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Relating Transportation Quality Indicators to Economic Conditions in the South-Central U.S.

Relating Transportation Quality Indicators to Economic Conditions in the South-Central U.S.

Jonathan C. Comer, Amy K. Graham, Stacey R. Brown
Copyright: © 2011 |Volume: 2 |Issue: 3 |Pages: 19
ISSN: 1947-9654|EISSN: 1947-9662|EISBN13: 9781613505595|DOI: 10.4018/jagr.2011070101
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MLA

Comer, Jonathan C., et al. "Relating Transportation Quality Indicators to Economic Conditions in the South-Central U.S." IJAGR vol.2, no.3 2011: pp.1-19. http://doi.org/10.4018/jagr.2011070101

APA

Comer, J. C., Graham, A. K., & Brown, S. R. (2011). Relating Transportation Quality Indicators to Economic Conditions in the South-Central U.S. International Journal of Applied Geospatial Research (IJAGR), 2(3), 1-19. http://doi.org/10.4018/jagr.2011070101

Chicago

Comer, Jonathan C., Amy K. Graham, and Stacey R. Brown. "Relating Transportation Quality Indicators to Economic Conditions in the South-Central U.S.," International Journal of Applied Geospatial Research (IJAGR) 2, no.3: 1-19. http://doi.org/10.4018/jagr.2011070101

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Abstract

Investment in transportation infrastructure is widely assumed to spur economic growth, a belief that persists among both the general public and government officials. However, research has provided inconsistent evidence to date, and many researchers believe that good transportation is a necessary but insufficient condition for regional growth. This study examines the issue from a different perspective than the majority of past research, using spatial regression techniques to explore the relationship between transportation quality and regional economic development at an intermediate spatial resolution. Using federal highway statistics on pavement roughness and bridge quality, this research examines the relationship between measurable results of transportation spending, as evidenced by better quality roads and bridges, and various indicators of economic health. This relationship is examined in the South-Central U.S. (Arkansas, Kansas, Oklahoma, and Texas) at the county level and uncovers moderate to weak regression coefficients overall but with notable spatial variations across the study area.

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