Gini Coefficient: Slicing the Economic Pie


Economists have many different ways of measuring the economy and making conclusions about how it is doing. Some measurements analyze the total amount of money spent in a given time period, while others look at how economic activity has grown and changed over time. Others try to paint a picture of how individuals or different groups of people are doing and how they relate to each other in an economy. 


One way to think about the economic situation of a country is how income is distributed across the population. This means analyzing what percentage of income is earned by the wealthiest and poorest groups and the size of the gap between the two. The most common tool for conducting this analysis is the Gini coefficient. 

Gini Coefficient

The Gini coefficient, also known as the Gini index or Gini ratio, named after Italian statistician Corrado Gini, is a measurement that describes how income is distributed across a population. It is also less commonly used to observe wealth distribution. To understand the Gini coefficient, we must first look at the Lorenz curve. The Lorenz curve is graphically represented with percentage of the population on the x-axis and percentage of income on the y-axis. The curve shows how income is distributed among a group of people or households. The Gini coefficient relates the observed distribution, shown by the Lorenz curve, to an imagined perfectly equal distribution of income. So, a country’s Gini coefficient represents how far its income distribution is from perfect equality, where income would be distributed equally across each member of society. 

How It Works

The Gini coefficient is calculated based on a graph displaying the Lorenz curve of observed data and the line of perfect equality, which is, by definition, the line y=x with a constant slope of 1. The line of perfect inequality, on the other hand, is horizontal along the x-axis until the very end of the axis, at which point it becomes perfectly vertical. The Gini coefficient is equal to the area between the line of perfect equality and the Lorenz curve, divided by the entire area below the line of perfect equality. The coefficient may range from 0, indicating perfect equality, to 1, representing perfect inequality. It’s also often described as a percentage, ranging from 0 to 100 percent. If the sample includes negative incomes, the Gini coefficient could be greater than 1, but this is not common.

The line x=y with a slope of 1 represents perfect equality because it shows that each percentage of the population controls that exact percentage of income. So, the coordinate (90,90) means that 90 percent of the total population earns 90 percent of the total income. However, the coordinate (90,75) would indicate that 90 percent of the population earns 75 percent of the total income. In such a society, some people are making more money than others, but the inequality is not extreme and the Gini coefficient would be closer to 0. We can also imagine the coordinate (90,45) which shows that 90 percent of the population controls only 45 percent of the income. Income in this society is distributed much more unequally and the Gini coefficient would be closer to 1. 

Economists use inequality metrics such as the Gini coefficient to track the progress of income distribution trends over time and across nations. These measurements incorporate data from each percentile of a population in a given year. This allows for the analysis of economic repercussions of events, such as wars and recessions, and policies, including tax increases and cuts, on a country-wide scale.

Applying It

Since its invention in 1912, the Gini coefficient has been used across the globe as a primary economic inequality metric. Current and past Gini coefficients are available by country through The World Bank. That being said, reducing various economic circumstances affecting a nation to a single value comes with many notable limitations. Most importantly, the Gini coefficient describes the way that cumulative income is distributed, not how much income there is in the first place. This means that very high - and very low - income nations can have the exact same Gini coefficient. The Gini coefficient also does not address demographics, including race, gender, and age, within populations, which are essential components in our discussion of economic inequality. In addition, some countries calculate their coefficients differently than others, like using either pre- or post-tax values for income, making it much more difficult to make effective comparisons. 

Despite these limitations, the data provided by the World Bank is a great starting point if you’re interested in getting a glimpse into the world’s economies and how they have changed over time. Take a deeper look by researching policies and social conditions that may have contributed to major shifts in income distribution. Notice which countries have the highest and lowest Gini Coefficients and compare it with other metrics like gross domestic product (GDP) growth. All this information can be used to question and judge which metrics are most useful for developing an accurate picture of the health of the global economy. 

Think Further

  1. What other information could be included alongside the Gini coefficient to make a more complete comparison of two countries’ income distributions?
  2. How might an increase in income tax for the rich affect a country’s income distribution and Gini coefficient? 
  3. How might a decline in labor unions affect a country’s income distribution and Gini coefficient?  


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Learn More

  1. “GINI Index (World Bank Estimate).” Data,
  2. Chappelow, Jim. “Gini Index Definition.” Investopedia, Investopedia, 29 Jan. 2020,
  3. Lamb, Evelyn. “Ask Gini: How to Measure Inequality.” Scientific American, Scientific American, 12 Nov. 2012,