Hedonic analysis of price in the Istanbul housing market.

In this research, it is aimed to find out the determinants of the housing prices in Istanbul. A market-wide hedonic price model is employed by taking into property characteristics, socio-economic characteristics, neighbourhood quality characteristics and locational characteristics. The dataset used for this hedonic model is composed of two dataset. The data of property characteristics is provided from two major real estate agent's websites and this data set contains 2,175 transactions of single-family homes sold in Istanbul in November 2006 and in April. The second dataset provides information about the socio-economic and the neighbourhood quality characteristics. This dataset is derived from a survey that was undertaken by Istanbul Greater Municipality. The data of the locational characteristics such as travel time to jobs, schools and shopping areas (or centres) are taken from the second data set. The earthquake risk percentage measurement which is one of the most important locational characteristics is taken into account from predictions by the JICA (Japanese Agency for International Cooperation) (IBB, 2007).

The results of the hedonic model suggest that the housing price is determined by four types of characteristics: property, socio-economic, neighbourhood quality and locational characteristics. Among the property characteristics, living area being in a low storey building, being in a secured site (with swimming pool and garage), are found to have a positive impact on housing value. On the contrary to most studies on housing prices, age has a counterintuitive sign. Such similar results for Istanbul were found by Ozus et al. (2007) and Onder et al. (2004). Among the socio-economic characteristics, the length of time the inhabitants have lived in Istanbul, average income of the household and neighbour satisfaction, as a variable in the behaviour characteristics, have positive impacts on housing value. As expected, earthquake risk as a locational variable with a negative impact.

The results of this study also display the demand side preferences so that these can be used as a guide to improve the understanding within the supply side and investors. In addition to supply side and investors, policy makers and urban planners can use the results in order to analyze housing market behaviour.

For further studies, a second model will be employed, which includes neighbourhood dummy variables as a proxy for submarkets, and a multi-level modelling framework as the main analytical tool. The results of this can then be compared to those generated by two different forms of the standard hedonic model. The comparative analysis focuses on the estimated coefficients, significance and explanatory power of the models. Furthermore, the spatial pattern of the residuals will be explored and GIS techniques will be used to systematically examine the weaknesses of the different modelling approaches.

ACKNOWLEDGEMENTS

I would like to thank two anonymous referees and Dr. Tom Kauko for their helpful, constructive comments. I am grateful to my PhD supervisor Dr. Craig Watkins who provided valuable suggestions that considerably improved this paper and the research. Any errors are naturally my own responsibility.

Received 9 January 2008; accepted 27 March 2008

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Berna KESKIN

Department of Town and Regional Planning, University of Sheffield, Western Bank, Sheffield, S10 2TN, United Kingdom E-mail: trp05bk@shef.ac.uk

SANTRAUKA

STAMBULO BUSTO RINKOS KAINY HEDONINE ANALIZE

Berna KESKIN

Siame darbe siekiama isnagrineti veiksnius, kurie daro itaka busto kainoms Stambule. Pasitelkus hedonini kainu modeli, tyrinejami busto kainas lemiantys veiksniai, atsizvelgiant i nekilnojamojo turto charakteristikas, socialinius-ekonominius veiksnius, apylinkiu kokybes bruozus ir vietos veiksnius. Rezultatai rodo, kad busto kainoms itaka daro tokie veiksniai: gyvenamosios teritorijos dydis, pastato aukstingumas, buvimas sklype ir pastato amzius. Be siu veiksniu, busto kainas Stambule veikia ir laikas gyventas mieste, vidutines namu ukio pajamos, patinkantys kaimynai bei zemes drebejimu rizika toje teritorijoje. Siuloma atlikti tolesnius tyrimus, suformuojant antra fiktyviuosius apylinkiu kintamuosius apimantj modeli, kuris bus taikomas kaip subrinku pakaitalas, o naudojant daugialype modeliavimo struktura bus siekiama isanalizuoti miesto busto subrinkos sistema. Table 1. Descriptive statistics of housing units for Istanbul transaction data N: 2175

Minimum Maximum Price 34013.60 8,000,000 Age 0 150 Area 45 1920 Room 1 15 Total storey 1 27 Flat 0 1 Detached 0 1 Elevator 0 1 Garden 0 1 Balcony 0 1 Garage 0 1 Security 0 1 Swimming pool 0 1