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Spatial Determinants of Housing Price Values in Istanbul

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  • Turgay Kerem Koramaz
  • Vedia Dokmeci

Abstract

The aim of this study was to measure the effect of spatial characteristics on housing prices and to integrate an interpolation and regression model in terms of spatially predicting housing price values. In this paper, housing price is investigated by taking into consideration distance to city centre, transportation arteries and coasts, in addition to housing and neighbourhood characteristics as control variables. This investigation is conducted in two stages: firstly by the utilization of multiple regression analysis, and then by an interpolation technique which is generated to predict the spatial pattern of housing price on a continuous surface in order to test the reliability and consistency of the regression model. The results reveal that housing prices are significantly affected by spatial determinants referred to as the distance variables. By conducting a residual analysis from the regression model, housing price values are analysed and visualized in a continuous map which is globally consistent with the housing markets in Istanbul.

Suggested Citation

  • Turgay Kerem Koramaz & Vedia Dokmeci, 2012. "Spatial Determinants of Housing Price Values in Istanbul," European Planning Studies, Taylor & Francis Journals, vol. 20(7), pages 1221-1237, July.
    • Handle: RePEc:taf:eurpls:v:20:y:2012:i:7:p:1221-1237
    DOI: 10.1080/09654313.2012.673569
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    References listed on IDEAS

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    1. Daniel A. Griffith, 2003. "Spatial Autocorrelation and Spatial Filtering," Advances in Spatial Science, Springer, number 978-3-540-24806-4, december.
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    Cited by:

    1. Ming Li & Guojun Zhang & Yunliang Chen & Chunshan Zhou, 2019. "Evaluation of Residential Housing Prices on the Internet: Data Pitfalls," Complexity, Hindawi, vol. 2019, pages 1-15, February.
    2. Sisman, S. & Aydinoglu, A.C., 2022. "Improving performance of mass real estate valuation through application of the dataset optimization and Spatially Constrained Multivariate Clustering Analysis," Land Use Policy, Elsevier, vol. 119(C).
    3. Sidong Zhao & Kaixu Zhao & Ping Zhang, 2021. "Spatial Inequality in China’s Housing Market and the Driving Mechanism," Land, MDPI, vol. 10(8), pages 1-33, August.
    4. Duran, Hasan Engin & Özdoğan, Hilal, 2020. "Asymmetries across regional housing markets in Turkey," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    5. Sisman, S. & Aydinoglu, A.C., 2022. "A modelling approach with geographically weighted regression methods for determining geographic variation and influencing factors in housing price: A case in Istanbul," Land Use Policy, Elsevier, vol. 119(C).

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