Template-type: ReDIF-Paper 1.0
Author-Name: Bhupathiraju, Samyukta
Author-Email: bhupathiraju@merit.unu.edu
Author-Workplace-Name: UNU-MERIT/MGSoG
Author-Name: Verspagen, Bart
Author-Email: verspagen@merit.unu.edu
Author-Workplace-Name: UNU-MERIT/MGSoG, and Maastricht University
Author-Name: Ziesemer, Thomas
Author-Email: ziesemer@merit.unu.edu
Author-Workplace-Name: UNU-MERIT/MGSoG, and Maastricht University
Title: Summarizing large spatial datasets: Spatial principal components
	 and spatial canonical correlation 
Abstract: We propose a method for spatial principal components analysis that has
	 two important advantages over the method that Wartenberg (1985)
	 proposed. The first advantage is that, contrary to Wartenberg's method,
	 our method has a clear and exact interpretation: it produces a summary
	 measure (component) that itself has maximum spatial correlation. Second,
	 an easy and intuitive link can be made to canonical correlation
	 analysis. Our spatial canonical correlation analysis produces summary
	 measures of two datasets (e.g., each measuring a different phenomenon),
	 and these summary measures maximize the spatial correlation between
	 themselves. This provides an alternative weighting scheme as compared to
	 spatial principal components analysis. We provide example applications
	 of the methods and show that our variant of spatial canonical
	 correlation analysis may produce rather different results than spatial
	 principal components analysis using Wartenberg's method. We also
	 illustrate how spatial canonical correlation analysis may produce
	 different results than spatial principal components analysis.         
Classification-JEL: R10, R15, C10
Keywords: spatial principal components analysis, spatial canonical correlation
	 analysis, spatial econometrics, Moran coefficients, spatial concentration 
Series: UNU-MERIT Working Papers
Creation-Date: 2013
Number: 011
File-URL: http://www.merit.unu.edu/publications/wppdf/2013/wp2013-011.pdf
File-Format: application/pdf
File-Size: 275 Kb
Handle: RePEc:unm:unumer:2013011