comparison with the model currently used by the Los Angeles MTA, it was found that the models developed for this analysis estimate (a) higher peak costs and off-peak costs, (b) significant cost variation by mode, and (c) lower costs for incremental additions in service. The focus is on the limitations of the rudimentary cost-allocation models employed by most transit operators and not on the Los Angeles MTA per se. This analysis found that an array of factors addressed separately in the literature can be incorporated simultaneously and practically into a usable cost-allocation model to provide transit systems with far better information about the highly variable costs of producing service.

The cost of producing public transit service is not uniform, but varies by trip type (such as local or express), trip length, time of travel, and direction of travel, among other factors. Yet the models employed by public transit operators to estimate costs generally do not account for this variation. The exclusion of cost variability in most public transit cost allocation models has long been noted in the literature, particularly with respect to time-of-day variations in costs. This analysis addresses many of the limitations of cost allocation models typically used in practice by developing a set of models that account for marginal variations in vehicle passenger capacity, capital costs, and time-of-day costs using FY 1994 capital and operating data for the Los Angeles MTA. This analysis is unique in that it combines a number of previously and separately proposed improvements to cost allocation models. In comparison to the model currently used by the MTA, we find that the models developed for this analysis estimate: (1) higher peak period costs and lower base period costs, (2) significant variations in costs by mode, and (3) substantially lower costs for incremental additions in bus service. While this study uses Los Angeles MTA data, the focus of this analysis is not on the MTA per se, nor is this work intended as a critique of MTA practice. Rather, the focus of this study is on the limitations of the rudimentary, average cost allocation models employed by most transit operators. Toward that end, this analysis shows quite clearly that an array of factors addressed separately in the cost allocation model literature can be simultaneously and practically incorporated into a usable transit cost allocation model to provide transit systems with far better information on the highly variable costs of producing transit service.

How much does a transit trip cost? How does the subsidy a transit trip vary from trip-to-trip, passenger-to-passenger, and system-to-system? How does the of public transit patrons vary among various classes of transit users? These are important matters of public policy that have received surprisingly little attention in the research literature in recent years.

The cost of producing public transit service is not uniform, but varies by trip type (such as local or express), trip length, time of travel, and direction of travel, among other factors. Yet the models employed by public transit operators to estimate costs typically do not account for this variation. The exclusion of cost variability in most transit cost allocation models has long been noted in the literature, particularly with respect to time-of-day variations in costs.

This analysis addresses many of the limitations of cost allocation models typically used in practice by developing a set of models that account for marginal variations in vehicle passenger capacity, capital costs, and time-of-day costs using FY 1994 capital and operating data for the Los Angeles MTA. This analysis is unique in that it combines a number of previously and separately proposed improvements to cost allocation models. In comparison to the model currently used by the MTA, we find that the models developed for this analysis estimate: higher peak costs and off-peak costs, significant cost variation by mode, and lower costs for incremental additions in service. The focus of this study is on the limitations of the rudimentary cost allocation models employed by most transit operators, and not on the MTA per se. This analysis finds that an array of factors addressed separately in the literature can be simultaneously and practically incorporated into a usable cost allocation model to provide transit systems with far better information on the highly variable costs of producing service.

This report summarizes findings from interviews with transit officials at seven agencies in North America about smart card evaluations, expectations, and implementation. As part of the project, “Designing a Policy Framework for a Statewide Transit Smart Card System,” this report was preceded by a literature review of smart card projects and an online survey of transit agencies’ knowledge of and interest in interoperable smart card systems for fare collection. The literature review found a lot of booster-like enthusiasm for smart cards, but few studies that have rigorously evaluated smart card system benefits relative to their costs, nor have they addressed the array of institutional issues that hinder implementation. Our survey revealed that many transit agencies are in the process of considering or have already adopted smart card systems, often without clear or certain information about the costs of these systems. Prior to forming collaborations with other agencies, surveyed agency officials tended to underestimate the difficulty of multi-agency partnerships. Once they entered these collaborations, however, agency officials tended to cite multi-agency agreement as the most significant barrier, more difficult to overcome than the financial costs of the systems.

Interviews conducted with transit agency officials focused on the decision-making and collaboration processes involved in adopting interoperable smart card systems, and the barriers that they faced. This report documents our findings, and begins first with a description of our interview methods, followed by summaries and highlights of each of the seven smart card projects currently being evaluated or implemented. The case studies include projects in Los Angeles County, the San Francisco Bay Area, Ventura County, Orange County, Santa Barbara County, the Washington Metropolitan Area, and Southeastern Pennsylvania. The report concludes with a summary of issues common to the seven cases, some strategies used in implementing interoperable smart card systems, and a description of next steps of our research.

This chapter deals with an important citizen right: the ability to walk from home or work to the transit stop, or wait at a bus stop or on a station platform without the fear of being victimized. Crime and fear of crime unfortunately affect many aspects of everyday life in our cities. Transit crime is a rather persistent but underreported trend that scares and intimidates riders – particularly women. The majority of incidents represent public nuisance crimes. The majority of the victims are captive transit riders, frequently immigrant and poor. In Los Angeles some of the victims are even afraid to report transit crimes to the authorities lest they expose their illegal-resident status.

In this chapter, we want to argue that planners and policy makers need to often scratch beyond the surface of official numbers and crime statistics. At the same time, relying on one theory to understand a complex urban phenomenon, such as crime, may often prove inadequate. In our case, we found two seemingly antithetical theories useful, but still needing validation with empirical data: compositional theories that cast attention on offenders, and ecological theories that focus on the context of crime. We discovered that to understand a problem that is largely invisible to authorities, we had to rely not only on crime reports but also extensive fieldwork, to combine quantitative and qualitative techniques, and go from the macro to the micro, from census data to first-hand observation, and surveys of riders.