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Liquidity and prices: a cluster analysis of the German residential real estate market

Author

Listed:
  • Marcelo Cajias

    (Patrizia Immobilien AG)

  • Philipp Freudenreich

    (University of Regensburg)

  • Anna Freudenreich

    (University of Regensburg)

  • Wolfgang Schäfers

    (University of Regensburg)

Abstract

This paper analyses the highly under-researched German residential real estate market. Quality- and spatial-adjusted price and liquidity indices are calculated separately for the investment and rental market on a regional basis. Applying the “Partitioning Around Medoids (PAM)” clustering algorithm, the regions are clustered with respect to their price and liquidity development after the average silhouette method is applied to find the optimal number of clusters. The dataset underlying this analysis comprises more than 4.5 million observations in 380 German regions from 2013 Q1 to 2018 Q4. The clusters are then analysed by means of further economic and socioeconomic data in order to identify similarities. Furthermore, the clusters are interpreted from a geographic perspective. We find that the allocation to cluster 1 is always supported by higher growth rates in the variables, population, working population and real GDP, implying higher demand for space. Moreover, in each of the analysed categories cluster 1 reveals a lower unemployment rate as well as a higher disposable income. One of the most interesting implications is, that apparently a large part of the German population has developed into professional real estate investors. In Germany the largest share of landlords is the one of the so-called non-professional landlords. As the regions assigned to cluster 1, displaying the most significant price increase, seem to be chosen based on a very sophisticated market analysis by identifying the regions with the strongest fundamental data, it seems like the dominating market players have significantly increased their knowledge and approach for investing in residential real estate.

Suggested Citation

  • Marcelo Cajias & Philipp Freudenreich & Anna Freudenreich & Wolfgang Schäfers, 2020. "Liquidity and prices: a cluster analysis of the German residential real estate market," Journal of Business Economics, Springer, vol. 90(7), pages 1021-1056, August.
    • Handle: RePEc:spr:jbecon:v:90:y:2020:i:7:d:10.1007_s11573-020-00990-2
    DOI: 10.1007/s11573-020-00990-2
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    Cited by:

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    2. Kevin Bauer & Moritz von Zahn & Oliver Hinz, 2023. "Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users’ Information Processing," Information Systems Research, INFORMS, vol. 34(4), pages 1582-1602, December.
    3. Wolfgang Breuer & Bertram I. Steininger, 2020. "Recent trends in real estate research: a comparison of recent working papers and publications using machine learning algorithms," Journal of Business Economics, Springer, vol. 90(7), pages 963-974, August.

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    More about this item

    Keywords

    Residential; Housing; Liquidity; Index; Time on market; GAMLSS; Cluster; Partitioning around medoids;
    All these keywords.

    JEL classification:

    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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