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Student Thesis and Dissertations

Enhancing Performance Measurement: Implementing Computable General Equilibrium Models in Truck-Freight Network Investment Prioritization

 
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Publication: Freight Policy Transportation Institute
Publication Date: 2013
Summary:
The adoption of defensible performance measures and establishment of proven results has become a necessity of many state Transportation Departments. A major factor in demonstrating results is the impact a transportation infrastructure improvement project has on the region’s economic climate. Though often previously underrepresented in policy and planning of transportation systems, freight movement plays a critical role in the transference of infrastructure improvement benefits into regional economic impacts. The degree of impact influenced by freight movement improvements is dependent upon location and geographic scale of evaluation. This paper assesses the geographic scale considerations in selecting the modeling framework to evaluate economic impacts. Specifically, we consider the results of regional input-output (I-O) models as compared to those of computable general equilibrium (CGE) models in response to reduced travel time and operating costs in the freight highway network. Though widely used for policy and planning purposes, I-O models have come under criticism for their inability to realistically model the behaviors of a regional economy. Despite their increased flexibility in real-world modeling, CGE models have been resisted due to their complexity of use. We consider the implications of selecting between ease of use and model flexibility at scales ranging from a single county to statewide.

 

 

Authors: Dr. Anne Goodchild, Jeremy Sage, John Maxwell, Zun Wang, Ken Casavant
Recommended Citation:
Sage, Jeremy. John Maxwell, Zun Wang, Ken Casavant, and Anne Goodchild. "Enhancing Performance Measurement: Implementing Computable General Equilibrium Models in Truck-Freight Network Investment Prioritization." University of Washington Master's degree thesis.