Examining the effect of apartment attributes on their sale prices in Riyadh, Saudi Arabia

Hedonic regression is used to investigate the influence of various attributes on the apartment sale prices in Riyadh, Saudi Arabia. 592 apartments were sampled from online sale advertisements during early 2019. Relevant internal attributes such as apartment age and floor area were recorded during the sampling process. Apartments were then mapped using ArcGIS to account for apartments’ external attributes such as proximity to commercial centers and metro stations. Adopting a semi-log regression model (where the dependent variable, sale price, is log transformed) provided more explanatory power than regular linear regression. Internal attributes that had a positive relationship with the price were floor area, furnishings, the availability of yards and elevators, while attributes such as building age, the floor level of the apartment influenced prices negatively. As for external attributes, proximity to expressways, colleges, hospitals and future metro stations influenced prices positively, while the effect of proximity to hypermarkets and malls was positive only in the linear hedonic model. Among three probable Central Business Districts (CBDs) in Riyadh, Olaya district had the strongest positive influence on apartment prices. Proximity to the King Abdullah Financial District (KAFD) was positively associated with prices. However, contrary to what’s expected, proximity to the downtown (the traditional and formally recognized city center of Riyadh) negatively influenced the prices.