This thesis considers a statistical model for the apartment rent price per square meter (rent sqm) in Germany. The topic of apartment rent prices in Germany became relevant in major German cities since there is a strong increase in rent prices and in particular, the development of new apartment buildings is lacking. A data, collected by the FDZ Ruhr at RWI (and ImmobilienScout24) institution, is analyzed in this research. The data consists of 2.6 million apartments and 59 variables. We focus on the most relevant 31 variables such as ”the additional cost”, ”heat cost”, ”living space”, etc., and the cities Munich and Berlin for two time periods: 2015 and 2019. This will enable us to compare the behavior of rent sqm prices in both cities at two different time periods. Once we have done an exploratory data analysis to identify the significant covariates and useful model formulation, we decide to fit a multiple linear regression model (LM). The final fitted model also includes interaction terms between the variables. To assess model fit, we use the adjusted multiple coefficient of determination (R2adj) and the analysis of variance (ANOVA) ratio test to measure the fit and the complexity of the model, respectively. After we have found a suitable model, we use it for prediction within different scenarios. The results show that rent price per square meter is exponentially increasing over time in Munich and Berlin. Further, Munich has higher rent prices than Berlin. When a pet is allowed, it decreases the rent price per square meter in both cities, while Upscale furnishing apartments as well as apartments with a parking space increase rent sqm in both cities. In Berlin, rent sqm increases with respect to the order of the energy efficiency categories (Low, Medium, and High) as well as the order of the number of bedrooms (0-1, 2,>2) in both time periods. However, in Munich, rent sqm decreases in this order. Furthermore, the rent price per square meter decreases when renting larger apartments in Munich, whereas, in Berlin, this is not the case. Considering the predictions with our four scenarios: scenario 1 (smaller), scenario 2 (small), scenario 3 (large) and scenario 4 (larger) apartments, the rent sqm increased from 2015 to 2019 in Berlin by 8.70%, 38.16%, 29.16%, and 69.47%for smaller, small, large, and larger apartments. In Munich, on the other hand, rent sqm increased in the same period of time by 1.84%, 9.27%, 70.71%, and 60.13%, respectively. Also, in Berlin 2015, the rent sqm increased from scenario 1 to scenario 2, scenario 1 to scenario 3, and scenario 1 to scenario 4 by 36.31%, 54.35% and 67.73%, respectively, while, in Munich 2015, rent sqm decreased by 8.11%, 10.69% and 18.66%, respectively. Munich 2019, however, shows a different trend. The rent sqm decreased by 1.40% from scenario 1 to scenario 2 and increased by 49.70% and 27.89% from scenario 1 to scenario 3 and scenario 1 to scenario 4, respectively.     «

This thesis considers a statistical model for the apartment rent price per square meter (rent sqm) in Germany. The topic of apartment rent prices in Germany became relevant in major German cities since there is a strong increase in rent prices and in particular, the development of new apartment buildings is lacking. A data, collected by the FDZ Ruhr at RWI (and ImmobilienScout24) institution, is analyzed in this research. The data consists of 2.6 million apartments and 59 variables. We focus on...     »