AN ANALYSIS ON THE RELATIONSHIP BETWEEN HOUSING VALUES AND HOUSE-SPECIFIC FACTORS AND ITS NEIGHBOURING AMENITIES IN TURKEY

Yıl 2019, Cilt: 7 Sayı: 1, 65 - 75, 30.04.2019

Büşra Gezikol Sinan Esen Hakan Tunahan

https://doi.org/10.22139/jobs.510405

Öz

In the twentieth century, the societies have been transformed from a predominately agricultural society to an industrial and knowledge based economy centered in metropolitan cities.  And people have adopted a crowded and auto-centric life. This new system has enabled the creation of new high welfare segments in the societies by increasing the asset prices rapidly, and generated important opportunities in the socio-economic area.   

However, rapid urbanization has also led to distorted urbanization. One of the trends in response to this chaos is New Urbanism Approach. As a result of New Urbanism and similar movements, city planning has become important and practices which simplify and enrich the lives of residents have been implemented through legal regulations. These regulations and approaches have led to the addition of new ones to the factors affecting the prices of housing in the cities. One of these factors is the possibility of walking to daily living activities such as schools, stores, parks and libraries. These facilities which can be measured by various instruments used in developed countries have an increasing importance in determining the housing price.

The housing sector has an important engine in the economic growth of the countries. For this reason, the decision-makers closely follow the construction sector and the housing market and keep the market alive in case of stagnation risk by decreasing tax, interest and transaction fees. But it has been observed that walkability as a factor causing price increases is addressed as a variable in a limited way. Therefore, the aim of this study is to examine the effect of walkability and other specific factors on housing prices. 

The cities have become more walkable and in this way, it has become important for the city residents to reach the living spaces and social areas.  This situation has become particularly essential in housing prices. There are many factors affecting walking and walkability. Especially, socio-demographic characteristics play a key role. For example, residents with more mobility options are more responsive to amenities around them, and are more sensitive than those with fewer options (Manaugh and El‐Geneidy, 2011: 312). In addition, the value of walkability is influenced by pedestrian collision, the ability to connect to streets, length of pavements, speed limit and similar factors (Li et. al., 2014: 162). Walkability of cities is measured by various walkability indices. 

There are also studies about walkscore which is a new and most widely used dynamic that affects housing prices and is used to measure walkability. Cortright (2009), Manaugh and El-Geneidy (2010), Duncan et al. (2011), Rauterkus and Miller (2011) and Pivo ve Fisher (2011) have published many studies about walkscore and housing prices which one of the variables of this study. These studies show that walkscore has a positive effect on housing prices. Cortright (2009), Rauterkus and Miller (2011) focus their studies on walkscore how and to what extent the housing prices will increase. Pivo and Fisher (2011) in their differentiated study discuss the walkscore relationship with the prices of commercial workplaces.

This study aims to examine the effect of walkability, measured by Walkscore, and the age of the house, the square meter of the apartment, the floor of the apartment, the income of the district on the housing price. For this purpose, 2109 houses for sale ads in 29 district of Istanbul which are published on the website of a well-known company that provides real estate services globally has been evaluated for the period of 1-15 August 2018. Subsequently, a model has been created in which the housing price is dependent variable, the walk score index, the age of the house, the square meter of the apartment, the floor of apartment and the income of the district are independent variables. Information about the price, age, square meter and floor of the house has been obtained from the ads. The data related to the income of the district is collected from the results of the Mahallem Istanbul project (http://www.mahallemistanbul.com/) conducted by Istanbul University Faculty of Economics with the support of Istanbul Development Agency. The data for walkability variable is obtained from walkscore.com.

Walkscore measures walkability on a scale from 0 to 100 depending on walking routes to places such as groceries, schools, parks, restaurants and shops. It calculates the walking distance of each address (housing, workplace, any location) to the social facilities (park, school, etc.) and assigns a walking value between 0 and 100. 

Although there are many studies in the literature that examined the relationship between walkability and the housing prices, it hasn’t observed a study in Turkey about this issue. The results are in parallel with the results in the literature. According to this, housing prices are increasing as the walkability increases. On the other hand, according to the findings, the effect of the house age, the square meter of the apartment, the floor of apartment, the income of the district on the housing prices is remarkable. 

The findings are indicative for policy makers, sector representatives and housing demanders:

The finding on the relationship between the age of house and the housing price can be used as an indicator for determining the annual depreciation value of the houses in Istanbul. In addition, the home owner may make an analysis over rent value/housing price. Also, the square meter-price relationship can be an indicator for the determination of the sales prices of the companies in the construction sector, and the optimum size of the houses to be produced. Furthermore the relationship between the income of the region and the housing prices is very important in terms of showing the effect of the rent obtained as a result of the increase in housing prices on income distribution.

The analyses are based only on the prices of the houses in Istanbul and the ads given in a limited time period. In this context, it is suggested that data can analyzed for a wider time frame for whole Turkey.

Anahtar Kelimeler

Construction Industry, Housing Prices, Walkscore

TÜRKİYE’DE KONUT DEĞERİ İLE KONUT VE YAKIN ÇEVRESİNE ÖZGÜ FAKTÖRLERİN İLİŞKİSİ ÜZERİNE BİR ANALİZ

Öz

Amaç: Bu çalışma, temel olarak çoğunlukla konut fiyatlarında, konutun çevresindeki günlük yaşam aktivitelerine yürüyerek erişebilirliğin etkili olup olmadığını incelemeyi amaçlamaktadır. Bu amaç doğrultusunda konuta özgü diğer faktörlerin fiyat üzerindeki etkisi de tespit edilmeye çalışılmıştır.

Yöntem: Global olarak gayrimenkul hizmeti veren tanınmış bir firmanın web sitesinde yer alan İstanbul’un 29 ilçesinin 2109 satılık ev ilanındaki konut fiyatları ile Yürünebilirlik Skoru (Walkscore), binanın yaşı, dairenin metrekaresi, bulunduğu kat ve ilçenin geliri arasındaki ilişkiye yönelik En Küçük Kareler yöntemi ile analiz yapılmıştır.

Bulgular: Sonuçlar, konut fiyatları üzerinde yürüyüşe elverişliliğin anlamlı bir etkisi olduğunu göstermektedir. Ev fiyatlarında etkili olan diğer faktörlere yönelik de anlamlı etkiler tespit edilmiştir.  

Sonuç: Yapılan analizler sonucunda, konut çevresinde günlük yaşam aktivitelerine yürüme erişilebilirliğinin konut fiyatları üzerinde önemli bir etkisi olduğu tespit edilmiştir. Ek olarak, yapılan analizde, bina yaşı, dairenin metrekaresi, kat ve ilçe geliri gibi diğer faktörlerin etkisinin, aynı modelde konut fiyatlarını farklı düzeylerde etkilediği gösterilmiştir.

Anahtar Kelimeler

İnşaat Sektörü, Konut Fiyatları, Walkscore

Kaynakça

• Bayer, P., Ferreira, F., and McMillan, R. (2007). A unified framework for measuring preferences for schools and neighborhoods. Journal of political economy, 115(4), 588-638.
• Chau, K. W., and Chin, T. L. (2002). A critical review of literature on the hedonic price model. International Journal for Housing Science and Its Applications 27 (2), 145-165
• Chin, H. C., and Foong, K. W. (2006). Influence of school accessibility on housing values. Journal of urban planning and development, 132(3), 120-129.
• Congress for the New Urbanism. https://www.cnu.org/who-we-are/charter-new-urbanism, (31.12.2018).
• Cortright, J. (2009). Walking the walk: How walkability raises home values in US cities.
• Court. AT. (1939). Hedonic price indexes with automotive examples in The Dynamics of Automobile Demand: General Motors, New York.
• Damigos, D., and Anyfantis, F. (2011). The value of view through the eyes of real estate experts: A Fuzzy Delphi Approach. Landscape and Urban Planning, 101(2), 171-178.
• Duncan, D. T., Aldstadt, J., Whalen, J., Melly, S. J., and Gortmaker, S. L. (2011). Validation of Walk Score® for estimating neighborhood walkability: an analysis of four US metropolitan areas. International journal of environmental research and public health, 8(11), 4160-4179.
• Grether, D. M., and Mieszkowski, P. (1974). Determinants of real estate values. Journal of Urban Economics, 1(2), 127-145.
• Huang, D. J., Leung, C. K., and Qu, B. (2015). Do bank loans and local amenities explain Chinese urban house prices? China Economic Review, 34, 19-38.
• Hui, E. C., Chau, C. K., Pun, L., and Law, M. Y. (2007). Measuring the neighbouring and environmental effects on residential property value: Using spatial weighting matrix. Building and environment, 42(6), 2333-2343.
• Jane, J. (1961). The Death and Life of Great American Cities. New-York, NY: Vintage.
• Jim, C. Y., and Chen, W. Y. (2006). Impacts of urban environmental elements on residential housing prices in Guangzhou (China). Landscape and Urban Planning, 78(4), 422-434.
• Jim, C. Y., and Chen, W. Y. (2010). External effects of neighborhood parks and landscape elements on high-rise residential value. Land Use Policy, 27(2), 662-670.
• Jud, G. D., and Watts, J. M. (1981). Schools and housing values. Land Economics, 57(3), 459-470.
• Lancaster, K. J. (1966). A new approach to consumer theory. Journal of political economy, 74(2), 132-157.
• Li, W., Joh, K., Lee, C., Kim, J. H., Park, H., and Woo, A. (2014). From car-dependent neighborhoods to walkers' paradise: estimating walkability premiums in the condominium housing market. Transportation Research Record: Journal of the Transportation Research Board, (2453), 162-170.
• Mahallem İstanbul. http://www.mahallemistanbul.com/, (31.12.2018).
• Manaugh, K., and El-Geneidy, A. (2010, November). Who benefits from new transportation infrastructure? Evaluating social equity in transit provision in Montreal. In 57th Annual North American Meetings of the Regional Science Association (Vol. 20, No. 0).
• Manaugh, K., and El-Geneidy, A. (2011). Validating walkability indices: How do different households respond to the walkability of their neighborhood?. Transportation research part D: transport and environment, 16(4), 309-315.
• Pivo, G., and Fisher, J. D. (2011). The walkability premium in commercial real estate investments. Real Estate Economics, 39(2), 185-219.
• Rauterkus, S. Y., and Miller, N. (2011). Residential land values and walkability. Journal of Sustainable Real Estate, 3(1), 23-43.
• Rosen, S. (1974). Hedonic prices and implicit markets: product differentiation in pure competition. Journal of political economy, 82(1), 34-55.
• Tyrväinen, L., and Miettinen, A. (2000). Property prices and urban forest amenities. Journal of environmental economics and management, 39(2), 205-223.
• Walkscore. https://www.walkscore.com/methodology.shtml, (31.12.2018).