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Should you go to an Ivy League School, Part II

One of the topics I’ve covered here is the all-important issue of whether your choice in College matters in terms of your future earnings. To recap: the best research in the field until a few days ago suggested that the returns to going to a more selective College were quite large; a result which was somehow interpreted by many to suggest the exact opposite claim.

The original result that kicked this off a working paper by Dale and Krueger. They realized that simply comparing students who went to top schools with students who didn’t generates an obvious source of bias: students who go to highly ranked schools tend to earn more than others, but this may be due either to the impact of the school or the personal characteristics that got them in to begin with. To correct for this, the authors compared students who got into top schools, and chose to go; with students who got into those same schools, but decided to matriculate elsewhere. This is also not a perfect comparison, but manages to correct tremendously for this form of bias.

Their results suggested that something about the school was important. In the jargon, they ran a regression of future self-reported income against the identity of all 30 schools in their sample, and found that going to one school instead of another impacted your future income. Then they looked at the particular factors which might explain that, and found that what mattered was the tuition the school charged as well as its level of admissions selectivity as reported by Barron’s; but not the average SAT of the school.

Their publication paper performed virtually the same calculations. They found that the choice of school mattered; the tuition charged mattered; and that the average SAT of the school did not. Bizarrely, they claim that the results of the test for Barron’s selectivity was now no longer important, but they did not report any estimates from that specification (I’m not quite sure how that result could have changed, since the authors did not make any sample or specification changes between the two papers). In any case, even if the Barron’s selectivity measure doesn’t matter, it was clear that something about the choice of school matters, and that tuition charged is a good proxy for figuring out what that something is. In fact, their results suggest that every extra dollar of tuition provides something like a 13-15% internal real rate of return (down from a nominal 20-30% in the working paper). As is covered elsewhere, the results for SAT were highlighted, while the results for tuition were less discussed — even by the authors of the original paper.

Dale and Krueger are back with a new paper, which looks at another age group and also gets income data from government as opposed to self-reported income. Given that the correlation between self-reported income and actual income is .90, you might expect the results to be quite similar. Certainly, this is what David Leonhardt suggests in his writeup. In fact, the results are rather different. The authors now claim that neither the average SAT of the school, the tuition it charges, nor its selectivity influence future income. I have a few quibbles with this paper:

1) Unlike prior versions of their study, in this paper Kruger and Dale don’t run a specification testing whether Colleges matter at all, as opposed to the particular variables of SAT, Selectivity, or tuition. So even if the authors are correct in suggesting that, with the availability of new data and different age groups, none of their chief College selectivity variables predict future income — we don’t know whether some other aspect of College does. It’s possible that your choice of College matters even more than before, but in a different matter — ie, tuition paid could be a worse measure today given widespread tuition inflation; the US News & World report could have changed College rankings, or so forth.

2) In looking at why their results changed for this paper, Krueger and Dale find that their effects already diminish when using the sample of Colleges used for this paper as opposed to the sample from the old paper; and diminish even more when using government income rather than self-reported income. This tells us two things. One, the schools dropped for this paper (Denison, Hamilton, Kenyon, Rice, UNC) may matter a lot for future income, or else the inclusion of two historically black Colleges might affect the results. Second, it’s puzzling to think of why the results would change dramatically depending on the source of income. We know from other studies that individuals systematically under-report income both to surveys and in official government data. It’s not clear that the government data is “better” in the sense of getting a more accurate picture. The authors also exclude income received from capital gains, which doesn’t strike me as a good exclusion. Either students who went to elite schools lie more about their income, or are better at hiding it from the government (or else receive more of it in the form of capital gains). All that we can seriously say is that the conclusion you draw depends enormously on the data source you use for income and set of Colleges.

3) The results for both tuition and selectivity still show sizable effects for the 1976 cohort. Their Table 5 breaks out the effects of tuition and College selectivity by years. While none of these regressions are statistically significant on their own, the net effect is quite large. I applied the estimates on wages to the actual median wages in each time period (interpolating when the authors did not provide actual wage statistics). I estimate that a one percent increase in 1976 tuition (perhaps $100 total over four years) results in roughly a two percent increase in overall compensation through 2007 (assuming that you work for all 24 years), or $43k in non-inflation adjusted dollars. Alternately, a category shift in the Barron’s selectivity criteria (ie, from Highly Competitive to Most Competitive) is associated with $45k more in lifetime income. The effects of both selectivity and tuition grow over time, and are at their highest for wages observed in 2003-2007 (at this point, a one percent increase in tuition paid in 1976 gets you roughly $4k more a year per year. Presumably, this will rise even more by the time this cohort retires.

While the results from any one regression may not be statistically significant, that may simply be due to their sample size. The cumulative effect appears rather large in magnitude for both of the measures that were quite important in earlier drafts of the paper. This does change substantially when looking at the 1989 cohort, and it very possible that College selectivity is less important today (or else that group has not been in the workforce long enough to measure an effect).

4) Robin Hanson has some good commentary as well, focusing on the fact that the estimates for average school SAT on female earnings is negative and statistically significant. He suggests women going to more prestigious schools marry high earners, and so feel less need to make money themselves. I’ll only note that the results do subset among full-time earners, so it’s unlikely that this result is being generated by women withdrawing from the workplace altogether. The tuition/selectivity results above apply to a pooled sample of men and women, and so may result in even higher estimates for male workers.

Anyway, go check out all the papers referenced here. My prior belief on this, created by the first two Krueger and Dale papers, is that the College you go to affects your earnings. This new paper shakes this belief somewhat, and I am now not sure either way. Unfortunately, this data isn’t released publicly, so I can’t check to see if the authors calculations hold up depending on how you cut the data. In any case, you probably shouldn’t be basing your choice in Colleges on the basis of any study, and certainly not from this blog.

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