SPATIAL HETEROGENEITY IN ISTANBUL HOUSING MARKET: A GEOGRAPHICALLY WEIGHTED APPROACH

Year 2020, , 298 - 307, 31.12.2020

Orcun Moralı Neslihan Yılmaz

https://doi.org/10.17261/Pressacademia.2020.1304

Abstract

Purpose - This study examines and documents spatial heterogeneity in Istanbul housing market using Geographically Weighted Model (GWR).
Methodology - A GWR model with a Gaussian kernel and an adaptive bandwidth based on cross-validation is employed on a cross-sectional housing listing data set. Additional analysis is provided using geographically weighted Spearman’s rank correlation measure between prices and variables.
Findings- GWR model substantially boosts goodness of fit in our pricing model compared to a standard hedonic regression model. The variation within GWR coefficients is high and of micro nature. Median GWR coefficients often differ from standard hedonic regression coefficients. The variability of coefficients is plotted on map.
Conclusion- Findings suggest the existence of spatial non-stationarity in standard hedonic regressions and favor the use of models appropriate for spatial heterogeneity. Findings encourage further research in hedonic models applications such as in quality adjustments to price indices.

Keywords

Spatial heterogeneity, spatial non-stationarity, geographically weighted regression, Istanbul housing market, quality adjusted price index

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