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Micro-geographic property price and rent indices

Author

Listed:
  • Gabriel M. Ahlfeldt
  • Stephan Heblich
  • Tobias Seidel
Abstract
We develop a programming algorithm that predicts a balanced-panel mix-adjusted house price index for arbitrary spatial units from repeated cross-sections of geocoded micro data. The algorithm combines parametric and non-parametric estimation techniques to provide a tight local fit where the underlying micro data are abundant and reliable extrapolations where data are sparse. To illustrate the functionality, we generate a panel of German property prices and rents that is unprecedented in its spatial coverage and detail. This novel data set uncovers a battery of stylized facts that motivate further research, e.g. on the density bias of price-to-rent ratios in levels and trends, within and between cities. Our method lends itself to the creation of comparable neighborhood-level qualified price and rent indices for residential and commercial property.

Suggested Citation

  • Gabriel M. Ahlfeldt & Stephan Heblich & Tobias Seidel, 2021. "Micro-geographic property price and rent indices," CEP Discussion Papers dp1782, Centre for Economic Performance, LSE.
    • Handle: RePEc:cep:cepdps:dp1782
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    4. Bachtrögler-Unger, Julia & Dolls, Mathias & Krolage, Carla & Schüle, Paul & Taubenböck, Hannes & Weigand, Matthias, 2023. "EU cohesion policy on the ground: Analyzing small-scale effects using satellite data," Regional Science and Urban Economics, Elsevier, vol. 103(C).
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    More about this item

    Keywords

    index; real estate; price; property; rent;
    All these keywords.

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General

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