Alan Reynolds poses a straightforward question: “Has American inequality really increased?” Based on my reading of the evidence, including his recent paper, article, and op-ed pieces, my answer is “Yes, inequality has increased.” I would guess, based on the tone of his writing, this is not the take-away conclusion he hopes to hear.
Reynolds is skeptical there is any clear evidence showing inequality has risen since the late 1980s. He offers a number of reasons for skepticism. Most of them boil down to this: The many data series that show income inequality has risen are not worthy of our trust, whereas the series that show very little trend should be accepted at face value.
Like many students of the income distribution, I take seriously some of Reynolds’s criticisms of the data on income disparities. No single data source is perfect, and a couple of them have serious flaws. An unwary user can draw misleading conclusions if the data problems are ignored. Reynolds points to some serious problems, and in many cases fair-minded experts will agree with him.
The problem is, he is strongly critical of data series that do not support his views, while he is usually silent about equal or more serious problems with data sets that show little change in inequality. Rather than do the hard work needed to measure the effect of particular data problems, he cherry-picks evidence to attack researchers whose results he finds displeasing.
Like many people with conservative inclinations he is enamored of consumption data in the BLS’s Consumer Expenditure Survey (CES). This is probably because it shows no overall change in inequality since about 1986. What Reynolds doesn’t mention is that the quality of the consumption data has deteriorated badly since the mid-1980s. In 1985, the CES uncovered 80% of the consumption that is recorded in the U.S. National Income and Product Accounts. By the year 2000, the percentage had fallen to 61%. If the trend in total consumption is not reliably reflected in the survey, it is hard to see why we should accept its estimate of the trend in the distribution of consumption. (Contrary to Reynolds claim, the CES, not the Survey of Consumer Finances (SCF), is the information source used by Johnson, Smeeding, and Torrey to derive estimates of the trend in consumption inequality. The SCF is a survey of wealth holdings, and thus it provides no direct evidence on household consumption.) So far as I know, no statistical series that tries to approximate total income has suffered such a terrible decline in quality as the data from the consumption survey. You’ll look long and in vain for any mention of this problem in Reynolds’s paper.
Reading his analysis, one is struck by how much it resembles a lawyer’s brief rather than an even-handed weighing of evidence. My reading of the evidence is reasonably straightforward, and it seems consistent with most of the income data available to us. Income inequality was higher at the end of the 1980s than it was in the beginning of that decade, and it was higher in 2005 than it was in 1989. Reynolds is certainly right when he says inequality did not increase “continuously” between 1979 and the present. It fell in some years, and remained approximately stable in others. On the whole, however, income inequality rose in the 1980s, and it also increased after 1989.
There’s an important difference between the rise in inequality in the earlier period and in the more recent period, however. Between 1979 and 1989, the percentage gap between the incomes of the middle-class and the poor got bigger, and the percentage gap between the rich and the middle class also got bigger. Inequality widened up and down the U.S. income distribution. Starting at some point in the early or mid-1990s, the proportional gap between low-income and middle-income Americans stopped rising and in fact probably shrank somewhat. After the early 1990s, the main way in which inequality widened is that the incomes of very well off Americans increased much faster than those of both the middle class and the poor.
Reynolds devotes most of his criticisms to the use of income tax data to measure trends in the income distribution. People who don’t know much about income distribution statistics might think this is because the income tax statistics are the country’s main source of information about distributional trends. They aren’t. Ever since the income distribution became a hot topic in the 1980s, the main source of information on which people rely comes from an annual Census Bureau survey of American households. The reason most people think inequality has risen since the late 1980s is because the household survey suggests it has.
Economists’ favorite indicator of inequality is the Gini coefficient. A higher Gini means there’s more inequality; a smaller Gini means there’s less. In 1989 the Census Bureau reported a Gini coefficient of household money income equal to 0.431. In 2005, the Bureau said the Gini coefficient was 0.469, which incidentally is the highest Gini coefficient ever recorded. By this measure, American inequality was about 9% higher in 2005 than it was in 1989. You can forgive most reporters and ordinary citizens for interpreting this Census statistic to mean that inequality has gone up.
There are problems with the Census Bureau’s main income statistics. One big problem is that the Bureau’s standard measure of income excludes in-kind benefits and capital gains, and it ignores the effects of income and payroll taxes. The Bureau recognizes these problems, and it publishes several alternative measures of inequality which use different definitions of income. If you look at some of the most comprehensive definitions of income, it turns out that inequality increased less, possibly much less, after 1989 than indicated by the Census Bureau’s headline number.
By the same token, however, inequality increased much faster under those alternative definitions during the 1980s than it did as measured by the Census Bureau’s headline number. So the Bureau’s headline number understated the growth in inequality during the 1980s and overstated the rise after 1989. Characteristically, Reynolds mentions the overstatement but fails to mention the understatement.
Reynolds could have written a very short paper in which he urged readers to ignore the Census Bureau’s headline measure of inequality and turn instead to a more obscure measure of inequality that is only published with a lag after the poverty and income statistics are first released. But that would have been a very short and uninteresting paper. It would also have been a very misleading one.
For a number of reasons, the Census Bureau survey does not provide accurate or consistent assessments of the incomes of the top 2% of income recipients. One reason is that respondents’ answers are top-coded, and the top-coding procedures have varied from time to time. Another is that the sample of high-income recipients is too small to give an accurate or consistent estimate of the incomes of the very top income recipients, say, those with incomes above $750,000 a year. Still another is that some income items that are important to the wealthy are under-reported in the Census survey. This means the Census Bureau probably gives us an underestimate of the gap between rich and middle-class families every year, no matter which concept of income we choose to measure.
What is worse, the underestimate will get bigger if top income recipients have incomes that grow faster than the incomes of people further down in the income distribution. That is precisely what most experts think has occurred since the late 1980s. It is also the interpretation of the data that Reynolds passionately wishes to reject.
If we cannot rely on the Census surveys to tell us what has happened to incomes at the top of the distribution, where might we turn? The scholars criticized by Reynolds have turned to income tax records. Another potential source of information is the Social Security Administration’s tabulations of the W-2 files, though this data series only covers wage earnings. The advantage of these administrative records is that they are supplied by many taxpayers. The records are so numerous that we can develop very accurate estimates of the incomes of people at the very top of the distribution.
Reynolds’ problem is that the data from both income tax returns and the W-2 records tell a simple and similar story. The relative incomes and wages of very top income recipients have been increasing much faster than the incomes and wages of people further down in the distribution. This was true in the 1980s, and it has also been true since 1990. Between 1990 and 2005 the median annual earnings of a full-time, year-round American worker increased about 4½%. What happened to the wages of top wage earners according to the W-2 records? At the 98th percentile, real earnings rose 33%; at the 99th percentile they rose 37%; at the 99.99th percentile, they rose 82%. Most people hearing those numbers would conclude – rightly, in my view – that wage inequality has gone up since 1990. That’s because 33%, 37%, and 82% are all bigger numbers than 4.5%.
Reynolds criticizes researchers who tabulate income reported on IRS 1040 forms without making any adjustment for the changing incentives to report income to the tax authorities. He notes, for example, that the 1986 Tax Reform Act made it advantageous to report capital income on 1040 forms rather than to partially shelter it by retaining earnings inside of a corporation. Tax reform in 1986 certainly increased the amount of income that top income recipients directly reported on their 1040s.
Reynolds’ problem here is that analysts he criticizes, like those at the CBO, recognize many of the problems of relying solely on income tax records, and they have tried to address them. CBO calculates total tax burdens faced by Americans, taking into account both the personal and the corporate taxes that they pay, directly on their own tax returns and indirectly through the corporations in which they have an ownership share. CBO may not do a perfect job, but at least it attempts to measure tax burdens and net incomes in an even-handed and consistent way. In addition, the CBO has developed a comprehensive measure of household income, including taxed and untaxed income, including in-kind benefits.
Reynolds is eager to remind readers that assets held in IRAs, 401(k)s, and pension plans generate current capital income that is not reported on income tax forms. (However, an unknown percentage of this income is reported on the Census Bureau’s household income survey.) If we corrected the omission, it would certainly add to the incomes of many middle-class households. Reynolds seems to believe this will reduce the measured trend toward greater inequality. He forgets that the assets in these plans are even more unequally distributed than ordinary income. If we included all the capital income that these plans produce, standard estimates of inequality would almost certainly rise, not fall. What matters for measuring the trend in inequality is the distribution of changes in untaxed capital income across the income distribution. Characteristically, Reynolds does nothing to learn how these changes have actually been distributed. He simply assumes (or hopes readers will conclude) that the additions to capital income will reduce the trend toward inequality. My suspicion is the opposite, but I would not try to persuade readers of this opinion before doing a careful analysis of the distribution of pension assets across households.
On an after-tax basis, the CBO’s estimates show that the average income of the top 1% of income recipients was 13.7 times the average income of the middle one-fifth of families in 1988-1990. By 2002-2004, this income ratio had risen to 15.9. Because 15.9 is a bigger number than 13.7, it seems reasonable to conclude inequality has gone up since the late 1980s. I don’t think Alan Reynolds has given us any persuasive reason to think this conclusion is wrong.
Reynolds is harshly critical of the tabulations and conclusions of analysts who find inequality has increased. It’s hard to see how these criticisms can have a big impact on our interpretation of the W-2 records. These clearly show a rise in wage inequality at the very top. In 1990 the ratio of the wage received by an earner at the 99.99th percentile to the median wage was 46:1. In 2005 that same ratio was 81:1. Yes, part of this increase was because of stock options, bonuses, and other nifty elements of the modern compensation package, but so what? In the old days, highly compensated wage earners did not receive these kinds of benefits or received much smaller helpings of them. Their total compensation was nearer to that of middle-income wage earners.
You can argue, as Reynolds does, that much of the increase in incomes at the top is due to turbo-charged stock prices and other special circumstances. Using the same line of reasoning you could also argue that, adjusting for the weather and the season, no homeowner in New Orleans ended up with a wet basement in August 2005. It might be true, but it’s not much comfort to the residents who had to flee a flooded home.
Ordinary citizens who think inequality has gone up are not making sophisticated adjustments for stock prices or other factors that vary from time to time. They’re reading news stories that tell how Robert Nardelli received compensation of $40–$45 million a year while failing to serve effectively as CEO of Home Depot. They’re asking why Hank McKinnell received an even more generous compensation package for doing an even worse job at Pfizer. Yes, these are horror stories; they are not data. But when careful economists go sifting through SEC filings, they find that the data match the horror stories. Top corporate officers’ pay rose faster than most people’s wages in the 1980s, and the growth differential was even bigger after 1990 than it was in the 1980s. If you think the typical U.S. worker got pay increases of 9½% a year after adjusting for inflation, as top corporate officers did in the 1990s, you move in different circles than the rest of us.
 David S. Johnson, Timothy M. Smeeding, and Barbara Boyle Torrey, “Economic Inequality Through the Prisms of Income and Consumption,” Monthly Labor Review, April 2005, http://www.bls.gov/opub/mlr/2005/04/art2full.pdf [pdf].