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Gini Coefficient

Gini Coefficient

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Gini coefficient is a common way to measure inequality of income/wealth across a population in a region. The coefficient ranges from 0 to 1, with 0 representing perfect equality and 1 representing perfect inequality. It helps to give an overview on how income/wealth in an economy is distributed.

Gini Coefficient Overview

Gini coefficient is a common way to measure inequality of income/wealth across a population in a region. The coefficient ranges from 0 to 1, with 0 representing perfect equality and 1 representing perfect inequality. It helps to give an overview on how income/wealth in an economy is distributed.

Insight analysis and Assumptions

China’s Gini coefficient reached a peak at 0.491 in 2008 and then began to decline for the first time since the “Reform and Opening” in 1978. It maintained in a level between 0.46-0.47 since 2009. There are a few factors contributing to the inequality in China. Firstly, the solidification of the lowest and highest income households is more pronounced in recent years based on different socioeconomic means. Secondly, there are structural factors where big income gaps emerged between urban and rural areas, Southeast versus Northeast and a few western regions and different industries. To read other income and wealth topics, please visit related subjects: Income distribution (link), Grey income (link) and Household wealth (link).

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Demographic data

The Dataist data service provides demographic data for China 31 provinces and 300 prefecture level cities. Data include population level and growth rates by gender, age-groups and urban/rural split. Data range covers period from year 2000 up to 2050.

Source and methodology

The Dataist demographic data for China are based on the China demographic surveys by the National Bureau of Statistics, the 5th survey in 2000, 6th survey in 2010 and 7th survey in 2020, and generated by the Dataist demographic forecast model. The model tracks the demographic natural growth (deaths and births), as well as migration trends, in order to forecast the population changes in the near future and longer-term period.

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