Boosting the Accuracy of Commercial Real Estate Appraisals: An Interpretable Machine Learning Approach

URN to cite this document:: urn:nbn:de:bvb:355-epub-540215
DOI to cite this document:: 10.5283/epub.54021

Deppner, Juergen

; von Ahlefeldt-Dehn, Benedict ; Beracha, Eli ; Schäfers, Wolfgang

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 06 Apr 2023 08:41

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Abstract

In this article, we examine the accuracy and bias of market valuations in the U.S. commercial real estate sector using properties included in the NCREIF Property Index (NPI) between 1997 and 2021 and assess the potential of machine learning algorithms (i.e., boosting trees) to shrink the deviations between market values and subsequent transaction prices. Under consideration of 50 covariates, we ...