Hedonic Analysis of Price in the Istanbul Housing Market

Abstract

The purpose of this paper is to explore the factors that affect housing prices in Istanbul. A hedonic price model is employed in order to examine housing price determinants with respect to property characteristics, socio‐economic characteristics, neighbourhood quality characteristics, and locational factors. The results reveal that housing prices are affected by these factors: living area size, being in a low storey building, being in a secured site (with swimming pool and garage), and age of the building. In addition to these determinants, the length of time the inhabitants have lived in Istanbul, the average income of the household, neighbour satisfaction and earthquake risk of the area have effects on the residential prices in Istanbul. Further research is suggested by constructing a second model that includes neighbourhood dummy variables as a proxy for submarkets, and a multi‐level modelling framework will be employed in order to analyse the urban housing submarket system. Santrauka Šiame darbe siekiama išnagrinėti veiksnius, kurie daro įtaką būsto kainoms Stambule. Pa si tel kus hedoninį kainų modelį, tyrinėjami būsto kainas lemiantys veiksniai, atsižvelgiant į nekilnojamojo turto charakteristikas, socialinius-ekonominius veiksnius, apylinkių kokybės bruožus ir vietos veiksnius. Rezultatai rodo, kad būsto kainoms įtaką daro tokie veiksniai: gy ve namosios teritorijos dydis, pastato aukštingumas, buvimas sklype ir pastato amžius. Be šių veiksnių, būsto kainas Stambule veikia ir laikas gyventas mieste, vidutinės namų ūkio pajamos, patinkantys kaimynai bei žemės drebėjimų rizika toje terito ri jo je. Siūloma atlikti tolesnius tyrimus, suformuojant antrą fi ktyviuosius apylinkių kintamuosius apimantį modelį, kuris bus taikomas kaip subrinkų pakaitalas, o naudojant daugialypę modeliavimo struktūrą bus siekiama išanalizuoti miesto būsto subrinkos sistemą.

Defining spatial housing submarkets: Exploring the case for expert delineated boundaries

“…This form was preferred to log-log and semi-log variants on the basis that it produced parameter estimates that were consistent with prior theory, a parsimonious equation that provided the best fit to the data and achieved the strongest performance on standard diagnostic tests. The superiority of the linear model over non-linear specifications is unusual but not unique (Keskin, 2008;Palmquist, 1984). The estimated parameters explain 61 per cent of the variation in house price levels which, although modest, falls within the normal range for reported hedonic models (Malpezzi, 2003).…”

Hedonic Modeling for a Growing Housing Market: Valuation of Apartments in Complexes

“…Furthermore, variables such as the number of rooms, house size, availability of parking spaces and presence of ponds tended to have a price-increasing effect; however, being outside of the downtown area affected the price adversely. Keskin (2008) and Caglayan and Arikan (2009) both studied housing prices in Istanbul by taking the metropolitan area as a single market. Keskin, including socio-economic and neighborhood quality characteristics into her analysis, reported that the average income of the household, the length of time they lived in Istanbul and neighbor satisfaction increased the price while earthquake risk of the area decreased it.…”

Housing Choice Structure: Examples of Two Different-Size Cities From Turkey

“…In the IMA, housing market is spatially segmented (Alkay 2008;Keskin 2008). Consequently, the changes in the market values seem to greater in the metropolitan area (Koramaz, Dökmeci 2012).…”