Residential housing prices: impact of housing characteristics, accessibility and neighbouring apartments – a case study of Dortmund, Germany

In this research we analyse the most important factors that determine housing prices. On the one hand, we test whether neighbourhoods with a good accessibility are more attractive and consequently show higher housing prices. For this purpose, we introduce an adapted Walk Score as part of the accessibility indicators. On the other hand, we compare an ordinary-least-squares regression (OLS) and a spatial lag model and test which model better explains residential housing prices. The regression models show the importance of classical factors such as dwelling characteristics or the types of neighbours. In addition, they also reveal that a differentiated approach is needed for analysing the accessibility, the location and the environment of a dwelling. The mere presence of a single amenity, a public transport stop or a motorway access is not a sufficient explanatory factor. Information such as density of supply, walking distances or public transport service quality needs to be taken into account as well as. The test of the spatial lag model reveals that prices of the most proximate dwellings can be taken into account as a relevant factor in explaining residential housing prices and should therefore be included in research on residential housing prices.