Contents lists available at ScienceDirect Land Use Policy journal homepage: www.elsevier.com/locate/landusepol Mass appraisal of farmland using classical econometrics and spatial modeling Marlene Salete Uberti ⁎ , Mauro Antonio Homem Antunes, Paula Debiasi, Wagner Tassinari Federal Rural University of Rio de Janeiro, Seropédica, Rio de Janeiro, Brazil ARTICLE INFO Keywords: Plan of generic values – PGV Mass appraisal Ordinary kriging Surface of values ABSTRACT Mass appraisals of properties traditionally use classical linear regression models (CLRMs); however, there has been the need to model the data spatially. Such modeling of the geographic effects has been used mainly in appraisals of urban areas, but the values of the properties in rural areas are also affected by the geographic location. This paper aims to use spatial regression econometric models in a sample of rural properties to ela- borate the plan of values for an area of the North Fluminense Region – RJ, Brazil. The proposed methodology is to investigate and model the effects caused by the spatial autocorrelation on the CLRMs, evaluate their per- formance comparing them with the spatial models and produce the plan of values through ordinary kriging. The utilized sample consisted of 113 observations and 25 samples of verification. The performance of the obtained surfaces of values was evaluated through the Root Mean Squared Error (RMSE). The results showed that the spatial autocorrelation can have its effects controlled by Spatial Regression Models, because the Spatial Error Model (CAR) allowed to model the spatial dependence present in the residuals. Using the metrics of Akaike information criterion (AIC), R 2 and likelihood function (LIK), the CAR model showed better fit in comparison to the CLRM. The results showed that the surface generated by the CAR model showed the best performance with the lowest RMSE. The combination of the methodologies of classical and spatial regressions and the use of geostatistical techniques were adequate to elaborate and obtain the plan of values for rural areas, to be used for various purposes, such as taxation, financing, expropriations, indemnities (in case of creation of conservation units or even in environmental disasters), among others. 1. Introduction Brazil is a country with continental dimensions, territorial surface of 8,514,876.599 km 2 and the rural properties occupy 71.10% of this surface. Thus, the techniques of mass appraisal of values of the prop- erties 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 determi- nation of the values, such as: financing, expropriations, indemnities (in case of creation of conservation units or even in environmental dis- asters), 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 million 1 . Using the area estimated by the National Institute of Colonization and Land Re- form – 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 homo- genization of the values of a sample of properties collected in the real estate market. However, there has been the need to incorporate vari- ables 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). However, there are no studies in the literature on the spatial ana- lysis of values of rural properties for the determination of which is the best technique to obtain the PVG. Thus, the present study aims to treat the data statistically through Classical and Spatial Regressions, generate the surface of values through Geostatistics and thus elaborate the plan https://doi.org/10.1016/j.landusepol.2017.12.044 Received 21 October 2016; Received in revised form 13 December 2017; Accepted 13 December 2017 ⁎ Corresponding author. E-mail addresses: msuberti@ufrrj.br (M.S. Uberti), mauroantunes@ufrrj.br (M.A.H. Antunes), paula@ufrrj.br (P. Debiasi), tassinari@ufrrj.br (W. Tassinari). 1 In December 31, 2012, the exchange rate was 1USD=R$2.04 Land Use Policy 72 (2018) 161–170 0264-8377/ © 2017 Elsevier Ltd. All rights reserved. T