Identifying Berlin's land value map using Adaptive Weights Smoothing

Jens Kolbe, Rainer Schulz, Martin Wersing, Axel Werwatz

    Research output: Working paperDiscussion paper

    Abstract

    We use Adaptive Weights Smoothing (AWS) of Polzehl and Spokoiny (2000, 2003, 2006) to estimate a map of land values for Berlin, Germany. Our data are prices of undeveloped land that was transacted between 1996-2009. Even though the observed land price is an indicator of the respective land value, it is influenced by transaction noise. The iterative AWS applies piecewise constant regression to reduce this noise and tests at each location for constancy at the margin. If not rejected, further observations are included in the local regres- sion. The estimated land value map conforms overall well with expert-based land values. Our application suggests that the transparent AWS could prove a useful tool for researchers and real estate practitioners alike.
    Original languageEnglish
    Place of PublicationBerlin
    PublisherHumboldt-Universität zu Berlin
    Number of pages41
    Publication statusPublished - 2015

    Publication series

    NameSFB 649 Discussion paper
    PublisherHumboldt-Universität zu Berlin
    No.2015-003

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    Cite this

    Kolbe, J., Schulz, R., Wersing, M., & Werwatz, A. (2015). Identifying Berlin's land value map using Adaptive Weights Smoothing. (SFB 649 Discussion paper; No. 2015-003). Berlin: Humboldt-Universität zu Berlin.