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

In: New Directions in Spatial Econometrics

Author

Listed:
  • Arthur Getis

    (San Diego State University)

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.

Suggested Citation

  • Arthur Getis, 1995. "Spatial Filtering in a Regression Framework: Examples Using Data on Urban Crime, Regional Inequality, and Government Expenditures," Advances in Spatial Science, in: Luc Anselin & Raymond J. G. M. Florax (ed.), New Directions in Spatial Econometrics, chapter 8, pages 172-185, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-79877-1_8
    DOI: 10.1007/978-3-642-79877-1_8
    as

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