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Ranking inequality: Applications of multivariate subset selection

  • William Horrace


  • Joseph Marchand
  • Timothy Smeeding

Inequality measures are often presented in the form of a rank ordering to highlight their relative magnitudes. However, a rank ordering may produce misleading inference, because the inequality measures themselves are statistical estimators with different standard errors, and because a rank ordering necessarily implies multiple comparisons across all measures. Wityhin this setting, if differences between several inequality measures are *simultaneously* and statistically insignificant, the interpretation of the ranking is changed. This study uses a multivariate subset selection procedure to make simultaneous distinctions across inequality measures at a pre-specified confidence level. Three applications of this procedure are explored using country-level data from the Luxembourg Income Study. The findings show that simultaneous precision plays an important role in relative inequality comparisons and should not be ignored.

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Article provided by Springer in its journal The Journal of Economic Inequality.

Volume (Year): 6 (2008)
Issue (Month): 1 (March)
Pages: 5-32

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Handle: RePEc:kap:jecinq:v:6:y:2008:i:1:p:5-32
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