Automated valuation modelling: A specification exercise

Rainer Schulz, Martin Wersing and Axel Werwatz

No 2013-046, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: Market value predictions for residential properties are important for investment decisions and the risk management of households, banks, and real estate developers. The increased access to market data has spurred the development and application of Automated Valuation Models (AVMs), which can provide appraisals at low cost. We discuss the stages involved when developing an AVM. By reflecting on our experience with md*immo, an AVM from Berlin, Germany, our paper contributes to an area that has not received much attention in the academic literature. In addition to discussing the main stages of AVM development, we examine empirically the statistical model development and validation step. We find that automated outlier removal is important and that a log model performs best, but only if it accounts for the retransformation problem and heteroscedasticity.

Keywords: Hedonic regression; log transformation; predictive performance (search for similar items in EconPapers)
JEL-codes: C52 C53 R32 (search for similar items in EconPapers)
Date: 2013
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Journal Article: Automated valuation modelling: a specification exercise (2014)
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