Housing valuations in Germany (part 1)

How is the German housing market doing? This morning, Zeit-Online reported results of a recent survey suggesting that most people looking for houses consider a price range of between EUR 200,000 and EUR 400,000. The price range aligns relatively well with German median income, yet, it is difficult to find housing in that price range close to the big cities (the article portrays a family that is willing to take on a 2 hour daily commute to find housing that price range).

To get a sense of valuations, I’m starting a series of posts about housing in Germany. I focus on apartments rather than houses (the apartment market seems more liquid and has more observations of listings).

In the first post, I am trying to get a quick sense of how much apartment rents are driven by apartment characteristics versus location characteristics. I start with a simple model of monthly apartment rent as a function of living space, the number of rooms, whether or not the apartment has a balcony, a garden or a kitchen. The idea is that the above apartment characteristics (to the extent available) can be viewed as fundamentals and are unrelated to location characteristics. Of course, location is important and can also provide quality of life. You can think of this post as trying to decompose rents in a part given by apartment quality and a part that might reflect location quality.

I omit the model details here, but the model explains about 70% of the variation in apartment rents. For each apartment, I compute the fundamental apartment rent as the prediced value from my model above.

The figure below shows the distribution of actual rent and rent based on fundamental value. As one can see, fundamental rent is often higher than actual rent.

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How is this difference between actual and fundamental rent distributed across regions? The figure below shows results. In particular, it shows by how much actual rent deviates from fundamental rent (in percent). Positive values mean actual rent is above fundamental rent and negative values mean the opposite.
Not surprisingly, renting in cities is more expensive conditional on fixed apartment characteristics. You can clearly see Munich, Frankfurt, Stuttgart, Cologne and Berlin on the map.

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Which are the cities with the highest share of apartments that are listed at least 50% above fundamental value? The top 25 are in the table below and they do include the usual suspects, in particular Munich and its surrounding region. It’s interesting to note that Cologne appears to have a much higher share of those fundamentally overvalued apartment listings than its neighboring city Dusseldorf. Does that suggest higher quality of life in Cologne?

##                               City ShareMorethan50
## 1                          München            0.76
## 2                  München (Kreis)            0.48
## 3                Starnberg (Kreis)            0.48
## 4         Fürstenfeldbruck (Kreis)            0.47
## 5                Frankfurt am Main            0.45
## 6                        Stuttgart            0.44
## 7                  Lörrach (Kreis)            0.43
## 8                            Fürth            0.35
## 9                       Heidelberg            0.35
## 10                            Köln            0.35
## 11                  Dachau (Kreis)            0.34
## 12                Miesbach (Kreis)            0.33
## 13                        Nürnberg            0.33
## 14                          Berlin            0.31
## 15                        Würzburg            0.31
## 16               Ebersberg (Kreis)            0.29
## 17                      Ingolstadt            0.29
## 18                      Regensburg            0.28
## 19                         Hamburg            0.27
## 20                      Düsseldorf            0.24
## 21                       Karlsruhe            0.23
## 22 Bad Tölz-Wolfratshausen (Kreis)            0.22
## 23                        Erlangen            0.22
## 24                         Münster            0.22
## 25               Oberhavel (Kreis)            0.22