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Identifying Berlin's land value map using adaptive weights smoothing

Author

Listed:
  • Kolbe, Jens
  • Schulz, Rainer
  • Wersing, Martin
  • Werwatz, Axel

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 in uenced 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 regression. 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.

Suggested Citation

  • Kolbe, Jens & Schulz, Rainer & Wersing, Martin & Werwatz, Axel, 2014. "Identifying Berlin's land value map using adaptive weights smoothing," SFB 649 Discussion Papers 2015-003, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2015-003
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    More about this item

    Keywords

    land value; adaptive weight smoothing; spatial modeling;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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