General Overview

The PSRC has developed a set of procedures and methods for project and program evaluation for transportation benefit-cost analysis. Benefit-cost methods produce information about the relative magnitude of benefits and costs that accrue (over time) to society as a result of any given action. The purpose of such analysis is to compare the benefits associated with a policy or investment with the costs of implementing the policy or investment. If the sum of the benefits of the project or policy exceeds the costs then there is a general economic argument supporting the action to make the investment or implement the policy.

Transportation planning decisions can involve large up front costs, with benefits that play out over time. The benefits of projects accrue across multiple users with both localized and broadly distributed effects. The complexity of these problems is recognized and accounted for in the travel demand modeling practices of regional planning agencies. A natural extension of these modeling practices is the accurate accounting of benefits and costs in a manner that can directly support decision making. A dominant approach to this kind of accounting is benefit-cost analysis, and in Washington state these methods are a necessary part of fulfilling regional planning requirements set out in state law under a more general heading of “least-cost planning”.

PSRC Benefit-Cost Analysis tool

The PSRC commissioned the development of custom benefit-cost accounting software from the consulting firm ECONorthwest. The primary methods for estimation of user benefits that underpin the PSRC Benefit-Cost Analysis (BCA) tool are the same as those developed for AASHTO’s “Red Book”, and those developed for a companion manual for estimation of transit user benefits.

The software developed by ECONorthwest makes use of standard data available in specially prepared travel model databanks from the regional travel demand model software, EMME/3. The databanks contain various trip cost, time, vehicle class and time of day information aggregated at either the origin-destination pair or links in the model network. This data is extracted and processed in a manner that permits consumer surplus and environmental benefit accounting when one model run is compared directly with the base case scenario. The benefit-cost analysis tool consists of a number of software elements written in the Python programming language. Data is processed and stored as schema in a Postgres relational database. Results are then compiled through a web-based (Django) user interface, with programmable input parameters, and then tabulated in .csv output files that can be opened directly with standard spreadsheet software.