This post is on the Gini ratio and how it changes over time and across presidencies. I had an earlier aborted look at the Gini ratio, but I’m trying again here.
Let me start by simply copying some verbage from that earlier post:
This post is going to look like a post on income inequality by presidential administration. It even has a nice picture showing data going back to 1953. I’ll start by describing what I did, and then explain why its not a post on income inequality.
I was hoping data on the distribution of income per person. The IRS has data on idnvidual income, but it has several problems, not the least of which it doesn’t go back before 1987. (That’s OK, but not if other data is available.) The Census unfortunately only computes median and mean income for individuals. If you want to know how the income was distributed (e.g., bottom 20% get X, top 20% get Y, etc.) you have to make do with data on families or households.
So I decided OK, let’s go with families. See what it looks like. Well… the Census also goes ahead and computes the Gini ratio for families in time series form. Basically… the closer to 0, the more equality, the closer to 1, the more inequality. (More information on Gini here.)
Anyway, last time I got to this point, I noted the big structural break at the start of the Clinton admin and threw up my hands. This time, I decided… heck, let’s deal with it. If you look at the graph, there are several other points at which it really seems like something changed in the data. I went back and checked each of these, and read the footnotes on the table… I noted that on three occasions, there was what appeared to be a discontinuity in the graph that occurred on a year in which the Census made a big change in how it computed the data…
a. In 1961, they used a new procedure to impute missing data
b. In 1967, they came up with a new processing system
c. In 1993, they started using a computer-assisted interview process
I assume the primary effect of these changes was to produce a one time jump in the series. Therefore, to summarize results by President, for JFK/LBJ I am going to look only at the period from 1961 to 1966, and for Clinton, instead of looking at the change from 1992 to 2000, I will look at the change from 1993 to 2000. (Note… the full term results appear at the bottom of the table regardless. Note also that this is the same approach I used to deal with a discontinuity at the start of the Reagan administration on the post about children living in 2 parent households.)
So what does the summary tell us? The biggest movements toward equality occurred during the LBJ/JFK, Ike, and Clinton administrations. GHW and Reagan bring up the rear. GW and Nixon/Ford do better than Carter. I don’t think any part of these results are surprising.
Now, with the exception of Ike, I don’t think any Republicans ever talked about equality of opportunity or making sure everyone got a fair shake. So should this matter to Republicans? And where does greater equality or inequality come from? Was JFK right? Does a rising tide (generally) lift all boats? Granted, JFK/LBJ and Clinton had the fastest growing economies in our sample, but Reagan came in third… Ike was second last and GHW last. So let’s see what the data says about the relationship between changes in real person median income and changes in the Gini ratio…
(I probably should have used family median income for consistency, but I had personal data lying around.) There’s a very small negative correlation between changes in the Gini ratio and changes in the median real income. I doubt it would be significant if I were to run a rigorous test. Similarly, changes in real income don’t seem to be associated with changes in income inequality. But… changes in the previous year’s median income have a –0.26 correlation with this year’s Gini ratio. This may also not be significant… but it is at least suggestive that the faster real median income rises, the greater the tendency toward equality in the distribution of income. Not a huge effect, but it may well be there.
Some time soon… a look at poverty.