Factors affecting housing prices in Izmir, Turkey: a quantile regression approach

Abstract

Purpose The purpose of this paper is to investigate empirically the main factors that affect the house prices in Izmir, Turkey using the quantile regression and ordinary least square approaches. Design/methodology/approach Sample data about the housing market for Izmir collected from the web pages of various real estate agencies during June 2018. Following this, the quantile regression method is used to estimate all possible effects of variables on each interested quantile to determine the factors that affect house prices to guide the potential consumers, house developers, city planners and the policymakers in Izmir, Turkey. Findings Results show that the age of the house, central heating and parking have no significant effect on prices. The size of the house, the existence of an elevator, fire and security have a positive and significant effect on prices. The number of rooms has lower values for high-priced houses, while the floor, the number of balconies, air conditioning, proximity to schools have a higher value for high-priced houses. The number of toilets, the number of bathrooms and the distance to the hospital have a lower value on the high-priced housing. The value of the distance from the city center and the shopping center is almost uniform in all quantiles and lowers the value of the higher-priced houses. With the exception of the value of the houses in the 10th percentile in Balcova district, the value of the houses in Konak, Balcova and Narlidere is lower prices in Karsiyaka. Originality/value This is the first comprehensive research to determine the major factors that affect house prices in Izmir. The second contribution of this paper is that it includes all possible variables and accordingly derives adequate policy implications, which could be used both by the public housing authority and private housing constructing companies in designing and implementing effective housing policies.

Study of factors influencing apartment prices in Prishtina, Kosovo

“…Moreover, Yusof and Ismail (2012) found that location-related attributes have the strongest effect on property prices. Finally, Özsoy and Şahin (2021) are of the same opinion that location has a uniform impact on apartment prices. This finding has an implication for real estate developers and investors in Prishtina, who should understand that Prishtina is a mono-centric city and that any distance from the city center affects the prices of the apartments.…”

“…In like manner, size is an important structural variable in property prices (Aziz et al , 2020). Above all, Özsoy and Şahin (2021) in their study found that the size of the house, the existence of an elevator, fire and security have a positive and significant effect on prices. Finally, the size and age of the building are considered to be important structural attributes affecting apartment prices (Shetty et al , 2020).…”

“…To this end, Aziz et al (2020) argue that distance to the inner center is a key locational attribute. Likewise, Özsoy and Şahin (2021) using the quantile regression approach found that distance from the center has a uniform impact on the property prices in all quantiles of the Balkova district in Izmir, Turkey. Finally, Shetty et al (2020) using multiple regression analysis found that location is the key determinant of property prices in India.…”

“…In this regard, in their study, Candas et al (2015) found that floor is an important factor influencing property prices. Likewise, the floor is found to be an important factor influencing high-priced houses in Izmir, Turkey (Özsoy and Şahin, 2021). Similiarly, Shetty et al (2020) found the floor to be an important determinant of apartment prices.…”

Nonlinear Influence of Public Services on Urban Housing Prices: A Case Study of China

“…In terms of medical care, Wang et al's [24] research on several megacities in China finds that hospitals near communities are positively correlated with housing values; the farther away from the hospital, the lower the value of the house [25].…”