Aggregation und gewichtung von unterschiedlichen wertermittlungsdaten in kaufpreisarmen lagen mittels varianzkomponentenschatzung

authored by
Alexander Dorndorf, Matthias Soot, Alexandra Weitkamp, Hamza Alkhatib

In Germany, real estate valuation is realized by three standardized methods, among which the approach based on sales comparison is considered as being closest to the real estate market. With this approach, regression analysis is frequently used to solve the linear relationship. The regression model, however, normally requires approximately 15 purchases per independent variable for an accurate estimate in real estate valuation. This causes a problem for areas with few transactions in which only 10 to 30 purchases are available. To solve this problem, the current paper presents a mathematical-statistical model for an accurate estimation of regression coefficients in areas with few transactions. This aim is realized by using additional market data, which are combined with the available purchase cases. Challenges with this approach are the acquisition of the additional market data and the optimal combination of the data in the adjustment model. In this paper, survey data from real estate experts and offer prices are used as additional market data. The combination of these data with the purchase cases is carried out by means of variance component estimation (VCE). The quality assessment of the various market data shows a good conformity between the purchase cases and the experts' survey data. The offer prices differ from the other two datasets. The investigation concerning the VCE for the weighting of the different datasets within the adjustment model has two results: VCE yields more precise estimates of the regression coefficients, but this does not allow for a better prediction of the market values.

Geodetic Institute
External Organisation(s)
Technische Universität Dresden
AVN Allgemeine Vermessungs-Nachrichten
No. of pages
Publication date
Publication status
Peer reviewed
ASJC Scopus subject areas
Geography, Planning and Development, Civil and Structural Engineering, Earth and Planetary Sciences (miscellaneous)

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