The graph shows that, if measured by inches, the top 1 percent of earners gained 884 feet, or $628,817 dollars in income, while the bottom 90 percent gained one inch, or $59 dollars from 1966 to 2011. From the article:
“In 2011 the average AGI of the vast majority fell to $30,437 per taxpayer, its lowest level since 1966 when measured in 2011 dollars. The vast majority averaged a mere $59 more in 2011 than in 1966. For the top 10 percent, by the same measures, average income rose by $116,071 to $254,864, an increase of 84 percent over 1966.” He goes on to essentially blame the taxA tax is a mandatory payment or charge collected by local, state, and national governments from individuals or businesses to cover the costs of general government services, goods, and activities. system for this inequality.
Analyses like these are fascinating, but they do not tell you much and can be very misleading. However, people still jump to conclusions about them without much thought. There are a number of issues that people need to keep in mind when looking at average incomes, especially that aggregates tell you very little about the well-being of individuals. These issues have nothing to do with the tax system, but have everything to do with data.
Take this example: A mother has two children and wants to measure their height this year. The average of the two children is 40 inches. Next year, she measures again and those children grow, so the average grows to 42 inches. The third year, the lucky family has a third child. The mother measures the height again, but lo and behold the average now shrinks to 35 inches. “Oh no, my children are shrinking!” But we all know this isn’t the case. She just had a third child with a lower height; the other two children did not shrink.
A silly example, but this has to be considered when looking at “average incomes” for income quintiles. The composition of your quintiles matters a lot and a change in that composition over time can play tricks on you. Demographic and economic changes such as millions of low-skilled immigrants entering America slow the rate of income growth of the bottom quintile, creating the same new-child illusion in your data. And as with the new child, there is no reason to think the immigrant will be forever stuck in the bottom quintile.
Other factors that tend to exaggerate growth in income inequality include:
1) The entrance of women into the workforce.
2) The aging of the baby boomers.
3) The income measure comes from the IRS, and does not include fringe benefits such as healthcare, which go disproportionately to low-income households and have grown substantially since 1966.
4) Nor does the income measure include government transfer payments, which also go disproportionately to low-income households and have grown substantially since 1966.
5) It ignores the changing size and structure of households, including increased cohabitation rather than marriage and increased dual-income marriages.
The lesson here is to be wary of these analyses; they are often misleading and far too simplistic. Aggregates are useful, but they can be misused.
Follow William McBride on Twitter @EconoWillShare