Multi-Regional Economic Models for Transportation Planning
Corresponding Author: Derek Cutler, Economic Development Research Group, Inc.
Presented By: Chandler Duncan, Economic Development Group
Abstract
The state of the practice in economic impact modeling has evolved in the last 5-10 years in ways that can have significant implications for traffic modeling, long range transportation planning and freight systems analysis. For many years economic impact models applied in the transportation context have treated each “region” as its own sub-economy within a larger system. For example, it is quite typical for economic impact models to derive transportation cost savings from associated travel demand models and simply allow transportation savings to generate changes in earnings, output, jobs and housing proportional to the share of the transportation savings which is known to accrue in the region (or county) with the remainder treated as “external.” In the case of multi-county or multi-state models, “out of region” impacts have often simply been proportionally allocated based on each external station (or external county or region’s) share of overall inbound or outbound trips, or even based on a share of background employment or GDP.
However, increasingly the industry standard is for economic models to distribute the employment (and associated housing) impact of transportation performance improvements among counties based on known trade relationships between counties. For example, if a bottleneck is removed in Columbus, Ohio, increasingly economic models will distribute the job gains between Columbus and surrounding cities like Cincinnati, Cleveland and Pittsburgh based on known trade patterns between those cities (instead of simply by some ration of employment or pre-existing trip distribution). This new type of model for deriving and allocating economic impacts has significant implications for feedback loops in statewide travel models as well as multi-county regional and MPO models. This presentation describes the significance of multi-regional input-output models both for validating travel demand results and ensuring appropriate feedbacks between traffic and economic models. Examples of multi-regional input output models from Nebraska and California are used in case examples to demonstrate how this change in economic models can be of significance to transportation applications throughout the nation.