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Discovering and Applying Location Influence Patterns in the Mass Valuation of Domestic Real Property

This thesis addresses the important question of how to incorporate location into a model for the mass valuation of residential (domestic) real property. Two new methods for doing so are described. The first is a process for detecting distinct market segments within a defined study area. It makes use of Geographically Weighted Regression to construct a three dimensional point pattern surface throughout the area for a home of identical characteristics. When the surface displays a discernable spatial structure, evidence is provided for the existence of market segments. The segments detected by this technique are used in a system of models that account for large-scale effects of location on value and thereby improve the predictive accuracy of this model system as compared to a single global model of the same form. The second is a modification to the comparable sales method of valuation such that it provides a prediction accuracy superior to both ordinary least squares (OLS) estimates and the comparables sales method itself. It is formed by taking an optimal linear combination of the OLS model and the comparables sales model based on an examination of the spatial structure of the localized residual errors of the OLS. In combination, these two methods provide improved predictive accuracy and a reduction in the spatial autocorrelation of the residual errors of the resultant predictions when compared to alternative model structures

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- by Richard Borst
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- 2
  Geostatistics, MASS APPRAISALS

A Proposal of a Mass Appraisal System in Greece with CAMA System: Evaluating GWR and MRA techniques in Thessaloniki Municipality

Property tax in Greece is levied since 1985 not on Market Values but on the " objective value " of the properties as it is defined by the Ministry of Economics. It forms a non-flexible system, with market-irrelevant and unreal-istic values, inducing land-policy practices and potential political cost to each periodical update. Furthermore, instead of adjusting taxation levels to the current economic reality, the real estate market is experiencing further burdening through approximately 40 different property taxes and levies, leading to further shrinking and depreciation. The authors believe that a fairer taxation system could significantly assist the property sector in Greece. Thus, through this paper and by studying and analyzing best practices from other countries, they propose models that can be applied with the use of existing data in Greece. This work aims to identify the critical parameters that affecting property values in Thessaloniki to create a Market Value forecasting tool for a fairer taxation system, to highlight the importance of a GIS system for this purpose and to compare the results of MRA with the use of SPSS with those of GWR in ArcGIS environment. For the purposes of this study, the Municipality of Thessaloniki was chosen due to its very well organized portal with significant and well organized geographical data and because authors manage to access some data from the Central Bank of Greece, regarding property valuations.

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Introducing local property tax for fiscal decentralization and local authority autonomy

Charles Tiebout (1956), in his work “A Pure Theory of Local Expenditures”, provides a vision of the workings of the local public sector, acknowledging many similarities to the features of a competitive market, however omitting any references to local taxation. Contrary to other researchers’ claim that the Tiebout model and the theory of fiscal decentralization are by no means synonymous, this paper aims to expand Tiebout’s theory, by adding the local property tax in the context, introducing a fair, ad valorem property taxation system based on the automated assessment of the value of real estate properties within the boundaries of local authorities. Computer Assisted Mass Appraisal methodology integrated with Remote Sensing technology and GIS analysis is applied to local authorities’ property registries and cadastral data, building a spatial relational database and providing data to be statistically processed through Multiple Regression Analysis modeling. The proposed scheme accomplishes economy of scale using CAMA procedures on one hand, but also succeeds in making local authorities self-sufficient through a decentralized, fair, locally calibrated property taxation model, providing rational income administration.

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- by Thomas Dimopoulos and +1
  Tassos Labropoulos
- •
- 5
  Land and Property Development, Real estate valuation, Property Tax, AVM

Accuracy measurement of Random Forests and Linear Regression for mass appraisal models that estimate the prices of residential apartments in Nicosia, Cyprus

The purpose of this article is to examine the prediction accuracy of the Random Forests, a machine learning method, when it is applied for residential mass appraisals in the city of Nicosia, Cyprus. The analysis is performed using transaction sales data from the Cyprus Department of Lands and Surveys, the Consumer Price Index of Cyprus from the Cyprus Statistical Service and the Central Bank of Cyprus' Residential Index (Price index for apartments). The Consumer Price Index and the price index for apartments record quarterly price changes, while the dependent variables for the computational models were the Declared and the Accepted Prices that were conditional on observed values of a variety of independent variables. The Random Forests method exhibited enhanced prediction accuracy, especially for the models that comprised of a sufficient number of independent variables , indicating the method as prominent, although it has not yet been utilized adequately for mass appraisals.

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Sensitivity Analysis of Machine Learning Models for the Mass Appraisal of Real Estate. Case Study of Residential Units in Nicosia, Cyprus

A recent study of property valuation literature indicated that the vast majority of researchers and academics in the field of real estate are focusing on Mass Appraisals rather than on the further development of the existing valuation methods. Researchers are using a variety of mathematical models used within the field of Machine Learning, which are applied to real estate valuations with high accuracy. On the other hand, it appears that professional valuers do not use these sophisticated models during daily practice, rather they operate using the traditional five methods. The Department of Lands and Surveys in Cyprus recently published the property values (General Valuation) for taxation purposes which were calculated by applying a hybrid model based on the Cost approach with the use of regression analysis in order to quantify the specific parameters of each property. In this paper, the authors propose a number of algorithms based on Artificial Intelligence and Machine Learning approaches that improve the accuracy of these results significantly. The aim of this work is to investigate the capabilities of such models and how they can be used for the mass appraisal of properties, to highlight the importance of sensitivity analysis in such models and also to increase the transparency so that automated valuation models (AVM) can be used for the day-today work of the valuer.

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Discovering and Applying Location Influence Patterns in the Mass Valuation of Domestic Real Property

The goal of this study is to develop an improved method for modelling the influence of location in a hedonic model for estimating the value of domestic properties, thus improving the model’s predictive accuracy and reducing observable spatial patterns in the model’s residual errors. The aims of this study are to detect market segments and to use them in a model structure that accounts for large-scale market influences, and to use the internal structure of the market segments to model localised market influences. Two new methods for doing so are described. The first is a process for detecting distinct market segments within a defined study area. It makes use of Geographically Weighted Regression to construct a three dimensional point pattern surface of values for a home of identical characteristics throughout the area. When the surface displays a discernable spatial structure, evidence is provided for the existence of market segments. The segments detected by this technique are used ...

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- by Richard Borst
- •
- 3
  Computer Science, Geostatistics, MASS APPRAISALS

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