Guest post by Scott Winship, Brookings Institution. Follow him on Twitter: @swinshi

My last post provided an initial look at the inequality figures focusing on "the top one percent," which show sharply rising income concentration over the past 30 years.  But those figures rely entirely or heavily on tax return data from the IRS.  This creates some issues that warrant skepticism about the magnitude of the increase I described.

Piketty and Saez rank order and compare tax returns to isolate "the top one percent."  But that is not the same thing as rank-ordering and comparing householdsPiketty and Saez themselves note that even after a small adjustment to add in non-filers, there are 30 percent more tax returns than there are households, and average tax-return income is 25 percent smaller than average household income.  Research by the Federal Reserve Board looking at tax returns in 2000 estimated that the number of tax returns filed exceeded the number of tax returns filed by household heads and their partners by 25 percent. 

There are two reasons for the discrepancy.  First, unmarried couples (and many married couples) file separate tax returns, as do teens with summer jobs and college kids on work-study. You can see why this might be a problem: the "top 1 percent" of tax returns ends up being a bigger group than the top 1 percent of households because the bottom "99 percent" is padded with these extra people.  That's fine as far as it goes, and if the ratio of tax returns to households hasn't risen appreciably, then the trend might be the same for households even if the share of income received by the top one percent of households is overstated by the share received by the top one percent of tax returns.

The other reason that average tax-return income is smaller than average household income is that the IRS data excludes income from nontaxable sources, the most important of which include nontaxable amounts of government benefits and of pensions and employer-provided health insurance. Including these sources of income would tend to lower the share of income going to the top, and it might reduce the increase too.

CBO's figures are theoretically based on households, and they include all public benefits and employer-provided health coverage as income.  But in some sense, the CBO figures are even trickier to interpret than the Piketty/Saez figures.  That's because CBO analysts start with households in the Current Population Survey data, attempt to disaggregate households and their incomes to tax-return-like units, and append actual IRS tax return data from similar-looking tax-return-like units to the disaggregated household data.  They then aggregate the incomes back into households and combine income from the tax return data with income from the household survey.  Finally, they rank people (not households or tax returns) on the basis of incomes adjusted to account for household size differences, but report household incomes and shares going to the top and going to other groups in non-adjusted dollars.

All of this is much less straightforward than going to a household survey and just ordering households by household income to see what you get. The problem is that nearly all household surveys are incapable of giving reliable information about the top 1 percent, simply because in order to sweep up members of, say, the top one percent of the top one percent in a survey, you have to go to great lengths--either interviewing a massive number of people or developing a distinct strategy for finding and interviewing the richest of the rich. Even when massive surveys are available--the census that is taken once every ten years, for instance--because of privacy concerns, the incomes of the very rich are camouflaged. Only one survey has taken the second approach of strategically focusing on the rich separately in collecting income data: the Survey of Consumer Finances (SCF). The best one can do with other household surveys is to make some assumption about how the camouflaged incomes at the top are really distributed and to assign those households new incomes.

I recently analyzed the 1982 and 2006 income data from the SCF, which are the earliest and latest years for which comparable estimates are available. All of the figures in this paragraph compare incomes before taxes that include realized capital gains. The share of the top one percent in the SCF rose from 11 to 21 percent from 1982 to 2006, which is startlingly close to the Piketty/Saez figures (11 to 23 percent) and the CBO pre-tax figures (10 to 19 percent).  That is despite the fact that the income levels in the data sets differ notably. In the SCF, the entry point to the top one percent was $317,500 in 1982 (expressed in terms of what that income would have purchased in 2010).  It rose to $698,700 by 2006 -- an increase of 120 percent. In the Piketty and Saez data those numbers are $206,600 and $407,100 -- significantly lower, as expected, but the 97 percent increase is similar to that in the SCF. In the CBO data, the entry point to the top one percent is defined in terms of size-adjusted income, so we can't compare it to the others.  But the increase in the size-adjusted threshold was 113 percent. Even the percent of real income gains that accrued to the top one percent from 1982 to 2006 is similar across the data sets: 45 percent in the SCF, 53 percent in Piketty/Saez, and 39 percent in the CBO data.

In short, despite the shortcomings of the IRS-based top-one-percent measures in terms of units of analysis and income definitions, the basic conclusions about the rise in inequality hold up awfully well using the very different -- and in some ways preferable -- SCF. So why can't I learn to stop worrying and love the top one percent inequality estimates? One last post on trends in high-end inequality, and then I'll turn to low-end inequality.