Why Change the Subject?

Gary Burtless rightly emphasizes that “economists’ favorite indicator of inequality is the Gini coefficient,” but “the Bureau’s standard measure of income excludes in-kind benefits and capital gains, and it ignores the effects of income and payroll taxes.” That is why I presented a chart of 25 years of Gini coefficients[pdf] for the Census Bureau’s measure of “disposable income” — which adds transfer payments and taxable capital gains, but subtracts income and payroll taxes.

Suppose that instead of providing data for 25 years, I had mentioned only two years as Burtless, Bernanke, Piketty and Saez and other keep doing. I could then say the Gini coefficient for disposable income fell from 0.41 in 1986 to 0.40 in 2004, proving inequality has fallen for more than 20 years. Or I could say the Gini coefficient rose from .39 in 1985 to .40 in 2004, proving inequality has increased. We cannot find out what happened when by showing data for only two years and then drawing an imaginary line between them.

A look at the past 25 years of Gini coefficients shows no significant and sustained increase in inequality of disposable income since 1988, or even 1985. Thoma claims, “The Gini coefficient evidence is by no means the refutation of rising inequality that Reynolds would have us believe.” Amazingly, he refers only to a Gini coefficient for wealth — as if income doesn’t matter. After ignoring all income statistics, he accuses me of “an incomplete presentation of the evidence” and “attempts to cloud the issue.”

Thoma asks, “What about the Census top-coding issue, does Reynolds have a point there?” My point, which he never mentions, is that the increase in (misnamed) “top-coding” in 1993 made it appear as if inequality had jumped to a higher plateau when all that happened is that the survey did a better job of recording higher incomes. I respect the Economic Policy Institute for properly reporting that “a change in survey methodology in 1993 led to a sharp rise in measured inequality,” and I naively expect others to be equally honest. It is for this reason, as Burkhauser explains, that “Burtless’ simple comparison of the difference in these two values overstates the trend in income inequality after 1989.” Burtless refers only to the “headline” Gini coefficient which he criticized and only for two years, 1989 and 2005.

Ben Bernanke

Thoma quotes Ben Bernanke saying “rising inequality … has been evident for at least three decades.” But Bernanke also presented data for only two years, 1979 and 2004. In the seriously flawed income data he mentioned, all of the increase in inequality (aside from the survey change in 1993) occurred between 1979 and 1985. The data Bernanke cited for the share of income received by households in the top and bottom fifths were not, as he claimed, “after taxes have been paid and government transfers have been received.” The figures he cited were not for disposable income, as he implied, but for “post-social insurance income” — which shows what income distribution would look like if there were no poverty programs and no taxes. His measure includes taxable capital gains but not the taxes on those gains or any other taxes, and it explicitly excludes all means-tested transfer payments such as the EITC, TANF, WIC, Medicaid, housing allowances and food stamps.

Bernanke began by mis-defining income inequality as differences in the wages of college grads and dropouts. Yet Burtless found that wage inequality explains “only about one-third of the increase [from 1967 to 1999] in income disparities.”[1]

Quoting such famous people appears to provide comfort to those unwilling to even look at my graphs. But a cozy consensus of “professional opinion” about bad data is no substitute for good data.

Paul Krugman

Thoma links to Paul Krugman’s discussion of a topic illustrated in my Figure 4 — the $1 trillion gap between the Piketty-Saez and Census Bureau estimates of the top 5 percent’s income share. The Census data, I wrote, say the income share “rose from 18% in 1986 to 20.9% in 2004, mostly because of a data break in 1993. The comparable Piketty-Saez figure jumped from 22.6% in 1986 to 27% in 1988 … [and] hit 31.2% by 2004.” Krugman claims the difference of 10.3 percentage points in 2004 is because Census supposedly misses extremely high incomes. Even if Census missed every dollar above $5 million (where the tax data shine), that would not come close to explaining the gap. If we “exclude all income above $5 million from the Piketty-Saez estimate of the top 5 percent’s share,” I calculated, that would narrow the gap by less than one percentage point.

Krugman concealed the huge gap and thereby trivialized the issue into a matter of differences in rates of change since 1994. He wrote that, “The Census data say that the income share of the top 5% rose only slightly, from 21.2% to 22.2%, between 1994 and 2005. The Piketty-Saez data, which only go up to 2004, show a 3.7% rise. Our little exercise with earnings data suggests that the missed income due to reporting limits rose by about 2 percentage points over the same period.”

The Piketty-Saez estimate of the top 5 percent’s share rose by 8.6 percentage points from 1986 to 2004. Figure 4 shows that half of that happened between 1986 and 1988, when the business portion of top 5% incomes from 8.8% in 1986 to 15.5%. Krugman’s Pareto interpolation seems a painfully elaborate ruse to avoid discussing (1) the trillion dollar gap between the two series, and (2) the fact that, as Burtless put it, “tax reform in 1986 certainly increased the amount of income that top income recipients directly reported on their 1040s.”


When Thoma comments on my Wall Street Journal piece with David Henderson, he changes the subject from corporate profits to interest income. He imagines we wrote that “since tax-deferred earnings are not reported, the distribution of interest income from these assets is imputed from reported interest on other assets and this skews the measured distribution of income toward inequality.” Amazingly, the words “corporate profits” appear nowhere in his convoluted analysis of something we never wrote, even though the misallocation of 59.4% of corporate profits to the top 1% was the focal point of our graph and article. The CBO added 39% of corporate profits to top 1% incomes in 1989 and 59% in 2004, thus fabricating a wholly artificial increase in the top 1 percent’s share.

“CBO may not do a perfect job,” says Burtless, “but at least it attempts to measure tax burdens and net incomes in an even-handed and consistent way.” Attempting something is not the same as achieving it. The CBO’s attempt to include tax-exempt interest before it began being reported in 1987, to include only the taxable portion of capital gains (outside of IRAs), and to allocate corporate profits by using an indefensible technique renders CBO data much worse than useless for estimating top centile shares of income over time.

Piketty and Saez

I plan to write a detailed comment on the Piketty and Saez reply to my December Wall Street Journal article elsewhere. For now, I will mainly focus on sections from their reply that others have mentioned.

Piketty and Saez did not suggest that I have misquoted them or that any of my statistics are wrong. If their reply to me is correct, then much of what they have written in the past (and I have quoted extensively) must have been wrong.

They now assert, for example, that there is an “emerging consensus” that the elasticity of taxable income (ETI) is just a transitory blip. On the contrary, the most recent (1999 to 2004) estimates for permanent ETI were 0.57 from Auten and Carroll, 0.40 from Gruber and Saez, and 0.53 from Kopczuk and 0.62 from Saez himself. Piketty and Saez claim that Goolsbee’s 2000 paper about executive pay (which double-counts stock options when granted and exercised) trumps Saez’s 2004 paper. Yet Eissa and Giertz report that, “for executives, we find a permanent earned income elasticity for the early 1990s of 0.8 (with no anticipation effect).”

By the time the Piketty and Saez reply reached The Wall Street Journal’s letter section on January 11, they had prudently omitted their previous comment that my “small point on 401(k)s is conceptually mistaken.” My Figure 3[pdf] shows it is not a small point http://www.cato.org/event.php?eventid=3441. The Reynolds-Henderson piece proves it is not mistaken.

Playing the tiresome two-year game, Piketty and Saez say “the share of income going to the top 1% families has doubled from 8% in 1980 to 16% in 2004.” But their data are for tax units, not families. Two married people earning $50,000 apiece report twice as much income per tax unit as an unmarried couple with the same income. Half of the 1980-2004 increase in top centile shares happened in just two years, 1986-87, and all of the apparent increase since 1986 is fully accounted for in the Cato paper and even in Figure 1 and Figure 2.

Although their data exclude taxes and transfers, Piketty and Saez boldly assert that, “the reduction in taxes at the top since 2001 has mechanically exacerbated the discrepancy in disposable income.” CBO estimates show the opposite of what Piketty and Saez assert.

Brad DeLong recently singled out the most substantive comment in the Piketty and Saez reply. They suggest that if many businesses had switched from filing under the corporate tax to the individual tax (a “scenario” documented by Saez), then we would have seen more business income in the top 1% but also smaller capital gains. So what?

My Figure 2[pdf] shows that the share of top incomes from capital gains did indeed fall dramatically in 1986-88 when the share from business soared, confirming the Piketty-Saez theory. But the dollars gained from business income were much larger than dollars lost from capital gains, so the net effect pushed the top income shares way up. The capital gains tax soared as the business share stopped rising after the individual income tax was increased in 1993, but cutting the capital gains tax in 1997 was a major reason. When tax rates were simultaneously reduced on business income, capital gains and dividends, the top 1 percent’s income from those sources climbed as the salary portion declined. Yet Piketty and Saez focus on the dwindling salary share. The only way to see what happened is to reveal all the data, rather than just two years. The Piketty-Saez time series on sources of top income shares reveal that their data is seriously distorted by taxpayer responses to changing tax rates.

Gary Burtless

Burtless and Thoma make a reasonable request for a fair and even-handed weighing of the defects of distribution studies based on samples of tax returns, the Consumer Expenditures Survey (CES), and Census Bureau’s Current Population Survey. I make the same request for my work on CBO and Piketty-Saez data, and for my figures on changes in median income by fractile from the Fed’s Survey of Consumer Finances in Figure 7.

I do not believe an even-handed approach would have been possible before the publication of Income and Wealth. Until then, scarcely anyone had seriously questioned income distribution estimates that were based on tax returns. I have now presented considerable evidence that taxpayers change what they report as income, and how they report it, in response to changes in absolute income tax rates (elasticity) and relative tax rates (income shifting). To dismiss all that evidence as “inconsequential,” as Thoma does, is neither reasonable nor persuasive.

Unlike taxpayer behavior, the topic of consumption inequality has never been a major focus of my work; it takes up only 3 of the 231 pages in my book (pp.162-64). I have written hundreds of articles since 1972 about income, or about wealth. But I recall writing only one that used the CES. I have mainly left this important topic to experts, such as Krueger and Perri.

Burtless corrects my careless memory lapse, when I wrongly suggested that Johnston, Torrey and Smeeding did not rely on the Consumer Expenditure Survey. He finds it a sign of unfair bias on my part that I failed to mention that, in his words, “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%.” I didn’t mention those figures because I find them misleading.

A team of five BLS economists recently found that when comparing comparable categories of items, “that CE aggregate expenditures are 86 percent of PCE aggregate expenditures for 1992, drop to 85 percent in 1997, and fall further to 81 percent in 2002.”[2] To push that 81% down to about 60%, as Burtless does, requires comparing categories that are not at all comparable.

The CES asks what consumers spend. PCE also includes what governments and nonprofit organizations spend on products and services used by consumers. The main reason the gap has widened between PCE and CES is Medicare and Medicaid, plus other third party expenditures on education, social welfare, religion, research and war. In 1997, the CES was only 17% as large as the PCE for medical care – a $724 billion gap. The CES was only 51% as large as the PCE for education and research, only 27% as large for legal services, and only 13% as large for Social Welfare. Unlike PCE, the CES does not include clothing and food for the troops in Iraq, or research grants and scholarships, or purchases of food and clothing by churches and the Salvation Army. The fact that only the NIPA’s PCE series includes such rapidly-expanding spending by governments and nonprofits is not evidence the CES suffers from declining quality.

Another Red Herring

Citing a newspaper article, Thoma opines that treating R&D expenses as an investment would “dwarf the kinds of adjustments Reynolds discusses.” The article claims that “when R&D is counted as profit, the employee compensation share of national income drops by more than one percentage point,” and says this would somehow shrink labor’s share from 65% in the sixties (no R&D back then?) to “less than 60 percent today.” But investment is not profit and one percentage point is not five. Labor’s share of national income (aside from self-employment) was 62.5% from 1960 to 1960 and 65.5% from 2001 to 2005.[3] Besides, changes in NIPA bookkeeping conventions have no effect on anyone’s income.

What does this swelling sea of red herrings have to do with my simple request for some credible evidence — meaning, not based on tax returns — that shows rising inequality from 1988 to 2000 and/or from 2000 to date?

Anyone seriously interested in the level or change in relative living standards must look at either consumption or a mix of disposable income for the whole population, — not just for 1 percent or for a few dozen CEOs in the study Burtless cites, and not for just for two years separated by such major breaks as the 1986 tax reform and the 1993 change in top-coding.

Nobody has yet found fault in the evidence I presented showing no significant and sustained change in the inequality of disposable income or consumption since 1988. If we can get past attempts to change the subject, perhaps we might begin to examine the facts.


[1] Gary Burtless, “Has Widening Inequality Promoted or Retarded U.S. Growth,” Canadian Public Policy, Vol XXIX, 2003, p. S189.

[2] Thesia I. Garner, et. al., “The CE and the PCE: a comparison,” Monthly Labor Review, September 2006.

[3] Alan Reynolds, “Statistical Politics Update.” The Washington Times, October 22, 2006. (Webbed here.)

Also from this issue

Lead Essay

  • A headline in today’s Wall Street Journal reads “Fed Chief Warns of Widening Inequality.” Bernanke worries that inequality erodes tolerance of the “dynamism” that lays the golden eggs of “economic progress.” But is inequality widening at all? Cato Institute senior fellow Alan Reynolds has his doubts. Following up his own controversial Wall Street Journal op-ed, a Cato Institute policy forum, and a new Cato policy paper, Reynolds in this month’s lead essay digs yet deeper into the mysteries of the official numbers and comes up with … not much: “If there were any [good] data showing a significant and sustained increase in the inequality of disposable income, consumption, wages, or wealth since 1988,” Reynolds concludes, “I suspect someone would have shared it with us by now.”

Response Essays

  • Gary Burtless agrees that analysts of the American income distribution should “take seriously some of Reynolds’s criticisms of the data on income disparities.” “Reynolds points to some serious problems,” Burtless concedes, “and in many cases fair-minded experts will agree with him.” Nevertheless, Burtless dissents sharply from Reynolds’s larger claim that inequality apparently stopped increasing in the late 1980s. “Income inequality was higher at the end of the 1980s than it was in the beginning of that decade,” he states, “and it was higher in 2005 than it was in 1989.” According to Burtless, Reynolds can reach his unorthodox conclusion only by manipulating the evidence. “The problem is,” Burtless charges, “he is harshly 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.”

  • In his response to Alan Reynolds, Mark Thoma invites us to “step back” and survey the wider picture of data and expert opinion on income inequality. The verdict? Fed Chairman Ben Bernanke, and the consensus generally, has got this one right. “The preponderance of evidence and of professional opinion,” writes Thoma, “clearly indicates that inequality has been rising since [at least] 1988.” Like Burtless, Thoma finds little in Reynolds’ analysis to agree with, describing his main points as “either too inconsequential to change the inequality picture,” suffering from “an incomplete presentation of the evidence, or rebutted by other work.” Thoma then goes a step further, pointing to new evidence suggesting that income inequality might be even greater than currently estimated.

  • Invoking Kurosawa and Derrida, Richard Burkhauser dives into the contested complexities of the Current Population Survey data on household income. His conclusion: “Over the 1990s business cycle the entire distribution moved to the right with little or no change in income inequality. Since 1989 household income inequality has risen very little and much less than in the previous decade. This is very good news that matters.” Burkhauser admits that the CPS data are not well suited to tracking trends for the top 1 percent of earners. “But does this really matter?” he asks. “Our economy is not a zero sum game. My gain does not mean your loss or vice-versa. I know of no evidence that increases in the incomes of the top 1 percent of our population are the root cause of the challenges faced by those at the other end of the distribution.”

  • Dirk Krueger and Fabrizio Perri suggest that we shift our attention away from inequality in current incomes. “[I]f one is ultimately interested in the distribution of well-being across U.S. households,” they write, “the object of study ought to be the joint distribution of lifetime consumption and leisure across them.” Unfortunately, good data on lifetime consumption are not available. However, citing Milton Friedman and Franco Modigliani, Krueger and Perri contend that “if households can borrow and lend on financial markets, then there is a strong link between the lifetime resources of a household (sometimes also called its permanent income) and its current consumption.” And the trends in current consumption data show that “the increase in income inequality in the U.S. has been much more pronounced than the corresponding increase in consumption inequality.”