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.

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This paper focuses on the everyday travel behaviour of immigrants in Germany. We use data from an empirical study conducted in Offenbach am Main, a city with one of the highest immigrant populations in Germany. We compared the travel behaviour of immigrants and their direct offspring to that of Germans without an immigration background. Compared to non-immigrants, immigrants own fewer cars or bicycles per household, and they were also less likely to be able to ride a bicycle or to drive a car and to have access to these modes of transport. For both groups, the most important transport mode is the private car. Immigrants, especially women, use public transport and ride in a car as a passenger on a regular basis more frequently than non-immigrants. Riding a bicycle tends to be a typical transport mode for non-immigrants, especially for men. We used logistic regression models to identify, in addition to gender and immigration status, factors that influenced the regular use of car (as driver), public transport, and bicycle. These factors include, for example, income, car ownership, household composition, education and socialisation. Our results shed some light on the travel behaviour of immigrants in Germany, but we also emphasize the need for further research to deepen our understanding of the travel behaviour of immigrants in Germany.

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