Note: An updated version of this graph is here.
Income inequality in the United States has been rising since the 1970s. What is the most effective way to succinctly convey this fact?
Here is my choice (a pdf version is available here):
The chart shows average inflation-adjusted incomes of the poorest 20%, middle 60%, and top 1% of households since the 1970s. The incomes include government transfers and subtract taxes. For the bulk of American households, incomes have increased moderately or minimally. For those at the top, by contrast, they have soared.
Why This Chart?
Here are what I think should be the principal considerations. Some are obvious, others perhaps not.
1. Tell the substantive story clearly. The graph does a good job of conveying the two key aspects of the rise in income inequality over the past generation. One is the dramatic increase in incomes for households at the very top. In 1979 household income among those in the top 1% averaged $325,000 (in 2005 dollars). By 2005 that had increased to nearly $1.1 million.
The other is stagnation at the bottom and modest growth in the middle. Among the poorest 20% of households, average income was $14,500 in 1979 and $15,500 in 2005. Among the middle 60% of households, average income rose from $42,000 to $51,000.
2. Use the best available data. There are various sources of income data, including the annual Current Population Survey (CPS), the decennial census, IRS income tax records, and others. The data used in this chart are from the Congressional Budget Office (CBO), which has merged tax records with the Current Population Survey. They’re available here. Tax records are incomplete, because many low-income citizens do not file tax returns. But they have the advantage of providing relatively good data on those with high incomes. The CPS data are from interviews of 50,000 or so households. They are more representative of the population. But for various reasons the CPS data are not as good for those at the top of the income distribution. Also, the CPS data are for pretax income. The CBO data arguably combine the best features of these two sources.
The main disadvantage of the CBO data is that they begin in 1979. It’s thus not possible to see the contrast with earlier periods. I say more about this below.
3. Show incomes, rather than a summary inequality measure. Common inequality measures include the Gini coefficient, percentile ratios (e.g., P90/P50 and P50/P10), and income shares (e.g., the income share of the top 1%). They are quite useful. Nice examples from the Economic Policy Institute’s The State of Working America are here, here, and here. But they have two drawbacks. One applies to the Gini index, which is the most commonly-used inequality statistic. It doesn’t identify where in the income distribution the rise in inequality has occurred. For example, suppose the Gini rises over time. Is that because those at the top have pulled farther away from everyone else? Because those at the bottom have fallen behind? Because of a widening spread in the middle? All three? Something else?
To address this problem analysts often turn to percentile ratio or income share measures. These, however, fail to provide information about trends in actual incomes. Suppose, for example, that the 90/50 ratio increases over time. Is that because the incomes of those at the top have risen faster than the incomes of those in the middle? Because incomes at the top have risen while those in the middle have been stagnant? Because both have decreased but those at the top have done so less rapidly? Something else?
Showing trends in actual incomes — adjusted for inflation, of course — overcomes these problems. A potential drawback of doing so is that it may not be obvious from the raw income data whether or not inequality has increased, or by how much. If the magnitude of the rise in inequality is small, it may be preferable to use an inequality measure. For the United States over the past generation, however, the increase in inequality is easy to spot from data on incomes.
4. Show income levels, rather than growth rates. A common and helpful inequality graph is a bar chart showing rates of growth of real incomes during different periods for households at various points in the income distribution. See here for an example. This gives a good sense of the magnitude of the change in inequality, but it doesn’t convey anything about the magnitude of the level of inequality.
5. Show the full trend, rather than snippets or period averages. A frequent choice is to show the level of inequality in selected years, or averaged over groups of years (e.g., business cycles). That’s fine in many instances, but when there is relative stability within periods it is usually preferable to show all data points.
A Helpful Supplement
The chief limitation of the above graph is that it doesn’t fully convey what has happened at the bottom of the distribution since the 1970s. It is clear from the chart that incomes for those in the top 1% have jumped dramatically and that incomes for much of the bottom half of the distribution have been stagnant. But the latter aspect is not highlighted to the degree it could be.
Here is a second chart that helps to flesh out this point:
This chart shows trends in real incomes for families at the 20th, 40th, 60th, 80th, and 95th percentiles of the income distribution. In order to go back to the 1940s we have to accept two data limitations: the income data, from the CPS, are pretax; and the units are families rather than households, so adults living alone are not included. These data are available here.
Between the late 1940s and the mid-1970s incomes increased at roughly the same pace throughout the distribution; they doubled for each group. Since the 1970s the story has been quite different. At the 95th percentile, incomes have continued to rise. At the upper-middle levels (the 80th and 60th percentiles), they’ve increased at a moderate pace. In the bottom half of the distribution (the 40th and 20th percentiles), they’ve been fairly stagnant.
This chart makes it clearer that a defining feature of rising inequality in the United States is the stagnation of incomes in the lower half of the distribution. Even at the 95th percentile, where incomes have increased appreciably since the 1970s, the rate of growth did not accelerate relative to earlier years; the average growth rate of family income at the 95th percentile was 1.5% per year between 1979 and 2005, compared to 2.4% per year between 1947 and 1979.
If you’ve seen an inequality graph that is as good or better, please let me know.