Automated valuation modelling: A specification exercise

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    23 Citations (Scopus)
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    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.
    Original languageEnglish
    Pages (from-to)131-153
    Number of pages23
    JournalJournal of Property Research
    Volume31
    Issue number2
    Early online date31 Oct 2013
    DOIs
    Publication statusPublished - 2014

    Keywords

    • hedonic regression
    • log transformation
    • predictive performance

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