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Rent growth near rail stations after the Great Recession

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  • John L. Renne
  • Jyothi Chava
  • Bruce Appleyard
  • Tara Tolford

Abstract

This study provides an incisive analysis of U.S. rail station area rent trends from 2012 to 2016, post-Great Recession. Utilizing Ordinary Least Squares (OLS), Hierarchical Spatial Autoregressive (HSAR), and Geographically Weighted Regression (GWR) models, it uncovers complex interplays between rent changes and socioeconomic, as well as built environment factors. Key findings reveal that increased rents are associated with walkability, higher housing density, and predominantly White neighborhoods. Conversely, rent decreases correlate with diverse land use, higher Black population percentages, and locations further from rail stations or business districts. These results are critical for understanding rent dynamics in transit-oriented development areas, impacting diverse housing market sectors, including workforce and affordable housing. The study’s regional analysis highlights the need for geographically tailored approaches. This research informs policy on housing development and affordability, aiming to mitigate displacement risks for low-income, transit-dependent communities in gentrifying urban areas.

Suggested Citation

  • John L. Renne & Jyothi Chava & Bruce Appleyard & Tara Tolford, 2024. "Rent growth near rail stations after the Great Recession," Journal of Sustainable Real Estate, Taylor & Francis Journals, vol. 16(1), pages 2300556-230, December.
    • Handle: RePEc:taf:rsrexx:v:16:y:2024:i:1:p:2300556
    DOI: 10.1080/19498276.2023.2300556
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