Mass appraisal of apartment through geographically weighted regression

Abstract

Housing Market appraisal studies generally apply classic regression models, whose parameters are globally estimated. However, the use of the Geographically Weighted Regression (GWR) model, allows the parameters to be locally estimated, increasing its precision. The aim of this article is to apply the GWR model to a sample of 82 apartments, in order to create a plan of values of some districts of the West Zone of Rio de Janeiro city, Brazil. With the proposed methodology, GWR and kernel estimator, it is possible to generate a surface of values. The performance of the surface of values was assessed with (i) cross-validation between the kernel functions, with the Root-Mean Square Standardized (RMSS) error; and with (ii) the GWR adjustment factors to determine the ideal bandwidth. The contribution of generating a surface of values with geographical location via kernel estimator lies on supporting apartment pricing, such as in calculating the venal value of apartments of the West Zone of Rio de Janeiro city, besides being applied in IPTU-Imposto sobre Propriedade Predial e Territorial (The Urban Real Estate Property Tax) and ITBI-Imposto de Transmissão de Bens Imóveis (Tax on the Transfer of Real Estate) and ITBI collection.