Good news!
However, the Gini index/coefficient has some cons to keep in mind:
"Cons of the Gini Coefficient
- Ignores Demographic Context: It cannot differentiate between where the inequality exists (e.g., whether the disparity is driven by a massive gap at the top or widespread poverty at the bottom).
- Different Distributions, Same Score: Two very differently structured economies can yield the exact same Gini coefficient, masking structural realities like regional disparities or aging populations.
- Not a Poverty Measure: A low Gini coefficient does not mean an economy is wealthy; it simply means everyone is relatively poor. Conversely, a high Gini coefficient tells you nothing about the absolute living standards of the lowest earners.
- Data Sensitivity and Scope: The coefficient is highly sensitive to the quality and source of data. For example, measuring pre-tax income versus post-tax wealth will produce drastically different results for the same population.
" (Google search)
"... The number of people who live in extreme poverty — i.e., less than $3 a day — is an important indicator to track the first part of this vision. To capture shared prosperity, the second part, requires a measure that includes not just the extreme poor — who constitute 10 percent of the global population today — but everyone. In addition, the measure captures both higher living standards through income growth and how it is distributed. ...
A measure that captures prosperity should account for both the level of welfare and level of inequality. A measure that captures inequality, such as the Gini index, is an example of a measure of inclusivity. The World Bank reports the number of economies with high levels of inequality, defined as those with a Gini index greater than 40. Based on this, the number of economies with high inequality has declined by more than a third in the past three decades. ..."
