Description/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.
Document Type
Working Paper
Date
10-2005
Keywords
Income distribution, Inference, Poverty, Subset Selection
Series
Working Papers Series
Disciplines
Economics | Public Affairs, Public Policy and Public Administration
Recommended Citation
Horrace, William C.; Marchand, Joseph T.; and Smeeding, Timothy M., "Ranking Inequality: Applications of Multivariate Subset Selection" (2005). Center for Policy Research. 177.
https://surface.syr.edu/cpr/177
Source
local input
Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.
Additional Information
Working paper no. 70