Premium
Stochastic dominance and decomposable measures of inequality and poverty
Author(s) -
Zheng Buhong
Publication year - 2021
Publication title -
journal of public economic theory
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.809
H-Index - 32
eISSN - 1467-9779
pISSN - 1097-3923
DOI - 10.1111/jpet.12496
Subject(s) - stochastic dominance , lorenz curve , inequality , dominance (genetics) , mathematics , econometrics , poverty , distribution (mathematics) , degree (music) , measure (data warehouse) , economics , statistics , gini coefficient , economic inequality , computer science , mathematical analysis , biology , biochemistry , physics , database , acoustics , gene , economic growth
In this paper, we characterize some new links between stochastic dominance and the measurement of inequality and poverty. We show that: for second‐degree normalized stochastic dominance (NSD), the weighted area between the NSD curve of a distribution and that of the equalized distribution is a decomposable inequality measure; for first‐degree and second‐degree censored stochastic dominance (CSD), the weighted area between the CSD curve of a distribution and that of the zero‐poverty distribution is a decomposable poverty measure. These characterizations provide graphical representations for decomposable inequality and poverty measures in the same manner as Lorenz curve does for the Gini index. The extensions of the links to higher degrees of stochastic dominance are also investigated.