Investigation of housing valuation models based on spatial and non-spatial techniques

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Date

2015

Author

Boza, Ertuğrul

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The aim of this thesis is to develop hedonic housing valuation models based on spatial (SAR-simultaneous spatial autoregression and GWR - geographically weighted regression) and non-spatial (OLS - ordinary least squares) techniques, to compare the performances of these models and to investigate significant factors affecting housing value. The developed housing valuation models were tested at the Çankaya and Keçiören districts of Ankara province, Turkey. The results of the analyses revealed that significant spatial non-stationarity exists between the dependent and independent variables. A semi-logarithmic hedonic model was used in order to interpret the coefficients easily and minimize the problem of heteroscedasticity. The results show that Area, Security and Distance to Shopping Center are common significant factors for both Çankaya and Keçiören districts in Ankara. Other important factors are the Type of Property and Distance to Subway for Çankaya and the Floor and Household variables for Keçiören. The SAR and the GWR spatial models gave a better approximation to the observed house values than the traditional non-spatial regression model. The SAR model showed the best performance in Çankaya and the GWR model indicated high performance in Keçiören. The GWR maps displayed the variation of the coefficients of each variable clearly.

Subject Keywords

Housing, Housing, Geospatial data., Geographic information systems.

URI

http://etd.lib.metu.edu.tr/upload/12618846/index.pdf
https://hdl.handle.net/11511/24722

Collections

Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

E. Boza, “Investigation of housing valuation models based on spatial and non-spatial techniques,” Ph.D. - Doctoral Program, Middle East Technical University, 2015.