Journal Article

No. 2011-11 | August 29, 2011
Polarization Measurement and Inference in Many Dimensions When Subgroups Can Not Be Identified PDF Icon

Abstract

The most popular general univariate polarization indexes for discrete and continuous variables are extended and combined to describe the extent of polarization between agents in a distribution defined over a collection of many discrete and continuous agent characteristics. A formula for the asymptotic variance of the index is also provided. The implementation of the index is illustrated with an application to Chinese urban household data drawn from six provinces in the years 1987 and 2001 (years spanning the growth and urbanization period subsequent to the economic reforms). The data relates to household adult equivalent log income, adult equivalent living space, which are both continuous variables and the education of the head of household which is a discrete variable. For this data set combining the characteristics changes the view of polarization that would be inferred from considering the indices individually.

Data Set

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The data set for this article can be found at: http://hdl.handle.net/1902.1/16236

JEL Classification

C14 C30 I32

Citation

Gordon Anderson (2011). Polarization Measurement and Inference in Many Dimensions When Subgroups Can Not Be Identified. Economics: The Open-Access, Open-Assessment E-Journal, 5 (2011-11): 1—19. http://dx.doi.org/10.5018/economics-ejournal.ja.2011-11

Assessment

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