Justin Wolfers writes:
Predictably enough, I spent yesterday reading lefty blogs trumpeting Corak’s analysis, and right-leaning blogs who didn’t want to believe the inequality-mobility link, endorsing Winship. But both missed the bigger picture implications. Either you’re convinced by Corak that the data can be trusted, and that they show there’s a strong link between actual inequality and actual mobility. Or you believe Winship that the data are a pretty poor proxy for what’s really happening, and so there’s actually a very strong link that’s being disguised by imperfect data.
Here is Scott’s latest response, with links to various critics.
As for my take, Justin is painting himself into a corner here of his own making. Let’s step back for a moment. I see two big and very real problems: slow income growth for many income classes and a problem with excessively high returns to finance at the very top. (As an aside, both of these problems contain elements of both “left-wing concerns” and “right-wing concerns,” and both problems are deeper than any particular ideology can solve and they should make virtually everyone rethink their views).
Those are the problems and we should try to fix them.
If we could fix these problems, that would mean a smaller financial sector, less moral hazard, better allocation of capital, and for most/all income classes rates of income growth comparable to the 1948-1972 period, chop it up as you wish. Imagine that everyone’s income went up three percent a year, every year, and every generation was about twice as rich as the parents. Whether there then would be more or less marginal “churn” in the relative income rankings is not a matter of irrelevance but having somewhat more churn should not be viewed as a major social goal per se. It would depend on the reason for the immobility, and the real focus of our concern would be the reason (e.g., bad schools? some kind of unfairness?), and not the marginal change in the numerical churn per se.
Given that background, and those two very real problems, you can in fact create other “problems” by creating and manipulating more complicated statistics, based on the initial problems, and that can lead you to various measures of inequality and immobility. But not all inequalities are bad, or avoidable, and the same is true for immobilities. The valid problems, as embedded in the new complicated measures, still will boil down to the two simpler problems mentioned above. In the meantime, toying around with misleading and less transparent aggregate measures of inequality and immobility will bring confusion as to what is really at stake.
Focus on the two very real and fairly simple (as distinct from simple to fix) problems.
Addendum: If you are looking for Turing test fail, mood affiliation, unwillingness to recognize comparisons on the margin (as if I am defending hereditary aristocracy), and us vs. them thinking, here are John Quiggin, Brad DeLong, and Paul Krugman, as if I had staged a satirical interchange to illustrate and make fun of their occasional proclivities. The commentary of Matt Yglesias, also on the left, does not commit any of these fallacies and in fact deftly sidesteps them; perhaps they should drink from his water, or from that of his father, who apparently did not finish high school.