This thesis addresses the important question of how to incorporate location into a model for the ... more 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
Journal of Property Valuation and Investment, Dec 1, 1997
Provides an outline of research seeking to apply to computer assisted mass appraisal (CAMA) model... more Provides an outline of research seeking to apply to computer assisted mass appraisal (CAMA) model capable of use within a geographic information system (GIS). The end product will be a working GIS/valuation integrated model. The model, in an operational context, can be utilized for property taxation purposes, to facilitate the rating and revaluation of residential properties in Northern Ireland. As the value of land and property is a function of economic, legal, physical and locational factors, consequently access to comprehensive, reliable and up‐to‐date transaction evidence is a prerequisite to property valuation. Valuation techniques depend on the collection and analysis of relevant data. Historically, the application of these techniques took place within a non‐spatial environment. Ultimately, market data support any estimate of value. Data searches and collection can prove both time consuming and expensive in relation to the fee earning potential of a valuation report. GIS can facilitate, in a spatial and aspatial context, the storage, manipulation and analysis of data, in a fraction of the time previously required. Current techniques for the mass appraisal of property, and for the prediction of residential property values, can be enhanced by utilizing the data handling capacity of GIS. Integration of a mass appraisal model within a GIS will add value to the valuation process.
Journal of Property Tax Assessment & Administration, 2009
Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earl... more Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earlier article (Borst 2008), the Fourier expansion method was compared to two other methods of ac-counting for time in a hedonic model ...
The Comparable Sales Method of Valuation (CSM) is widely used in the United States for valuing re... more The Comparable Sales Method of Valuation (CSM) is widely used in the United States for valuing residential properties. There is an identifiable relationship between CSM as practiced by mass appraisers and the recent developments in spatially aware valuation models. A modified CSM (MCSM) is shown to be a special case of a spatially lagged weight matrix model. There is a less formal but clear relationship with Geographically Weighted Regression as well. The predictive accuracy of the CSM and MCSM are compared to several Ordinary Least Squares Model configurations, and results obtained from Geographically Weighted Regression via empirical studies on diverse datasets. An example of a comparable sales weighting scheme as practiced by mass appraisers is provided. In addition, particular interest is focused on how well each method is able to model the spatial variations in property values. This is done by examining the spatial autocorrelation in residual errors of the predicted values.
International Journal of Housing Markets and Analysis, Aug 9, 2011
PurposeThe purpose of this paper is to describe a segmentation technique based on geostatistical ... more PurposeThe purpose of this paper is to describe a segmentation technique based on geostatistical modeling methods utilizing geographically weighted regression (GWR) to identify submarkets which could be applied within the mass appraisal environment.Design/methodology/approachGiven the spatial dimension within which neighbourhoods/submarkets exist, this paper has sought to utilize the geostatistical technique of GWR to identify them.FindingsThe efficacy of the procedure is established by demonstrating improvements in predictive accuracy of the resultant segmented market models as compared to a baseline global unsegmented model for each of the study areas. Optimal number of segments is obtained by measures of predictive accuracy, spatial autocorrelation in the residual errors and the Akaike information criterion.Research limitations/implicationsThe three datasets used allowed for an evaluation of the robustness of the method. Nonetheless it would be beneficial to test it on other datasets, particularly from different regions of the world.Practical implicationsMany researchers and mass appraisal practitioners have established the benefit of segmenting a study area into two or more submarkets as a means of incorporating the effects of location within mass valuation models. This approach develops the existing knowledge.Social implicationsThe research ultimately is developing more accurate valuation models upon which the property tax is based. This should create an environment of fair and acceptable assessed values by the tax paying community.Originality/valueThe contribution of this work lies in the methodological approach adopted which incorporates a market basket approach developed through a process of GWR. The importance of the research findings illustrate that submarket segmentation need no longer be an arbitrary process.
The article is focused n the techniques to select comparables, providing evidence that it is poss... more The article is focused n the techniques to select comparables, providing evidence that it is possible to deal with this delicate phase of the automated valuation process in a scientific way.
PurposeThe purpose of this research is to explore from a mass appraisal perspective how the effec... more PurposeThe purpose of this research is to explore from a mass appraisal perspective how the effects of location are reflected within valuation models. The paper sets out to detail the various techniques and the efficacy of their application.Design/methodology/approachThe approach adopted is analytical and based upon the development of locational attributes. An extensive literature base is synthesized with methods being evaluated in their application to mass appraisal.FindingsThis research has identified that the three main groups interested in residential property valuation, namely, academia, industry and commerce have to a certain extent been unfamiliar with the research developments occurring in the other groups. The impact of this is important, given the need for integration and collaboration in terms of future model development.Research limitations/implicationsThe research underpinning this paper will provide a solid basis for further research into this area. The importance of measuring the effect that location has on value is of major significance in the determination of objective estimates of property value.Practical implicationsThose within the assessment community could be described as pragmatists working in a situation that requires feasible and suitable solutions to the problem of measuring location value. It is our contention that the third generation techniques of spatially varying parameter models and spatial autocorrelation models will require greater industry verification before their use becomes more widely accepted.Originality/valueThis paper provides a detailed analysis of methodologies used to reflect the value of location over the last 50 years. The debate is taken forward by describing what will be the contribution to the development of the next generation of location‐specific modeling techniques.
Many researchers and mass appraisal practitioners have established the benefit of segmenting a st... more Many researchers and mass appraisal practitioners have established the benefit of segmenting a study area into two or more submarkets as a means of incorporating the large-scale effects of location within mass valuation models. The techniques applied for identifying locational submarkets or segments are quite varied, and often arbitrary. This article describes a segmentation technique based on the use of geographically weighted regression (GWR) which could be applied within the mass appraisal environment. The efficacy of the procedure is established by demonstrating improvements in predictive accuracy of the resultant segmented market models as compared to a baseline global unsegmented model for each of the study areas and then using the segmented markets in a series of spatially aware valuation models.
An Automated Valuation Model (AVM) that seeks to attain predictive accuracy must take into accoun... more An Automated Valuation Model (AVM) that seeks to attain predictive accuracy must take into account both spatial and temporal effects in the real estate market. A model structure that contains neither explicit spatial nor temporal variables is calibrated by a method that recognizes these variations in is calibration architecture. The method is conceptu-ally similar to Geographically Weighted Regression (GWR) except that it extends into the temporal domain. The methodology is explained and results provided illustrating spatio-temporal variations in value.
Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earl... more Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earlier article (Borst 2008), the Fourier expansion method was compared to two other methods of ac-counting for time in a hedonic model ...
This thesis addresses the important question of how to incorporate location into a model for the ... more 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
Journal of Property Valuation and Investment, Dec 1, 1997
Provides an outline of research seeking to apply to computer assisted mass appraisal (CAMA) model... more Provides an outline of research seeking to apply to computer assisted mass appraisal (CAMA) model capable of use within a geographic information system (GIS). The end product will be a working GIS/valuation integrated model. The model, in an operational context, can be utilized for property taxation purposes, to facilitate the rating and revaluation of residential properties in Northern Ireland. As the value of land and property is a function of economic, legal, physical and locational factors, consequently access to comprehensive, reliable and up‐to‐date transaction evidence is a prerequisite to property valuation. Valuation techniques depend on the collection and analysis of relevant data. Historically, the application of these techniques took place within a non‐spatial environment. Ultimately, market data support any estimate of value. Data searches and collection can prove both time consuming and expensive in relation to the fee earning potential of a valuation report. GIS can facilitate, in a spatial and aspatial context, the storage, manipulation and analysis of data, in a fraction of the time previously required. Current techniques for the mass appraisal of property, and for the prediction of residential property values, can be enhanced by utilizing the data handling capacity of GIS. Integration of a mass appraisal model within a GIS will add value to the valuation process.
Journal of Property Tax Assessment & Administration, 2009
Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earl... more Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earlier article (Borst 2008), the Fourier expansion method was compared to two other methods of ac-counting for time in a hedonic model ...
The Comparable Sales Method of Valuation (CSM) is widely used in the United States for valuing re... more The Comparable Sales Method of Valuation (CSM) is widely used in the United States for valuing residential properties. There is an identifiable relationship between CSM as practiced by mass appraisers and the recent developments in spatially aware valuation models. A modified CSM (MCSM) is shown to be a special case of a spatially lagged weight matrix model. There is a less formal but clear relationship with Geographically Weighted Regression as well. The predictive accuracy of the CSM and MCSM are compared to several Ordinary Least Squares Model configurations, and results obtained from Geographically Weighted Regression via empirical studies on diverse datasets. An example of a comparable sales weighting scheme as practiced by mass appraisers is provided. In addition, particular interest is focused on how well each method is able to model the spatial variations in property values. This is done by examining the spatial autocorrelation in residual errors of the predicted values.
International Journal of Housing Markets and Analysis, Aug 9, 2011
PurposeThe purpose of this paper is to describe a segmentation technique based on geostatistical ... more PurposeThe purpose of this paper is to describe a segmentation technique based on geostatistical modeling methods utilizing geographically weighted regression (GWR) to identify submarkets which could be applied within the mass appraisal environment.Design/methodology/approachGiven the spatial dimension within which neighbourhoods/submarkets exist, this paper has sought to utilize the geostatistical technique of GWR to identify them.FindingsThe efficacy of the procedure is established by demonstrating improvements in predictive accuracy of the resultant segmented market models as compared to a baseline global unsegmented model for each of the study areas. Optimal number of segments is obtained by measures of predictive accuracy, spatial autocorrelation in the residual errors and the Akaike information criterion.Research limitations/implicationsThe three datasets used allowed for an evaluation of the robustness of the method. Nonetheless it would be beneficial to test it on other datasets, particularly from different regions of the world.Practical implicationsMany researchers and mass appraisal practitioners have established the benefit of segmenting a study area into two or more submarkets as a means of incorporating the effects of location within mass valuation models. This approach develops the existing knowledge.Social implicationsThe research ultimately is developing more accurate valuation models upon which the property tax is based. This should create an environment of fair and acceptable assessed values by the tax paying community.Originality/valueThe contribution of this work lies in the methodological approach adopted which incorporates a market basket approach developed through a process of GWR. The importance of the research findings illustrate that submarket segmentation need no longer be an arbitrary process.
The article is focused n the techniques to select comparables, providing evidence that it is poss... more The article is focused n the techniques to select comparables, providing evidence that it is possible to deal with this delicate phase of the automated valuation process in a scientific way.
PurposeThe purpose of this research is to explore from a mass appraisal perspective how the effec... more PurposeThe purpose of this research is to explore from a mass appraisal perspective how the effects of location are reflected within valuation models. The paper sets out to detail the various techniques and the efficacy of their application.Design/methodology/approachThe approach adopted is analytical and based upon the development of locational attributes. An extensive literature base is synthesized with methods being evaluated in their application to mass appraisal.FindingsThis research has identified that the three main groups interested in residential property valuation, namely, academia, industry and commerce have to a certain extent been unfamiliar with the research developments occurring in the other groups. The impact of this is important, given the need for integration and collaboration in terms of future model development.Research limitations/implicationsThe research underpinning this paper will provide a solid basis for further research into this area. The importance of measuring the effect that location has on value is of major significance in the determination of objective estimates of property value.Practical implicationsThose within the assessment community could be described as pragmatists working in a situation that requires feasible and suitable solutions to the problem of measuring location value. It is our contention that the third generation techniques of spatially varying parameter models and spatial autocorrelation models will require greater industry verification before their use becomes more widely accepted.Originality/valueThis paper provides a detailed analysis of methodologies used to reflect the value of location over the last 50 years. The debate is taken forward by describing what will be the contribution to the development of the next generation of location‐specific modeling techniques.
Many researchers and mass appraisal practitioners have established the benefit of segmenting a st... more Many researchers and mass appraisal practitioners have established the benefit of segmenting a study area into two or more submarkets as a means of incorporating the large-scale effects of location within mass valuation models. The techniques applied for identifying locational submarkets or segments are quite varied, and often arbitrary. This article describes a segmentation technique based on the use of geographically weighted regression (GWR) which could be applied within the mass appraisal environment. The efficacy of the procedure is established by demonstrating improvements in predictive accuracy of the resultant segmented market models as compared to a baseline global unsegmented model for each of the study areas and then using the segmented markets in a series of spatially aware valuation models.
An Automated Valuation Model (AVM) that seeks to attain predictive accuracy must take into accoun... more An Automated Valuation Model (AVM) that seeks to attain predictive accuracy must take into account both spatial and temporal effects in the real estate market. A model structure that contains neither explicit spatial nor temporal variables is calibrated by a method that recognizes these variations in is calibration architecture. The method is conceptu-ally similar to Geographically Weighted Regression (GWR) except that it extends into the temporal domain. The methodology is explained and results provided illustrating spatio-temporal variations in value.
Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earl... more Page 1. Journal of Property Tax Assessment & Administration Volume 6, Issue 4 29 In an earlier article (Borst 2008), the Fourier expansion method was compared to two other methods of ac-counting for time in a hedonic model ...
Uploads
Talks by Richard Borst
Papers by Richard Borst