Combining machine learning and econometrics: Application to commercial real estate prices

Author:

Francke Marc1ORCID,van de Minne Alex23ORCID

Affiliation:

1. Finance Group, Amsterdam Business School University of Amsterdam Amsterdam Netherlands

2. School of Business University of Connecticut Storrs Connecticut USA

3. R&D Labs Ortec Finance Rotterdam Netherlands

Abstract

AbstractIn this article, we combine a random effects model with different machine learning algorithms via an iterative process when predicting commercial real estate asset values. Using both random effects and machine learning allows us to combine the strengths of both approaches. The random effects will be used to estimate a common trend, property type trends, location value, and property random effects for properties that sold more than once. The machine learning algorithm will fit the observed characteristics (features) in a complex nonlinear fashion. The model is applied to a small sample of 2652 transactions in Phoenix (AZ) between 2001 and 2021. We only observe a limited number of property characteristics. The average out‐of‐sample MAPE is below 11%, which is as good or even better compared to the average appraisal error found in literature. The out‐of‐sample MAPE is even 9% for properties that sold more than once in the training set. In addition, our model provides indexes and locational heatmaps. These have their own uses and cannot be obtained with standard machine learning algorithms.

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3