 Evaluating Factor Contributions for Sold HomesJason R. Bailey, W. Brent Lindquist and Svetlozar T. Rachev Abstract: We evaluate the contributions of ten intrinsic and extrinsic factors, including ESG (environmental, social, and governance) factors readily available from website data to individual home sale prices using a P-spline generalized additive model (GAM). We identify the relative significance of each factor by evaluating the change in adjusted R^2 value resulting from its removal from the model. We combine this with information from correlation matrices to identify the added predictive value of a factor. Based on data from 2022 through 2024 for three major U.S. cities, the GAM consistently achieved higher adjusted R^2 values across all cities (compared to a benchmark generalized linear model) and identified all factors as statistically significant at the 0.5% level. The tests revealed that living area and location (latitude, longitude) were the most significant factors; each independently adds predictive value. The ESG-related factors exhibited limited significance; two of them each adding independent predictive value. The elderly/disabled accessibility factor was much more significant in one retirement-oriented city. In all cities, the accessibility factor showed moderate correlation with one intrinsic factor. Despite the granularity of the ESG data, this study also represents a pivotal step toward integrating sustainability-related factors into predictive models for real estate valuation. Date: 2025-11 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2511.02120 Access Statistics for this paper More papers in Papers from arXiv.org |
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