HEDONIC MODELING OF OFFICE RENTS WITH SEMIPARAMETRIC GEOADDITIVE APPROACH: A CASE OF ISTANBUL OFFICE MARKET

This study aims to establish a hedonic model for office space rents in Istanbul using dataset of 2348 spaces. The includes information on and building characteristics, as well lease, locational, neighborhood characteristics that influence rent. To analyze the relationship between rent these determinants, we utilized semiparametric geoadditive allows functional form flexibility captures locational effects through geographical smoothing functions instead dummies. Our findings suggest determinants is nonlinear nonparametric part model. Among vacancy rate - proxy demand has greatest impact rents. second most effective determinant Class A, an indicator quality, third possession Bosporus view.