In some applications of supervised machine learning, it is desirable to trade model complexity with greater interpretability for some covariates while letting other covariates remain a "black box". An important example is hedonic property valuation modeling, where machine learning techniques...

Accurate estimates of land values on a property-by-property basis are an important requirement for the effective implementation of land-based property taxes. We compare hedonic, residual, and matching techniques for mass appraisal of residential land values, using data from Maricopa County,...

This study extends recent work that developed and tested economic models of the joint decisions of household formation and homeownership. The cost of shelter is an important determinant of whether youth live independently (apart from parents and other nonrelated adults), and the cost of...

This paper outlines an approach to constructing a Dynamic Housing Affordability Index (DHAI) that reflects the true cost of owner-occupied housing and performs well in tracking changes in the demand for homeownership and other aspects of the housing market. Our index is grounded in user cost...

Purpose: The purpose of this paper is to investigate the accuracy and volatility of different methods for estimating and updating hedonic valuation models. Design/methodology/approach: The authors apply six estimation methods (linear least squares, robust regression, mixed-effects regression,...