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Annotated Bibliography - SSTI

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Title<br />

Models to Predict the Economic Development Impact of Transportation Projects:<br />

Historical Experience and New Applications<br />

Authors Glen Weisbrod<br />

Sponsor Economic Development Research Group (EDR Group)<br />

Date December, 2007<br />

Pages 25<br />

Category Economic Performance Measures, Modes: All<br />

Note<br />

Online<br />

Summary<br />

http://www.edrgroup.com/edr1/bm~doc/models‐to‐predict‐the‐eco.pdf<br />

This article provides a historical overview of the connection between transportation<br />

and economics, beginning in Roman times and ending with current computerized<br />

modeling. It explains that "predictive impact models used for decision‐making should be<br />

sensitive to causal factors and elements of access impact known to make a difference in<br />

the effect of transportation projects on regional economic growth and development".<br />

Discusses a shift from a primary focus on economic benefits of time and cost savings to<br />

broader functions of economic development such as accessibility roles in supply chains,<br />

labor market expansion, and global trade growth.<br />

The report explains how several classes of models have been implemented over time in<br />

order to assess economic development and transportation. These include impact<br />

models, land use‐development models, macro‐economic models, regional economic<br />

simulation models, and local access models. The report examines each of these types<br />

and provides a detailed history of a computer based model for each. For instance, it<br />

provides an in depth account of REMI Policy Insight (REMI‐PI) to demonstrate a regional<br />

simulation model. The first application of the model was to assess transportation and<br />

calculate the economic growth impacts of business cost changes for a proposed<br />

highway in Wisconsin in 1988. At this time, it was concluded that other models need to<br />

be applied along with REMI‐PI in order to yield the most accurate results and an<br />

economic geography element was added that modifies regional purchasing patterns<br />

dependent on changes in generalized commodity access and labor access indices.<br />

<strong>Annotated</strong> <strong>Bibliography</strong> Page 38

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