It appears from Mark Thoma’s last posting that he is inching his way into the consensus of Reynolds, Burtless, and Burkhauser, which says that it is hard to find much of an increase in household size adjusted income among the bottom 98 or 99 percent of the United States population since the 1980s using standard Gini measures and consistently top coded data from both the public use and internal restricted access Current Population Survey. And, though he doesn’t say so, it also appears he is inching his way toward the view that the gains from economic growth were more equally distributed over the last major business cycle (1989-2000) than the previous one (1979-1989) within this population.
Thoma has posted some very valuable references to the more technical economics literature, which uses alternative measures of income inequality and struggles to extract the most information about the entire distribution from imperfect data by making certain assumptions about the shape of the entire distribution given limited data at the top. He especially notes the problem that outliers at the top of the distribution cause in such efforts. Hence it appears he now recognizes that you sometimes need to be a weatherman (or at least need to carefully listen to several of them) to know which way the wind is blowing.
But instead of then agreeing that the literature on how exactly to capture this very high end of the distribution (the top 1 or 2 percent) is still developing — as is the literature on how exactly to use such measures to tell us about what has happened to income in this very high income population over the last thirty years — he concludes with a most amazing non-sequitur: “When researchers go through these exercises carefully and weigh the evidence objectively they conclude, with few exceptions, that inequality has been rising in recent years.”
A careful reading of the most recent article Thoma provides us makes no such claim:
“Robust stochastic dominance: A semi-parametric approach,” by Frank A. Cowell & Maria-Pia Victoria-Feser, Journal of Economic Inequality, April 2007. Rather, the article is a cautionary tale of the difficulties of making such judgments, and the sensitivity of such finding to outliers at the top of the distribution. While the paper uses British data, similar problems are likely to be found using the CPS and, I suspect, the other data sets we have discussed over the course of our conversation. That is why much of the income inequality literature using the CPS has used “trimming” or consistent top coding to avoid the problem of outliers and instead talks about the bottom 98-99 percent of the income distribution. Pinning down what has happened to the top 1 or 2 percent of the income distribution is the hard work that remains to be done before we can state definitively what has been happening there and how it impacts overall income distribution.