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Measuring Inequality: Gini Coefficient
Measuring Inequality: Gini Coefficient
The Gini coefficient, named after Italian statistician Corrado Gini, serves as a vital measure of income or wealth inequality within a given population. It's a numerical value that ranges between 0 and 1, where 0 signifies a state of perfect equality, indicating that every individual or household within the population possesses an equal share of income or wealth. On the other hand, a Gini coefficient of 1 represents perfect inequality, meaning one entity holds all the income or wealth, while everyone else has none.
The Lorenz Curve and Gini Coefficient
The Lorenz Curve and Gini Coefficient
The first thing we need to do is split the total population into 5 "Quintiles", each representing 20% of the population, based on the percentage share of the total income they have collectively. We can see this presented in the table below, where the lowest 20% of the population collectively have 5.2% of the overall income of an economy. We then have the next 20% which has 9.3% of the overall income of an economy. This continues to the Top 20% of the population, collectively has 46.7% of the entire income in the economy.
The first thing we do is plot the lowest 20% (x axis) at 5.2% (Y axis) of the income.
The key thing to remember next is that the axis are cumulative %. Therefore, to plot the next values, we have to add together the lowest 20% and the next 20%. Therefore for 40% of the population, we add together 5.2+9.3 = 14.5%. Therefore 40% of the population has 14.5% of the income cumulatively.
Once we have plotted the Lorenz curve, we can calculate the Gini Coefficient. To do this, we need to calculate the value of area A and area B. Once we have these values, we can calculate the Gini Coefficient by: Gini Cofficient = A/(A+B)
IT IS IMPORTANT TO NOTE YOU DO NOT NEED TO BE ABLE TO CALCULATE THE GINI COEFFICIENT
Real Life Data
Real Life Data
The data below provides some examples are high and low Gini coffiecients by regions of the world. It is important to remember that this data can change over time as well as by source of information and the methodology used. Therefore, it is recommended to use wording such as:
The gini coefficient for Sweden in 2021, was approximatly 0.3
It is also important to note that you may also see the figure expressed as figures between 0 & 100 (Gini Index) v 0-1 (Gini Coefficient)
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