This study draws on census data and geographic information systems (GIS) to investigate the relationship between light rail transit (LRT) infrastructure development and gentrification in Portland, Oregon. While recent research using comprehensive measures of neighborhood socioeconomic status (SES) supports a potentially causal link between transit development and gentrification, research into the effects of transit on property values alone tends to dominate the discourse. This study therefore seeks to build on previous research to develop an index measure of neighborhood SES and SES change based on measures of education, occupation, and income, using census data from 1980-2010. This multifaceted measure of neighborhood SES is analyzed in relation to LRT access using correlation, OLS regression, and GIS hot spot and choropleth mapping.
Findings: Throughout the study period, low SES neighborhoods largely disappeared from the City of Portland, while low-income households were gradually priced out. Simultaneously, the easternmost suburb of Gresham became more highly concentrated in low SES neighborhoods. No definitive relationship between LRT and SES is found along the Eastside Blue or Westside Blue Lines, but strong evidence is found supporting a positive effect of Yellow Line MAX development on the rapid gentrification of North Portland from 2000-2010. Regressions run on neighborhoods along the Yellow Line indicate that SES change was greatest for those that began the decade with large Black populations, low rents, and close proximity to stations. Findings are discussed through the theoretical framework of the urban growth machine, which suggests the differential relationship between LRT and neighborhood SES relates to the distinct values of different parts of the region for the pursuit of general growth goals.
| Identifer | oai:union.ndltd.org:pdx.edu/oai:pdxscholar.library.pdx.edu:open_access_etds-3923 |
| Date | 03 June 2016 |
| Creators | Rochester, Nathan Eric |
| Publisher | PDXScholar |
| Source Sets | Portland State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations and Theses |
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