Description:
This paper introduces new real estate price indices for 18 major German cities and their neighborhoods (Stadtbezirke) as well as a new composite indicator for the German housing market - the German Real Estate Index (GREIX). The series are constructed on the basis of long-run transaction level data from the Gutachteraussch¨ usse. The novel data set marks a significant advancement in promoting transparency in the German real estate market and provides researchers with an unparalleled resource to study housing market dynamics in Germany. We highlight five core insights: 1. The new indices underscore the shortcomings of existing housing price indices that tend to be unsuited to capture price cycles at higher frequency. Only the transaction level data provide a reliable reading of housing market trends at high frequencies. 2. The neighborhood data, for the first time, allow to track substantial polarization of housing markets within and across cities over the past decades. The price gap between the most and least expensive neighborhoods in Germany has more than doubled over the past 30 years, while the price gap between the most and least expensive city in our sample has almost tripled over the same period. 3. Despite the current downturn, German home owners have witnessed considerably wealth gains during the decade-long housing boom. The best performing city since 2000 was Berlin with cumulative gains after inflation of 160%. In particular homeowners in Hamburg-Eppendorf, Munich-Maxvorstadt and Berlin-Kreuzberg registered real price increases of more than 180%. For a typical 100 square meter apartment in Berlin, the associated rise in real wealth amounts to approximately 300.000 Euros. 4. Since 2022, rising interest rates have triggered a pronounced correction in the German real estate market that is still under way. In inflation-adjusted terms, some cities have already seen price drops in the vicinity of 20%, for the country as a whole prices are down by close to 15% from peak in inflation-adjusted terms, and close to 8% in nominal terms. 5. We build a state-of-the-art dynamic factor prediction model to nowcast Q2 price developments on the basis of available data. The data point to further weakness ahead, but the pace of the decline appears to be moderating. Prices are likely to decrease by additional 2% in nominal terms, bringing the decline from peak to 19% in inflation-adjusted terms for the country as a whole.