MASS APPRAISAL OF APARTMENT THROUGH GEOGRAPHICALLY WEIGHTED REGRESSION

Caio Flávio Martinez Fontoura Júnior,Marlene Saleti Uberti,Vilma Mayumi Tachibana

doi:10.1590/s1982-21702020000200005

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.

Highlights

For market evaluation, local factors and real conditions must be considered in the elaboration of statistical models
One how Brazilian municipalities obtain it as a source of resources is through tax collection by charging fees and taxes such as 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)
The 82 observations, that were acquired by the real estate websites of the city of Rio de Janeiro, were used

Summary

Introduction

Local factors and real conditions must be considered in the elaboration of statistical models. One how Brazilian municipalities obtain it as a source of resources is through tax collection by charging fees and taxes such as 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). These taxes are calculated according to municipal laws, based on the property’s market value, and are acquired based on local real estate behavior. Its main attribute is the definition of a real estate tax policy that is fair and equal (Averbeck, 2003; Malaman and Amorim, 2017)

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