Konut Fiyatlarının Mekânsal Kantil Regresyon Yaklaşımına Göre Modellenmesi: Denizli İli Örneği (Modelling of Housing Prices by Spatial Quantile Regression Approach: A Case of Denizli Province)

The aim of the study is to examine the relationships between housing prices and characteristics by spatial quantile regression approach within the framework of hedonic price theory. In the period of May-June 2019, 3666 units of housing data for sale were obtained from the central districts for the Denizli housing market and it was aimed to provide information regarding the demand direction of the Denizli housing market. According to the estimation results of spatial quantile regression, the effects of structural, physical and locational housing characteristics on the housing prices change for the quantiles with the highest and lowest housing prices. One of the remarkable findings of the study is that an increment in the prices of neighboring houses for different segments of the distribution of housing asking prices increases the housing prices at different rates. The housing prices in neighbor locations most affect positively the housing prices at the bottom of 25th quartile. Consequently, determining the characteristics that increase and decrease the housing prices for different segments might implicitly provide information about the housing preferences of households with different income levels.