Determining Housing Prices Using The Semiparametric Estimation Within The Hedonic Price Model Framework: Case Study of Istanbul Housing Market Example

Abstract

Different properties of the houses have given heterogeneous structure to the housing markets. Therefore, the housing market can be analyzed with the hedonic price model In this direction, this study is important in terms of revealing the effects of different characteristics of houses on housing prices to follow the price changes in the housing market. The study aims to examine the effect of flat-type residential properties in İstanbul on the price within the scope of hedonic price model. For this purpose, estimation was made with semiparametric regression models for 974 flat-house, housing prices and factors affecting prices. In as much as the semiparametric estimation is superior to parametric estimation in that it doesn’t force the data set to certain assumptions and takes into account the variable structure that has a nonlinear effect on the dependent variable. According to the findings, the properties that affect the housing prices (apartment) for sale are determined as the parking variable, credit eligibility variable, and elevator variable respectively. As for the nonparametric variables, it was concluded that the square meter variable had a reducing effect on house prices after 400 m2, and the age of housing had a positive effect on prices after 15 years.

Keywords

• i̇stanbul konut piyasası
• hedonik fiyat modeli
• nonparametrik yaklaşım
• semiparametrik tahmin
• istanbul housing market
• hedonik price model
• nonparametric approach
• semiparametric estimation