First, apologies to Arnold, I missed his post when traveling and so he does discuss natural experiments, contrary to my previous claim about EconLog bloggers. That said, I’m not so happy with his analysis. He’s taking a few of the papers he sees as the weakest and he explains why they are weak. I would rather he dissects the strongest pieces and compares them to the strongest pieces, using natural experiments, showing very low rates of return to education. The Joshua Angrist papers (often with Alan Krueger) for instance are quite sophisticated and do not run afoul of Arnold’s objections. In works such as this (later versions seem to be gated), Angrist and Krueger perform exactly the natural experiment which Arnold requests and they find high (marginal) returns to education. Or see this piece by Card.
Here is Bryan’s response to my post. Focus on his #2, which is the crux of the matter:. He cites the signaling motives for education and concludes: “Here, the evidence Tyler cites is simply irrelevant.” This is simply not true and indeed these papers are obsessed with distinguishing learning effects from preexisting human capital differences. That is what these papers are, so to speak. In that context, “ability bias” in the estimates doesn’t seem to be very large, see for instance the Angrist or Card pieces linked to above. This paper surveys some of the “adjusting for ability bias” literature; it is considered quite “pessimistic” (allows for a good deal of signaling, in Caplan’s terminology) and still it finds a positive five percent a year real productivity gain from an extra year of schooling.
What’s striking about the work surveyed by Card is how many different methods are used and how consistent their results are. You can knock down any one of them (“are identical twins really identical?, etc.), but at the end of the day which are the pieces — using natural or field experiments — standing on the other side of the scale? The Card results are also consistent with theory, namely that models which emphasize signaling imply large unrealized gains from trade; it’s not that hard for an employer to administer an implicit IQ test as Google and Microsoft do all the time. As a separate (and here undocumented) point, I would argue the Angrist and Card results are consistent with the bulk of results from sociological and anthropological investigations.
There really does seem to be a professional consensus. Maybe it’s wrong, and/or dominated by biased pro-education specialists, but I’m not seeing very strong arguments against it. For the time being at least, I don’t see that there is much anywhere else to go with one’s beliefs. If Arnold or Bryan (or David) suggests a good paper with a natural experiment showing a low marginal ROR for education, I am happy to read the paper and report back and compare it to the preponderance of evidence on the other side.
The real puzzle is how large measured marginal returns to education are consistent with the continuing observed failures of the American educational system. Why does the low-hanging fruit persist or is it low-hanging at all? The traditional liberal view is that further educational subsidies are needed, but a possible alternative is that some people simply do not wish to step across to the other side of the divide to a “better life,” at least as defined by middle class values and income statistics. Or is there some other hypothesis? Whichever way you cut it, a big improvement in this area does not seem about to happen and arguably we are moving in the opposite direction. Whatever gains are there “in the data,” we don’t seem able or willing to capture them.