Ranking Inequality: Applications of Multivariate Subset Selection

William C. Horrace (), Joseph Marchand and Timothy M. Smeeding
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William C. Horrace: Center for Policy Research, Maxwell School, Syracuse University, https://www.maxwell.syr.edu/directory/william-c-horrace

No 70, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

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. 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.

Keywords: income distribution; inference; poverty; subset selection (search for similar items in EconPapers)
JEL-codes: C12 D31 (search for similar items in EconPapers)
Pages: 47 pages
Date: 2005-10
New Economics Papers: this item is included in nep-dcm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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https://surface.syr.edu/cpr/93/ (application/pdf)

Related works:
Journal Article: Ranking inequality: Applications of multivariate subset selection (2008)
Working Paper: Ranking Inequality: Applications of Multivariate Subset Selection (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:max:cprwps:70

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