Inequality measures based on log power function-lognormal composite distribution

ABSTRACT

In this paper, we examine trends in inequality of Chinese rural household income from 1989 through 2015 using log power function lognormal composite distribution. Six inequality measures, Gini coefficient, Generalized entropy index, Theil’s entropy index, Atkinson index, Bonferroni index, and Zenga index, were computed by numerical methods. The results show that the all the inequality measures exhibit a similar pattern, and a steadily increased tendency through a slight slowdown for some in the time period of our analysis.

KEYWORDS:

• Income inequality
• inequality measures
• income distribution
• log power function-lognormal distribution

JEL CODES:

• C13
• I31
• O15
• O18

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author gratefully acknowledges the editor and two anonymous referees for their insightful comments and constructive suggestions that led to a marked improvement of the article. This work was supported by the National Social Science Fund of China, Grant No. 19BTJ051.