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Neighborhood Walkability and Housing Prices: A Correlation Study

Author

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  • Eun Jung Kim

    (Department of Urban Planning, Keimyung University, Daegu 42601, Korea)

  • Hyunjung Kim

    (Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Korea)

Abstract

This study aims to examine the relationship between the level of walkability and housing prices in Seoul, Korea. The average transaction price per square meter for each apartment complex was set as a dependent variable and the walkability score was used as an independent variable. This study divided a total of 5986 apartment complexes into areas with high and low housing prices for analysis. Based on the strong spatial autocorrelations of housing prices, this study employed spatial regression models in addition to the Ordinary Least Squares (OLS) model. Results showed that housing prices positively correlated with the walkability score in areas with low housing prices, whereas no significant association was observed in areas with high housing prices. Additional findings showed that housing prices were associated with building age (−), number of households in the complex (+), slope (−), and greenness (+) in both subsamples. Results also showed that high school quality had a different association with housing prices depending on the subsample (e.g., the sign was positive in areas with high housing prices and no significance in areas with low housing prices). The results herein support public policy proposals relevant to urban planning, environmental design, and housing policies.

Suggested Citation

  • Eun Jung Kim & Hyunjung Kim, 2020. "Neighborhood Walkability and Housing Prices: A Correlation Study," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:593-:d:308331
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    References listed on IDEAS

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    5. Jônatas Augusto Manzolli & André Oliveira & Miguel de Castro Neto, 2021. "Evaluating Walkability through a Multi-Criteria Decision Analysis Approach: A Lisbon Case Study," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
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    7. Dong Hyun Kim & Amina Irakoze, 2022. "Identifying Market Segment for the Assessment of a Price Premium for Green Certified Housing: A Cluster Analysis Approach," Sustainability, MDPI, vol. 15(1), pages 1-16, December.
    8. Daniel Lo & Kwong Wing Chau & Siu Kei Wong & Michael McCord & Martin Haran, 2022. "Factors Affecting Spatial Autocorrelation in Residential Property Prices," Land, MDPI, vol. 11(6), pages 1-16, June.
    9. Bradley Bereitschaft, 2023. "The changing ethno-racial profile of ‘very walkable’ urban neighbourhoods in the US (2010–2020): Are minorities under-represented?," Urban Studies, Urban Studies Journal Limited, vol. 60(4), pages 638-654, March.
    10. Haruka Kato & Atsushi Takizawa, 2021. "Which Residential Clusters of Walkability Affect Future Population from the Perspective of Real Estate Prices in the Osaka Metropolitan Area?," Sustainability, MDPI, vol. 13(23), pages 1-20, December.
    11. Gao, Qishuo & Shi, Vivien & Pettit, Christopher & Han, Hoon, 2022. "Property valuation using machine learning algorithms on statistical areas in Greater Sydney, Australia," Land Use Policy, Elsevier, vol. 123(C).
    12. Pereira, Mauro F. & Vale, David S. & Santana, Paula, 2023. "Is walkability equitably distributed across socio-economic groups? – A spatial analysis for Lisbon metropolitan area," Journal of Transport Geography, Elsevier, vol. 106(C).

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