Combining geographic information systems and regression models to generate locational value residual surfaces in the assessment of residential property values

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Locational Value Residual Surface (LVRS) has been suggested as an alternative to resolving the difficulty in the traditional modelling of locational influence on property values in a particular area. The objective of this paper was to compare the relative performance of models that apply locational value residual surface (LVRS) and the traditional multiple regression models in the prediction of residential property values. A controlled sample of 125 single- and double-storey residential properties was used to construct regression models. It was found that models applying LVRS were marginally better than the traditional models in predicting property values.

Original languageEnglish
Pages (from-to)35-62
Number of pages28
JournalPacific Rim Property Research Journal
Volume13
Issue number1
Publication statusPublished - 1 Mar 2007
Externally publishedYes

Fingerprint

System model
Property values
Geographic information systems
Residential property
Regression model
Modeling
Relative performance
Multiple regression
Prediction

Keywords

  • Geographical Information System (GIS)
  • Locational factors
  • Locational value residual surface (LVRS)
  • Multiple regression analysis (MRA)
  • Residential property values

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)

Cite this

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abstract = "Locational Value Residual Surface (LVRS) has been suggested as an alternative to resolving the difficulty in the traditional modelling of locational influence on property values in a particular area. The objective of this paper was to compare the relative performance of models that apply locational value residual surface (LVRS) and the traditional multiple regression models in the prediction of residential property values. A controlled sample of 125 single- and double-storey residential properties was used to construct regression models. It was found that models applying LVRS were marginally better than the traditional models in predicting property values.",
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