Local particularities or distance gradient: what matters most in the case of the Viennese apartment market?

Purpose - This study aims to examine the impact of relative importance of local characteristics, distance from the city centre and unobservable spatial relation in explaining values of constant-quality apartment units in Vienna. Design/methodology/approach - Drawing on recent developments in spatial econometrics and spatial hedonic house price modelling, the rent gradient hypothesis is examined by means of hedonic regression and spatial hedonic regression. Spatial autocorrelation tests are applied in order to assess possible presence of spatial dependence. The authors borrow Florax et al.\u27s specification search strategy in order to choose the most appropriate spatial model specification. Findings - This research shows that local characteristics - or particularities - proxied by district and distance from the city centre are important location variables with regard to the Viennese apartment market. The spatial analysis suggests that the apartment prices are spatially autocorrelated and the Viennese apartment market has a distance-based neighbourhood structure. The main finding is, however, that residents are willing to bid more for constant-quality apartment units that are close to the centre of the city. Originality/value - Rent gradient hypothesis is usually tested within non-spatial hedonic frameworks: this study estimates a spatial hedonic model additionally in order to allow for comparison of results. This is also the first article to apply recent developments in spatial econometrics to examine explicitly rent gradient theory in the context of the Viennese apartment market