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Ranking inequality: Applications of multivariate subset selection

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  • William Horrace

    ()

  • Joseph Marchand
  • Timothy Smeeding

Abstract

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. Within 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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Bibliographic Info

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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Web page: http://springerlink.metapress.com/link.asp?id=111137

Related research

Keywords: income distribution; inference; poverty; subset selection.; C12; C15; D31; D63; I32.;

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References

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Citations

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Cited by:
  1. Agostino Tarsitano & Rosetta Lombardo, 2013. "A Coefficient of Correlation Based on Ratios of Ranks and Anti-ranks," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 233(2), pages 206-224, March.
  2. Agostino Tarsitano & Rosetta Lombardo, 2011. "An Exhaustive Coefficient Of Rank Correlation," Working Papers 201111, Università della Calabria, Dipartimento di Scienze Economiche, Statistiche e Finanziarie (Ex Dipartimento di Economia e Statistica).
  3. Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2007. "Identifying technically efficient fishing vessels: a non-empty, minimal subset approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 729-745.
  4. Lena Lindahl, 2011. "A comparison of family and neighborhood effects on grades, test scores, educational attainment and income—evidence from Sweden," Journal of Economic Inequality, Springer, vol. 9(2), pages 207-226, June.

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