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Full-Text Articles in Business
Accounting For Locational, Temporal, And Physical Similarity Of Residential Sales In Mass Appraisal Modeling: The Development And Application Of Geographically, Temporally, And Characteristically Weighted Regression, Paul E. Bidanset, Michael Mccord, John R. Lombard, Peadar Davis, William J. Mccluskey
Accounting For Locational, Temporal, And Physical Similarity Of Residential Sales In Mass Appraisal Modeling: The Development And Application Of Geographically, Temporally, And Characteristically Weighted Regression, Paul E. Bidanset, Michael Mccord, John R. Lombard, Peadar Davis, William J. Mccluskey
School of Public Service Faculty Publications
Geographically weighted regression (GWR) has been recognized in the assessment community as a viable automated valuation model (AVM) to help overcome, at least in part, modeling hurdles associated with location, such as spatial heterogeneity and spatial autocorrelation of error terms. Although previous researchers have adjusted the GWR weights matrix to also weight by time of sale or by structural similarity of properties in AVMs, the research described in this paper is the first that has done so by all three dimensions (i.e., location, structural similarity, and time of sale) simultaneously. Using 24 years of single-family residential sales in Fairfax, Virginia, …
Evaluating Spatial Model Accuracy In Mass Real Estate Appraisal: A Comparison Of Geographically Weighted Regression And The Spatial Lag Model, Paul E. Bidanset, John R. Lombard
Evaluating Spatial Model Accuracy In Mass Real Estate Appraisal: A Comparison Of Geographically Weighted Regression And The Spatial Lag Model, Paul E. Bidanset, John R. Lombard
School of Public Service Faculty Publications
Geographically weighted regression (GWR) has been shown to greatly increase the performance of ordinary least squares-based appraisal models, specifically regarding industry standard measurements of equity, namely the price-related differential and the coefficient of dispersion (COD; Borst and McCluskey, 2008; Lockwood and Rossini, 2011; McCluskey et al., 2013; Moore, 2009; Moore and Myers, 2010). Additional spatial regression models, such as spatial lag models (SLMs), have shown to improve multiple regression real estate models that suffer from spatial heterogeneity (Wilhelmsson, 2002). This research is performed using arms-length residential sales from 2010 to 2012 in Norfolk, Virginia, and compares the performance of GWR …
The Effect Of Kernel And Bandwidth Specification In Geographically Weighted Regression Models On The Accuracy And Uniformity Of Mass Real Estate Appraisal, Paul E. Bidanset, John R. Lombard
The Effect Of Kernel And Bandwidth Specification In Geographically Weighted Regression Models On The Accuracy And Uniformity Of Mass Real Estate Appraisal, Paul E. Bidanset, John R. Lombard
School of Public Service Faculty Publications
The article presents a study which examines the performance of kernel and bandwidth specification in geographically weighted regression (GWR) models in mass real estate appraisal. The kernels employed in the study are the bi-square kernel and the Gaussian kernel. Data from the sales of single-family homes in Norfolk, Virginia from 2010 to 2012 are highlighted.