Multidimensional polarization for ordinal data

Martyna Kobus () and Radosław Kurek
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Martyna Kobus: Polish Academy of Sciences
Radosław Kurek: Polish Academy of Sciences

The Journal of Economic Inequality, 2019, vol. 17, issue 3, No 1, 317 pages

Abstract: Abstract The dominant approach to evaluating distributional features of ordinal variables (e.g. self-reported health status) has been the Allison-Foster bipolarization ordering (henceforth AF). It has not yet been extended to a multidimensional setting. Here we fill this gap. A multidimensional extension of the AF relation is characterized by a sequence of median-preserving spreads on each dimension and association-changing switches. This extension does not pay attention to the dimensions’ association. We then offer one that does and characterize it in terms of classes of polarization measures and welfare functions. Based on these two orderings we construct polarization indices and develop statistical inference for them. We measure bidimensional polarization in educational attainment and life satisfaction across OECD members. Dependence does not affect whether or not countries dominate each other bidimensionally.

Keywords: Polarization; Ordinal data; Multidimensional inequality; Dominance (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s10888-018-9402-1

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