Extreme coefficients in Geographically Weighted Regression and their effects on mapping

Seong-Hoon Cho (), Dayton Lambert, SeungGyu Kim and Suhyun Jung

No 49117, 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin from Agricultural and Applied Economics Association

Abstract: This study deals with the issue of extreme coefficients in geographically weighted regression (GWR) and their effects on mapping coefficients using three datasets with different spatial resolutions. We found that although GWR yields extreme coefficients regardless of the resolution of the dataset or types of kernel function, 1) the GWR tends to generate extreme coefficients for less spatially dense datasets, 2) coefficient maps based on polygon data representing aggregated areal units are more sensitive to extreme coefficients, and 3) coefficient maps using bandwidths generated by a fixed calibration procedure are more vulnerable to the extreme coefficients than adaptive calibration.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 25
Date: 2009
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea09:49117

DOI: 10.22004/ag.econ.49117

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