Data on Repeated Offerings in the German Housing Market Based on RWI-GEO-RED

Abstract This paper introduces a repeated-sales algorithm tailored for the German real estate market, addressing the lack of such data. Utilizing the dataset RWI-GEO-RED from FDZ Ruhr at RWI, which exploits data from ImmobilienScout24.de, the algorithm classifies repeat-sales and repeat-rent listings, overcoming challenges like measurement errors and deviations in property characteristics. The methodology, based on nearest centroid classification, ensures accurate clustering of similar listings. The paper compares the new repeated-sales indices with the traditional hedonic price index, revealing more conservative estimates of rent growth. Additionally, the data’s panel structure allows for detailed analysis of unit-level dynamics and mispricing. The study highlights the advantages of this approach and suggests potential research avenues, providing a valuable tool for economists and policymakers to assess housing market trends in Germany.