Hybrid Geoinformatic-Statistical Analysis for Assessing Single-Family-Home Values: the Case of College Station, Texas

Abstract

This study investigates the impact of certain residential development elements on the value of single-family homes (SFH) within an urban setting. Development elements such as gatedness, level of amenity, and size and proximity of nearest city-park were investigated. Appraisals of SFH in the City of College Station, Texas; and market values and other SFH’s multiple listing services data for approximately 1326 randomly distributed SFH’s are utilized as the database for this study. The methodology of this research integrates traditional econometric techniques used in value analysis, namely the hedonic price function, with cutting edge geoinformatic technology. Automated spatial analysis tools offered efficient and accurate generation, validation, manipulation, and assessment of development variables. Furthermore, resolution of spatial autocorrelation encountered in statistical analysis was facilitated using residual mapping processes along with traditional residual plots and other statistical remedies. Findings indicate that the power of the hybrid geoinformatic-statistical model in analyzing, explaining, and presenting change in real estate value is significant. Furthermore, findings indicate that gatedness of a development has a higher positive impact on home values in such a development than the level of amenities provided, e.g. trails, playgrounds, common greens, etc.