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Analysing local-level rental markets based on the German Mikrozensus

Author

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  • Charlotte Articus
  • Hanna Brenzel
  • Ralf Münnich

Abstract

Recent developments on German real estate markets show a striking increase of rents, especially in larger towns. This development is, however, not homogeneous: The market dynamics vary between different parts of cities and prices develop highly heterogeneously. Therefore, small-scale results are of interest. The German Mikrocensus, Germany’s largest household survey, routinely provides information on housing, including rental prices. Since 2018 results are geo-coded, setting the prerequisite for obtaining results at a local level. This specifically strong regional disaggregation obviously results in small sample sizes for the entities of interest. While standard design-based estimators under these condition result in large standard errors, small are estimation techniques may be a solution to nevertheless obtain reliable estimates. Therefore, the present paper explores the opportunity of obtaining very small-scale estimates of average rental prices based on the Mikrozensus employing small area estimation models. The study focusses on the City of Cologne, which provides a broad range of indicators that can be employed as auxiliary information in the models.

Suggested Citation

  • Charlotte Articus & Hanna Brenzel & Ralf Münnich, 2020. "Analysing local-level rental markets based on the German Mikrozensus," Research Papers in Economics 2020-09, University of Trier, Department of Economics.
    • Handle: RePEc:trr:wpaper:202009
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    File URL: http://www.uni-trier.de/fileadmin/fb4/prof/VWL/EWF/Research_Papers/2020-09.pdf
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    References listed on IDEAS

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    1. Gauri Sankar Datta & J. N. K. Rao & David Daniel Smith, 2005. "On measuring the variability of small area estimators under a basic area level model," Biometrika, Biometrika Trust, vol. 92(1), pages 183-196, March.
    2. Florin Vaida & Suzette Blanchard, 2005. "Conditional Akaike information for mixed-effects models," Biometrika, Biometrika Trust, vol. 92(2), pages 351-370, June.
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    1. Jan Pablo Burgard & Domingo Morales & Anna-Lena Wölwer, 2022. "Small area estimation of socioeconomic indicators for sampled and unsampled domains," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 287-314, June.

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