where orders emerge
There is now a widely held view that the last 10 or 20 or even 40 years have been a time of great stagnation for the average American. Yes, the overall economy has grown, but all or most or nearly all of the gains have gone to the top 1% or top 10% or top 20%.
These claims are accompanied by various data that seem to confirm the claim.
These claims conflict with casual evidence available to people over a certain age who remember the 1970′s or 1980s. We are an immensely more prosperous nation than we were back then. Our cars are nicer. Our homes are bigger. Our toys are more clever. And more people have more of them. Some things are more expensive but that is because more people have access to those things–such as health and education–they are labor intensive and we’ve driven up their price. But these kind of claims are not totally convincing, nor should they be. The fact that the world looks dramatically more prosperous may be due to cloudy vision, or bias. But they do cause you to wonder if the data that are being used to measure stagnation are not completely accurate or perhaps the data are distorted by the way they’re collected.
Don and I have both written about these issues and the data problems with the claims many times.
One source of data that people often use is median household income. It’s a good idea to use the median rather than the mean–the mean can be very misleading. For example, the mean income of Harvard graduates who studied economics is going to be very high in the year that Jeremy Lin graduated. John Elway, another econ grad, pulled up the mean dramatically for Stanford grads that year.
But there is a problem with median household income and those who use it relentlessly to grind their policy axes never mention it. The problem is that when household structure is unstable, comparing medians over time is a very poor way of assessing the progress of the typical person.
As I have written many times, rising divorce rates in the 1970′s for example, meant that the number of households in the US grew 26.7%. Population grew only 11.5%. There was an increase in the number of households as one household became two. If both people were working, that alone would likely decrease median household income. If only one of the spouses was working, it was usually the man. The former wife found herself in the labor force unexpectedly. Her income is likely to be below the median. Both of these effects create new households with incomes below the median, dragging down the median over time.
It also lowered the home ownership rate. Politicians interpreted this fall as a problem with the housing market. It had nothing to do with the housing market. It had to do with a change in the marriage market.
So I have written about this many times. I’ve never thought about the fact that an increase in the divorce rate isn’t the same for every demographic group. Here is Charles Murray’s measure of the difference between rich and poor in the divorce rate in Coming Apart (as reported by Bryan Caplan):
The Fishtown folk at the top of the graph have never attended college. The Belmont people at the bottom have at least a bachelor’s degree. On average, the Fishtown folk are poor. The Belmont folk are much richer.
If the poorest people have the highest divorce rates, the increase in households in the 1980′s and beyond are going to come from the poorest people, adding numbers of households below the median and pulling the measured median down as a pure statistical artifact. That fall in median household income tells you nothing about the health of the economic system. It’s telling you something about the health of American marriages. (The increase in college attendance over this time period softens the magnitude of the impact, btw. But it doesn’t change it.)
You can’t conclude then, that “people are getting worse off.” Or “the average person has had no gains.”
The average (or more accurately, the median) person in 2011 is not the same person who was the median 10 and 20 and 30 and 40 years ago. To figure out how people are doing over time, you have to follow the same people over time. When you do that, people are getting richer across the income distribution (though the picture for blacks is mixed) and the biggest gains go to the poor (true of both whites and blacks).
And in all of these comparisons, the data on income are corrected for inflation using very imperfect price indices.
Though I think the consensus on these issues is wrong, we will be very lucky if all it leads to is higher taxes on the rich. I don’t think those have very much effect. The more worrisome change would be policies that follow from the view that the data on income distribution show that capitalism doesn’t work very well for the average person and that more radical change is needed. In fact, it is cronyism that doesn’t work well for the average person–the rewarding of special privileges to the politically powerful doesn’t do much for the average.
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