Here's the particular passage we have in mind as we ask that question:
A more blunt version of this technique was previewed a couple months ago by the American Enterprise Institute’s James Pethokoukis, perhaps the right’s most enthusiastic inequality denier. Pethokoukis cited a chart, compiled by Political Calculations, purporting to show that the only change in inequality results from changed family status. Pethokoukis triumphantly presented this as the “The one chart that explodes the myth of U.S. income inequality,” and used it to segue, as Brooks does today, to Murray’s arguments about family values:
So what we have here, as always in America it seems, is culture trumping economics (though the data don’t take into account how different income groups have different inflation rates, another equalizer). AEI’s Charles Murray has a new book coming out that will expand on how values and culture influence inequality.
But the chart is completely wrong. Reader Jacques Distler pointed out to me that it relies on census data, which only asks households if they earn more than $100,000 a year. Since all the change in income inequality has come within households earning well over that mark, the census data is not going to capture the rise in income inequality. (Think of it this way. Imagine you want to show that basketball centers get taller as you move from high school to college to the NBA. If your tallest category is "six foot two and over,” you’re not going to show much of an effect.)
I e-mailed Lane Kenworthy, an inequality expert, who confirmed this for me. Inequality between the top one percent and everybody else has increased dramatically.
You know, it occurs to us that there are at least three individuals or entities who could have been contacted, but who weren't consulted at all before the assembling of these paragraphs:
Because, if we had been contacted, we could have easily confirmed that while the Current Population Survey that is used to collect income data is indeed sent to households, it collects data for persons and families, in addition to households! It also doesn't limit those who are sent surveys to placing themselves into a "$100,000 or more" category. The individuals who participate in the survey report the amount of their income from all sources.
One important thing to note about the U.S. Census Bureau's reports is that the agency does indeed "top code" its reported income range categories, grouping the people at the very top end of the income spectrum into one income range in its reports. It does this largely for the sake of preserving the confidentiality of those in that topmost range. Otherwise, given how few people there are at those levels, it would be very easy to identify who is who based upon the information they might provide to the Census through the income survey.
And what's more, although the Census reports the Gini Coefficient, a very common and widely accepted measure of income inequality, in a standard table that groups top-end income earners into the category "100,000 and over", its calculation of the Gini Coefficient it reports for persons, families and households uses all the data it collects for persons, families and households respectively.
Better yet, the Census publishes another income distribution table for persons that goes all the way up to the topmost category of "$250,000 or more", breaking it down for both Men and Women (and by race too, if you're really into that sort of thing). In fact, we're very familiar with this data because we used the data for women for a more fun project.
That's significant because individuals with incomes of $250,000 or larger represent the "Top 0.6%" in 2010, so even the data the Census reports extends well up into the territory of the "Top 1%". That means we can indeed use the Census' data to make assessments of how income inequality for individuals is changing over time, because these are the people whom Jonathan Chait feels is most important for making such a determination!
Not that we need to go to that trouble anyway - if you want to see increasing income inequality, you can see it at the bottom of the income spectrum as well.
It seems then that relying upon "Reader Jacques Distler" for a technical assessment of the Census' data collection processes, analysis and reporting procedures isn't looking like too sharp a move on Jonathan Chait's part - he clearly didn't know any of this stuff. Perhaps if Chait had thought to actually direct questions to people who actually work with the data he could have found that out sooner, but he just wasn't curious enough! What a strange trait in a "journalist"!
As for Lane Kenworthy, inequality expert, it seems that Chait wasn't curious enough to ask him about the Census' actual data collection, handling and reporting practices, choosing instead to get some confirmation of what would the results be "if" data were collected and handled in the way he describes.
At this writing, we see that Chait's article on the New York Magazine web site has attracted some 70 comments since it was posted at 3:11 PM (Eastern Standard Time). We first became aware of it when one visitor, some four hours later, was curious enough to follow the link Chait provided to our site.
In the last three hours before we posted this article, no one appears to have been curious enough to click through to our site from the link provided Chait's article (could that be a shared characteristic of both Chait and his readers?) We would almost bet at this point that this post will drive more traffic to Chait's article than vice-versa!
You know, it occurs to us that we could have alternatively titled this post "The Incredibly Lazy Journalism of Jonathan Chait" and have still been right on the money.