Spatial Weight Matrices and Their Use As Baseline Values and Location-Adjustment Factors in Property Assessment Models

Carmela Quintos
Department of Finance, City of New York

SpAM
SpAM (Spatial Analysis and Methods) presents short articles on the use of spatial statistical techniques for housing or urban development research. Through this department of Cityscape, the Office of Policy Development and Research introduces readers to the use of emerging spatial data analysis methods or techniques for measuring geographic relationships in research data. Researchers increasingly use these new techniques to enhance their understanding of urban patterns but often do not have access to short demonstration articles for applied guidance. If you have an idea for an article of no more than 3,000 words presenting an applied spatial data analysis method or technique, please send a one-paragraph abstract to ronald.e.wilson@hud.gov for review.

Property assessment models, for the purpose of mass appraisal and taxation, estimate the market price of real estate as a function of its location and physical characteristics. Locational effects, which affect multiple properties in an area, typically are established separately from property-specific effects. Baseline prices are established based on neighborhood or boundary demarcations, then a regression framework gives the adjustments to this baseline based on property-specific characteristics. As an alternative, baseline prices based on physical characteristics are first established, then location adjustments are applied as factors in the regression. This article shows how the spatial weight matrix in a spatial lag regression can be used as either a locational baseline value or as a location-adjustment factor, depending on the model specification.