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Theory and methods for partitioned Gini coefficients computed on post-stratified data

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ABSTRACT The Gini coefficient is used to measure inequality in populations. However, shifts in the population distribution may affect subgroups differently. Consequently, it can be informative to examine inequality separately… Click to show full abstract

ABSTRACT The Gini coefficient is used to measure inequality in populations. However, shifts in the population distribution may affect subgroups differently. Consequently, it can be informative to examine inequality separately for these segments. Consider an independently and identically distributed sample split based on ranking and compute the Gini coefficient for each partition. These coefficients, calculated from post-stratified data, are not functions of U-statistics. Therefore, previous theoretical and methodological results cannot be applied. In this article, the asymptotic joint distribution is derived for the partitioned coefficients and bootstrap methods for inference are developed. Finally, an application to per capita income across census tracts is examined.

Keywords: partitioned gini; methods partitioned; post stratified; theory methods; stratified data

Journal Title: Communications in Statistics - Theory and Methods
Year Published: 2017

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