ارزیابی توده ای از زمین های کشاورزی با استفاده از اقتصاد سنجی کلاسیک و مدل سازی فضایی Mass appraisal of farmland using classical econometrics and spatial modeling

1. Introduction Brazil is a country with continental dimensions, territorial surface of 8,514,876.599 km2 and the rural properties occupy 71.10% of this surface. Thus, the techniques of mass appraisal of values of the properties are of great importance for a series of applications. One of the main applications is in the determination of the Rural Land Tax – RLT. In addition, another tax in Brazil that depends on the correct appraisal of the property is the Tax on the Transfer of Real Estate – TTRE, which is of total responsibility of the Municipal Governments. There are also many other actions in rural properties that also need correct determination of the values, such as: financing, expropriations, indemnities (in case of creation of conservation units or even in environmental disasters), real estate buying and selling, land reform, etc. Each one of these actions determines values that do not always follow evaluative techniques, generating different values for each situation. As to the RLT, according to the Federal Revenue Secretariat – FRS (BRASIL, 2012), the collection in 2012 was equal to R$ 677 million1 . Using the area estimated by the National Institute of Colonization and Land Reform – INCRA in the same year, 605,387,746.06 ha, the value in 2012 was 1.12 R$/ha, which is considered to be too small and reflects an inefficient taxation. The elaboration of the Plan of Generic Values – PGVs can use the statistical techniques of Multiple Regression, through the homogenization of the values of a sample of properties collected in the real estate market. However, there has been the need to incorporate variables of geographic location in the regression models, in order to model spatial effects. This modeling of the spatial effects, through spatial econometrics, has been used mainly in the PGVs of urban areas (Trivelloni, 2005; Hornburg, 2009), and the values of properties in rural areas are also affected by these effects (Santos, 2014).