A Comparison of Localized Regression Models in a Hedonic House Price Context

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Modelling hedonic residential rents for land use and transport simulation while considering spatial effects (2010, methodology): “…therefore, it may be regarded as the one which accounts best for the spatial variation. ey concluded that by allowing parameters to vary spatially, estimation accuracy of the response variable improves dramatically while spatial biases diminish to nominal amounts (Farber and Yeates 2006, 417).”
Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria (2014, background): “Extending Farber and Yeates (2006), who detected extreme coefficients which might emerge from local distributional irregularities, Cho et al. (2009) provide evidence that fixed bandwidths and less spatially dense data are potentially more vulnerable to extreme coefficients.”
A Simulation-Based Study of Geographically Weighted Regression as a Method for Investigating Spatially Varying Relationships (2011, methodology): “Farber and Yeates (2006) conclude that the prevalence of counterintuitive and extreme GWR coefficients pose a threat to the adoption of GWR. Farber and Päez (2007) suggest that volatility in the coefficient estimates may be due to the procedure used to select the bandwidth size required for…”