Your Money. Personal Finance. Your Practice. Popular Courses. Part Of. Elements of Inequality. Role of the Financial System. Legal Protections. Measuring Inequality. Theories Explaining Inequality. Models to Reduce Inequalilty. Economy Economics. Table of Contents Expand. What Is the Gini Index? Understanding the Gini Index. Graphical Representation.
The Gini Index Around the World. Key Takeaways The Gini index is a measure of the distribution of income across a population. A higher Gini index indicates greater inequality, with high-income individuals receiving much larger percentages of the total income of the population.
Global inequality as measured by the Gini index increased over the 19th and 20th centuries, but has declined in more recent years. Because of data and other limitations, the Gini index may overstate income inequality and can obscure important information about income distribution.
Article Sources. Investopedia requires writers to use primary sources to support their work. These include white papers, government data, original reporting, and interviews with industry experts. We also reference original research from other reputable publishers where appropriate. GE 1 is known as the Theil inequality index, named after the author who devised it in The Theil index is defined as follows:.
Another limitation of using the Gini index is whenever two or more countries share the same value of the Gini index but income inequality among them could be very different if taking into consideration the information on the income share held by the richest and that held by the poorest. For example, based on the data from the World Bank, in , Greece and Thailand have the same Gini index 0. That countries share the same Gini index but differ in the income gap between the richest and the poorest indicates that the Gini index alone cannot tell the difference in income inequality among countries.
Furthermore, Atkinson notes that the Gini index is more sensitive to changes in the middle of income distribution and less sensitive to changes at the top and the bottom of income distribution. The data used to calculate these inter-decile ratios or the ratios themselves including the Palma index are regularly updated and reported along with the Gini index by international organizations, such as the World Bank, the OECD, and the Human Development Report Office as the measures of income inequality.
From a mathematical and practical point of view, these values are more difficult to interpret and compare among countries since they have no upper bound relative to other inequality indices whose values are bounded. As noted in Eliazar , indices whose values are bounded are much more tangible to human perception than those whose values are unbounded.
In addition, by construction, these inter-decile ratios capture income inequality between the top and the bottom of distribution and ignore income of those in the middle of distribution. To overcome the limitations of the Gini index and the inter-decile ratios as discussed above, we devise an alternative method for measuring inequality. Our method is quite simple. These three indicators comprising the inequality index are selected based on availability, accessibility, and continuity of the data without the need to collect the data on income distribution at the micro level.
Our inequality index I takes values in the unit interval where the closer the index is to zero, the more equal the distribution of income and the closer the index is to one, the more unequal the distribution of income.
To demonstrate our method, we use the annual data on the Gini index and the income shares in from the World Bank a , b , c containing 75 countries and from the OECD IDD a , b comprising 35 countries. The reason to use the data in is that it has more countries than those in , , and For these reasons, we would like to define our inequality index I i as follows:.
Table 1 presents the results of our ranking of income inequality based on the Gini index using the World Bank database in The results indicate that the inequality index I can differentiate income inequality in case two or more countries share the same Gini index but differ in the income gap between the top and the bottom.
Thus, using our inequality index I , we can say that Greece has a higher level of income inequality than Thailand. Our results in Table 1 also show that when comparing the rankings of income inequality among countries using our inequality index I with those using the Gini index, there are 62 countries that their rankings have been changed while there are 13 countries whose rankings remain the same.
According to the World Bank database, during and , the Gini index of Mexico is around 0. In addition, our results from Table 2 show that when comparing the rankings of income inequality among countries using our inequality index I with those using the Gini index, there are 21 countries that their rankings have been changed while there are 14 countries whose rankings remain the same.
This suggests that the income inequality in Ireland is slightly higher than that in Switzerland, which could be distinguished by our inequality index I. However, our inequality index I could capture the dynamics of income inequality in Italy since the inequality index I shows a rising trend from 0. That two or more countries have the same value of the Gini index does not necessarily imply that these countries share the same level of income inequality. Likewise, two or more countries having the same ratio of the income share held by the richest to the income share held by the poorest does not always imply that income inequality among these countries is the same either.
The Gini index is known to be less sensitive to inequality at the tails of income distribution, whereas the ratios of income share of the richest to income share of the poorest do not account for inequality in the middle of income distribution.
To overcome the limitations of the Gini index and the inter-decile ratios as measures of income inequality, this study introduces a composite index for measuring inequality that does not require the micro-data of the distribution. Our inequality index is very simple to calculate.
The data on these three indicators are also available, easy to access, and regularly updated by countries and international organizations. This implies that there are other aspects of differences in income inequality among countries that our inequality index would not be able to capture. In this way, the whole range of the Lorenz curve would be covered. This is one way to take into account the difference in income inequality in case two or more countries share the same inequality index but have dissimilar Lorenz curves.
There might be other alternative ways to account for such a difference, which await future research. Last but not least, we hope that our simple method for measuring inequality could be applied not only to socioeconomics, but also to broad scientific disciplines as a measure of statistical heterogeneity and for size distributions of any non-negative quantities. The alternative index for any given country i can be defined as follows:. Since these measures were introduced, they have been applied to topics other than income and wealth, but mostly within Economics Cowell, , ; Jenkins, ; Sen, G is a measure of inequality, defined as the mean of absolute differences between all pairs of individuals for some measure.
The minimum value is 0 when all measurements are equal and the theoretical maximum is 1 for an infinitely large set of observations where all measurements but one has a value of 0, which is the ultimate inequality Stuart and Ord, When G is based on the Lorenz curve of income distribution, it can be interpreted as the expected income gap between two individuals randomly selected from the population Sen, If the x values are first placed in ascending order, such that each x has rank i, the some of the comparisons above can be avoided and computation is quicker:.
Originally thought of by Corrado Gini in , it is most commonly used to measure income inequality. Both the World Bank and the UN produce annual statistics for the Gini coefficient, and many governments use it to track its inequality.
The Gini coefficient, also known as the Gini Index, is widely used across the world. It is one of the most efficient and easily understood figures on inequality, which makes it easier to compare countries. At the same time, it does have its drawbacks which we will look at later. There are two ends of the measurement, ranging from 0 to 1. At 1, the measurement would show that one person receives all the national income.
By contrast, a measurement of 0 would suggest that income is perfectly split between all members of society. The Gini coefficient is calculated using the Lorenz Curve. This can be illustrated in the graph below. To explain, each percentile is plotted on the graph with a line situated at 45 degrees. This line represents perfect equality.
So the bottom 10 percent of the population receives 10 percent of income, whilst the top 10 percent also receives 10 percent of income.
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