Identifying Berlin's land value map using adaptive weights smoothing

Jens Kolbe, Rainer Schulz, Martin Wersing and Axel Werwatz

No 2015-003, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

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.

Keywords: land value; adaptive weight smoothing; spatial modeling (search for similar items in EconPapers)
JEL-codes: C14 R14 R15 (search for similar items in EconPapers)
Date: 2014
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Journal Article: Identifying Berlin’s land value map using adaptive weights smoothing (2015)
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