A draft manuscript describing my latest transportation research is now available. The title is, "Integrating Multimodal Data into Benefit-Cost Analysis for Transportation Planning and Public Policy"
In this paper, we explore two types of BCA models. The first type we refer to as models for public policy analysis. This is the type of analysis I am familiar with from teaching BCA to graduate and undergraduate students. We refer to the second type of models as models for planning. These are used, for example, at state Departments of Transportation. I was not very familiar with these types of models before beginning this research, but I have learned a good deal about them in the course of writing this report.
I am very happy with what we were able to produce and I will seeking feedback on it over the next couple of weeks, as this report goes through peer and editorial review. Please email me with any questions or comments!
The abstract is below:
Abstract
Federal,
state and local governments allocate billions of dollars in transportation
funds each year. One useful tool for
helping to decide which projects are best investments is Benefit-Cost Analysis
(BCA). Ideally, BCA takes into account
all impacts of a decision, and provides a way of selecting investments that
maximize social welfare. However, in
practice even the best BCAs only measure select impacts. This project develops methods of improving
BCA by better integrating multimodal transportation data. It considers both BCA for evaluating past
policy decisions, and BCA for planning and programming future transportation
investments. We identify shortcomings of
existing models, and propose, implement and evaluate concrete solutions. Case studies in transportation planning focus
on the California Department of Transportation (DOT), but benchmark
California’s competencies by exploring methods used by other states and local
governments. In addition, while the
focus is on BCA output as a concrete example of the type of performance measure
that may suffer from data integration problems, we also consider other
important models used by DOTs, especially travel demand models. The conclusion
lists all recommendations for improving transportation planning through more
integrated models. These will have
immediate use to Caltrans as it considers directions for developing new
planning capabilities. In addition by
fitting the planning models we explore in the broader context of transportation
planning and policy, this report will also serve as a valuable resource for
analysts, managers and others who are interested in better understanding BCA
methods and their use.