A couple weeks ago I made the point that it is strange to look at changes in income inequality and make calls for redistribution. First, its not clear that changes in inequality should matter for someone that cares about social justice. Even if changes in inequality rather than just the existence of it mattered for some reason, I made the argument that tracking changes in the differences between income percentiles confuses the subject.
Income levels vary drastically over a family’s lifetime ((BTW, the statistics on incomes are usually measured by the household or the family. This can be confusing if you try to compare these statistics to your own paycheck… something to keep in mind.)). Young families are smaller (maybe one or two people), the income earners are less experienced and therefore less skilled and often a big chunk of the family’s time is spent building human capital (an economist’s phrase for what normal people call “going to school”). All of these factors mean that younger families have less income.
As the family’s income earners get older they have more and more experience and they spend most of their time in the work force. Also, more people are married at this stage in their lives and most couples have children so family size is much larger. The family’s income go up, but they don’t consume all that extra income; they build their nest egg instead.
Later in life, the kids leave home and the income earners start retiring from the work force. The family shrinks and its income shrinks. It lives off its savings instead.
This is why income data show an inverted U shape over lifetimes. Young and old families have low incomes and middle aged families have high incomes. Also, this life-cycle story tells us where to look for explanations of changing inequality. Inequality could be increasing as a result of demographic changes (more middle aged families relative to young and old). I suspect the ageing of the baby boomers plays an important part in the story.
But the demographic story doesn’t explain this picture:
If demographics were the main driver of inequality, the inverted U wouldn’t be getting more dramatic over time.
Increasing inequality also could be a result of changes in the way the economy rewards different kinds of human capital. There were two types of human capital in the above story: the kind that you get at school and the kind you get with experience on the job. First, if skills learned in college ((Or if college let you demonstrate you have certain skills. I’ve suggested before that college is more about signaling quality rather than actually building quality.)) are more and more important for today’s jobs then people will have the incentives to get more education. Young people spending more time in college lowers their incomes and exasperates income inequality.
Second, if on the job knowledge is more important these days, then experienced folks will be paid more. By definition only older workers can be more experienced so this can be driving what we see in the above diagram.
The point of this post’s title, though, is that its not incomes that families care about for the most part. Its consumption. You can’t eat, drive or live in your paycheck. Consumption, as it turns out, varies much less over the life-cycle than income ((It varies about 10%, relative to about 50% variation in incomes, and is hump shaped like income (Gourinchas and Parker). This is an unsolved mystery in economics because standard theory says it shouldn’t vary at all.)) and this NYT opinion piece by two Fed economist argues consumption, surprisingly, doesn’t vary much between rich and poor.
UPDATE: Mark Thoma has more on consumption vs. income inequality. That post, Krugman’s reply to Cox and Alm and the general discussion is so damned muddied. People slip so easily between a descriptive “this is how it is” discussion to a normative “this is how it ought to be” discussion. For example, the Fed piece Thoma excerpts starts off by talking about the best measure of the poverty line (income or consumption) and then quickly gets side-tracked into a discussion of which measures are easiest to construct. Thoma himself uses the Fed’s measurement discussion as a spring board for a short discussion about what he thinks poverty really is (short Thoma, “its not about material stuff, except it is”). What that has to do with data issues, I don’t know. He then jumps from his quick and dirty definition of poverty to a sermon on the “decent and right” thing to do.
Often times, popular discussions of this topic have an air of back filling and data mining. People have some policy they want to implement and then they go squeeze data until it supports their policy. Call me naive, but I think policy should be guided by the science not the other way around.
One of the reasons I’m so attracted to this topic, though, is this level of muddiness. I’d like to think there would be some premium in it for the guy that can try to make sense out of it all. Economic inequality is an extremely complex topic. I believe we need to take a deep breath and try to understand the issue as level headed as possible. This means we need to measure it, understand inequality’s stylized facts and have clean theories that can be explicitly tested.