Spatial Filtering in a Regression Framework: Examples Using Data on Urban Crime, Regional Inequality, and Government Expenditures

Arthur Getis
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Arthur Getis: San Diego State University

Chapter 8 in New Directions in Spatial Econometrics, 1995, pp 172-185 from Springer

Abstract: Abstract In a recent paper [Getis (1990)], I develop a rationale for filtering spatially dependent variables into spatially independent variables and demonstrate a technique for changing one to the other. In that paper, the transformation is a multi-step procedure based on Ripley’s second order statistic (1981). In this chapter, I will briefly review the argument for the filtering procedure and propose a simplified method based on a spatial statistic developed by Getis and Ord (1992). The chapter is divided into four parts: 1) a short discussion of the rationale for filtering spatially dependent variables into spatially independent variables, 2) a review of a Getis-Ord statistic, 3) an outline of the filtering procedure, and 4) three examples taken from the literature on urban crime, regional inequality, and government expenditures.

Keywords: Spatial Autocorrelation; Spatial Dependence; Government Expenditure; Spatial Effect; Spatial Association (search for similar items in EconPapers)
Date: 1995
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DOI: 10.1007/978-3-642-79877-1_8

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