Hedonic Models Incorporating ESG Factors for Time Series of Average Annual Home Prices
arxiv(2024)
摘要
Using data from 2000 through 2022, we analyze the predictive capability of
the annual numbers of new home constructions and four available environmental,
social, and governance factors on the average annual price of homes sold in
eight major U.S. cities. We contrast the predictive capability of a P-spline
generalized additive model (GAM) against a strictly linear version of the
commonly used generalized linear model (GLM). As the data for the annual price
and predictor variables constitute non-stationary time series, to avoid
spurious correlations in the analysis we transform each time series
appropriately to produce stationary series for use in the GAM and GLM models.
While arithmetic returns or first differences are adequate transformations for
the predictor variables, for the average price response variable we utilize the
series of innovations obtained from AR(q)-ARCH(1) fits. Based on the GAM
results, we find that the influence of ESG factors varies markedly by city,
reflecting geographic diversity. Notably, the presence of air conditioning
emerges as a strong factor. Despite limitations on the length of available time
series, this study represents a pivotal step toward integrating ESG
considerations into predictive real estate models.
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