Valuing Locational Externalities: A GIS and Multilevel Modelling Approach

By S. Orford. 2002

119 citations recorded by the source corpus.

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A Big Data–Based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore (2018, background): “Because housing characteristics cannot be separated and are normally traded in bundles, real estate is normally treated as a heterogeneous good with a variety of attributes, including structural and locational or spatial attributes (Can 1992; Orford 2002).”
Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI (2007, unknown): “Given the traditional neglect of locational externalities by econometric models and the methodological constraints in incorporating spatial information, studies on locational effects have drawn inadequate attention (Orford, 2002).”
The Impact of Surrounding Land Use and Vegetation on Single-Family House Prices (2004, methodology): “…Griffith, 2002; Griffith, 1996), artificial neural networks (Din et al, 2001; Nguyen and Cripps, 2001; Tay and Ho, 1992; Worzala et al, 1995), the stochastic approach (Tse, 2002), or the multilevel approach (Orford, 2000; 2002), although presenting interesting avenues, were not used at this time.”