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How do we know income inequality is getting worse?

President Obama will make economic inequality a central theme of his State of the Union address on Tuesday, according to reports, highlighting the issue's emergence as a key political issue.

Less clear is whether economics itself has much to offer in ensuring that the gains of economic growth are distributed equitably. As Harvard Business Review executive editor Justin Fox recently wrote:


That is, economics can be helpful in characterizing the degree of inequality that exists, and it can help to explain why income is distributed so unequally. But economics tells us nothing at all about what the distribution of income should be. That is a political and moral question that is best left to others to decide.

Economists are split on why inequality has been rising, with the dividing line mainly between those who believe technology and globalization are the key factors that account for the rise in incomes at the very top, and others citing factors such as the decline in unionization and the decline in tax rates at the top as the wealthy have captured the political process and successfully eroded union support, lowered their tax burdens and so on.

Where economists have done a bit better is in characterizing the degree of inequality, but even here there is some disagreement. Should we look at pre- or post-tax incomes? Should we include programs such as unemployment compensation as part of income? Should we focus on income or consumption? What time period should we consider in measuring inequality? And in making such measurements, should we look at the nation as a whole, at individual states, or some other geographic or demographic breakdown?

There are two common two common ways of measuring the degree of inequality. One is to build graphs showing how the share of the nation's income has changed over time for particular income groups. The second is to calculate what is known is the Gini coefficient. For example, here is a graph from economists Thomas Piketty and Emmanuel Saez documenting how the share of income for the top 10 percent of income earners has changed between 1917 and 2012 (the last year for which data are available):


Note, however, that most of the change is due to the incomes not of the top 1 percent, but rather of the top 0.1 percent. Again, from Piketty and Saez:


This is a useful approach that gives considerable detail on how income shares have changed over time for different income groups in the economy. However, it's also useful to arrive at a single number that characterizes the degree of inequality, and for that the most common measure is the Gini coefficient.

The Gini coefficient varies between zero and one. A value of zero indicates that everyone has exactly the same income -- there is no inequality at all. By contrast, a value of one represents maximal inequality -- one person gets all the income and everyone else gets nothing.  More generally, values between zero and one indicate the degree to which the income distribution deviates from a perfectly equal distribution, with the distribution becoming more and more unequal as the Gini coefficient approaches one.

In the U.S. the Gini coefficient has been rising steadily since the late 1960s:


The Gini for the U.S. is also higher than in many other countries. For example, this analysis from the Pew Research Center shows that “the U.S. has one of the most unequal income distributions in the developed world, according to data from the Organization for Economic Cooperation and Development — even after taxes and social-welfare policies are taken into account.”

The Gini coefficient has many advantages. It is easy to calculate, allows changes in inequality to be tracked over time, and enables cross-region and cross-country comparisons.

But the Gini coefficient is not a perfect measure of inequality. For example, since the Gini coefficient is based upon relative rather than absolute measures of income, two countries with vastly different per capita incomes can have identical Gini coefficients. So the Gini does not tell us about living standards.

In addition, even when the total income and population of two countries are identical, the same Gini coefficient can arise from very different income distributions. To illustrate this, if the lower half of the income distribution has no income at all, and income is equally distributed across the upper half of the population, the Gini coefficient will be 0.5. But it will also be 0.5 if the lowest three-quarters of the population receives a quarter of total income, and the upper quarter of the income distribution receives three-quarters of the country’s total income.

Thus, economies with total income and Gini coefficients that are very similar can have very different distributions of income.

Despite these problems with the Gini coefficient, it is a useful and popular measure that summarizes the degree of income inequality with a single number. But it is best used in conjunction with other approaches such as the graphical technique outlined above that give more detailed information on how the distribution of income among various groups is changing over time.
