Micro-geographic property price and rent indices

Gabriel M. Ahlfeldt, Stephan Heblich and Tobias Seidel

Regional Science and Urban Economics, 2023, vol. 98, issue C

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 positive correlation between density and price-to-rent ratios in levels and trends, both within and between cities. Our method lends itself to the creation of comparable neighborhood-level rent indices (Mietspiegel) across Germany.

Keywords: Index; Real estate; Price; Property; Rent (search for similar items in EconPapers)
JEL-codes: R10 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (6)

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Working Paper: Micro-geographic property price and rent indices (2023)
Working Paper: Micro-geographic property price and rent indices (2021)
Working Paper: Micro-Geographic Property Price and Rent Indices (2021)
Working Paper: Micro-geographic property price and rent indices (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:98:y:2023:i:c:s0166046222000746

DOI: 10.1016/j.regsciurbeco.2022.103836

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