Land value appraisal using statistical methods

Arbeitspapier

The taxation of property based on market values requires frequent appraisals for a large number of properties. In light of the recent property tax reform discussion in Germany, it has been argued that a valuebased tax therefore cannot be implemented at a reasonable cost. In several other countries, however, mass appraisal systems based on statistical methods are used for property tax assessments. In this paper, we show how this could in principle be done in Germany, using transactions data that local surveyor commissions are obliged to collect by law. We discuss the regression techniques for estimating land values from such data and illustrate them by applying them to data from Berlin, Germany. We find that the methods are capable of producing land value estimates that match up well with expert based assessments.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: FORLand-Working Paper ; No. 07 (2019)

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Structure and Scope of Government: General ; Taxation, Subsidies, and Revenue: General ; Other Spatial Production and Pricing Analysis ; Finance in Urban and Rural Economies ; Regional Government Analysis: Land Use and Other Regulations
• Thema: land value ; mass appraisal ; nonparametric regression ; semiparametric regression

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Kolbe, Jens ; Schulz, Rainer ; Wersing, Martin ; Werwatz, Axel
• Ereignis: Veröffentlichung
• (wer): Humboldt-Universität zu Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets - Efficiency and Regulation"
• (wo): Berlin
• (wann): 2019

Weitere Informationen

• DOI: doi:10.18452/19722
• Handle: http://hdl.handle.net/10419/213061
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ