The Gini Index: Measuring Income Distribution

Income inequality is the imbalance of income found within a particular group of people. Put simply, certain parts of the population have lower levels of income compared to others. This means that inequality is higher when the distribution of income isn't equal. The divide is often accompanied by the distribution of wealth, too. When income inequality exists, so too does wealth inequality such that people with a higher proportion of income often have a greater degree of wealth.

But is there a way to measure this imbalance? This is done through the Gini coefficient. This measure was specifically designed to measure this factor, which has implications for the economic health and national policy of a nation. This article explains how to interpret and apply the Gini index. It also highlights some of the limitations that are associated with the index—notably, its accuracy and its sensitivity to sample sizes and changes.

Key Takeaways

  • The Gini index is a way to measure income and wealth inequality.
  • The index was developed by statistician Corrado Gini in 1912.
  • It provides a range that falls between zero and one, where zero means perfect equality and one indicates perfect inequality.
  • The Gini coefficient can be mapped out graphically on the Lorenz curve where the x-axis represents the population and the y-axis maps out the income.
  • The Gini coefficient depends on accurate and reliable data and proper sample sizes.

Interpreting the Gini

The Gini index is based on the Gini coefficient, which is a statistical dispersion measurement that ranks income distribution on a scale between zero and one. The measure was developed by Italian statistician Corrado Gini in 1912 and is still in use today. Although it can be used to measure the inequality of any distribution, it is commonly associated with wealth.

Here's how it works. A reading of one indicates perfect inequality. But what happens if everyone had exactly the same amount of money? In this case, the index would register a reading of zero. The number can be multiplied by 100 in order to express it as a percentage.

The Gini coefficient for a country is often displayed visually using a graph called the Lorenz curve, as depicted below. The x-axis represents the percentage of the population while the total percentage of income is shown along the y-axis.

Example of Lorenz Curve
Example of Lorenz Curve.

Gini In the Real World

Statistics for The World Factbook produced by the U.S. Central Intelligence Agency cite a range from 0.23 to 0.63. The following are some of the key findings from the data:

  • South Africa, Namibia, and Zambia had the highest coefficients with 0.63, 0.59, and 0.57 respectively.
  • Europe generally posts relatively low numbers with the United Kingdom posting about 0.35. Bulgaria had the highest coefficient at 0.4 and Faroe Islands had the lowest at 0.23.
  • The United States ranked in the 54th spot globally with a coefficient of 0.41 while Canada came in at 128 with 0.33.
  • China's coefficient of 0.38 put it in the 73rd spot and India came in 98th with 0.36.

While low numbers represent greater equality, low numbers aren't always a perfect indicator of economic health. Nations such as Sweden, Belgium, and Iceland all cluster in the 0.20s, as do a host of former Soviet nations. In the former nations, the numbers are close because residents generally have a high standard of living, while in the latter the close numbers suggest a relatively equal distribution of poverty.

Even in affluent countries, the Gini index measures net income rather than net worth, so the majority of a nation's wealth can still be concentrated in the hands of a small number of people even if income distribution is relatively equal. Consider that the significant holdings of non-dividend paying stocks, for example, could give an individual a low income but simultaneously signal a high net worth.

Wealth Inequality, World Bank
Wealth Inequality, World Bank.

Tracking Trends

Seeing a single number provides a picture of the distribution at a given point in time while tracking the trends provide a picture of the direction in which a nation is moving.

For example, the numbers in the United States are rising and have trended that way for more than three decades. As such, the rich are truly getting richer.

This trend is reflected in the phenomenon of the disappearing middle class, as income distribution increases at the top end of the scale. This forces those in the middle toward the lower end of the scale.

The Gini index can fall below zero and can go above one. Negative values mean that wealth is lacking and people have more debts than assets while the reverse is true when it passes the top range.

Implications for National Policy

The Gini index can help nations and leaders track poverty levels. When the income distribution becomes more unequal, government officials are able to delve into the issue and determine some of the root causes.

The Gini index can also be compared to gross domestic product (GDP) figures. Some may believe that an increase in GDP means that a country's citizens are doing better for themselves. But that isn't necessarily the case when the Gini index also rises. When this happens, it suggests that the majority of the population may not be experiencing increased income.

When it comes to income inequality, governments will sometimes redistribute wealth through certain social programs and taxation policies.

Shortcomings of the Gini Index

While the Gini index is able to provide a basis for measuring income distribution, there are some downfalls that are associated with it.

As noted above, the Gini index depends on the accuracy of the dependent data, including figures related to people's incomes and GDP. If these figures aren't accurate, you won't get reliable Gini coefficients. Informal data can often put certain countries (especially developing nations) at the lower end of the spectrum. And it's often hard to determine how wealth is distributed when data is protected as is the case in tax havens.

Sample sizes are also just as important and can skew the results. Smaller countries and those that don't release a significant amount of economic data often end up with lower scores on the Gini index. The type of data can also make a difference. For instance, some countries release data that takes pretax earnings into account while others do so using after-tax income. This can provide an apples-to-oranges comparison of countries, making the comparison pointless.

The fact that the coefficient is a single-digit reading is also problematic. That's because it doesn't actually relate any information related to the distribution of wealth in a given country, especially when it comes to gender, social class, age, race, and differing abilities. In essence, it lumps everyone into a single group.

There is, however, an alternative to the Gini index that takes certain changes into account. The developers of the Palma ratio claim it is more intuitive. That's because it looks at the higher and lower ends of the income scale. It is the ratio of the top 10% of a country's gross national income (GNI) divided by the lowest 40% of the population. A country that has a Palma ratio of three means that the top 10% of earners are making three times more than the bottom 40% of earners in a country.

What Is the Gini Coefficient?

The Gini coefficient was developed by Corrado Gini in 1912 and is still used today. It is used to measure income and wealth inequality within a particular group—usually a specific country. It provides a single-digit reading between zero and one. This reading highlights the degree to which income and wealth inequality exists within the group. A reading of 0 means that individuals are perfectly equal while a reading closer to one indicates the population is perfectly unequal.

How Do You Calculate the Gini Coefficient?

You can calculate the Gini coefficient by using the Lorenz Curve. It maps out income and wealth inequality within a particular group on a graph. The x-axis represents the population from lowest to highest. The y-axis, on the other hand, shows the increasing percentage of owned wealth or income. In a group that is equal, the y would equal x.

What Does a Gini Coefficient of 0.1 Mean for a Country?

A Gini coefficient of 0.1 means that a country has good equality when it comes to income and wealth distribution. That's because a coefficient of zero means perfect equality. Countries with a reading of one means that there is perfect inequality so if the score fell closer to that range, there would be a higher degree of inequality in the country.

Which Country Has the Highest Gini Coefficient?

South Africa has the highest Gini coefficient. According to data from the World Factbook published by the CIA, it has a coefficient of 0.63 or 63%.

The Bottom Line

If the gap between rich and poor continues to increase, the evaluation of the income gap can become more important. And the Gini index can provide a great starting point when it comes to measuring that income inequality. Knowing the Gini index numbers is no panacea, but this measure does provide a way to quantify and track the direction in which a society is moving, which may open the door for dialogue and potential solutions.

But keep in mind, though, that there are limitations associated with using this measure. The coefficient is only as reliable as the data used to calculate it and it only provides a single-digit reading, which doesn't take different groups within the sample into account.

Article Sources
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  1. BBC News. "Who, What, Why: What is the Gini coefficient?"

  2. Journal of Economic Surveys. "The Gini Concentration Index: A Review of the Inference Literature."

  3. United States Census Bureau. "Gini Index."

  4. Towards Data Science. "Clearly Explained: Gini coefficient and Lorenz curve."

  5. Central Intelligence Agency. "Gini Index coefficient - distribution of family income."

  6. Pew Research. "1. Trends in income and wealth inequality."

  7. NetGreen. "Inequality: Where Palma is better than Gini."

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