Elite College Fems Earn Less

David Leonhardt:

A decade ago, two economists — Stacy Dale and Alan Krueger — published a research paper arguing that elite colleges did not seem to give most graduates an earnings boost. … Ms. Dale and Mr. Krueger have just finished a new version of the study — with vastly more and better data … and the new version comes to the same conclusion. (more; HT Tyler)

Ezra Klein quotes David approvingly. But as I reported two years ago, many, like David and the original paper’s abstract, quite misleadingly ignored its (statistically significant) finding that:

Men who attend the most competitive colleges [according to Barron’s 1982 ratings] earn 23 percent more than men who attend very competitive colleges, other variables in the equation being equal. …

Ack!  I was almost conned by elite journal editors and media reporters into believing a comforting lie!  What saved me was becoming puzzled by actually reading the original paper.

The new study’s abstract is also seriously misleading, suggesting that the study finds no effect of college average SAT scores on graduate earnings:

When we adjust for unobserved student ability by controlling for the average SAT score of the colleges that students applied to, our estimates of the return to college selectivity fall substantially and are generally indistinguishable from zero. There were notable exceptions for certain subgroups, [namley] for black and Hispanic students and for students who come from less-educated families.

To find the truth, you have to study Table 4 carefully, and note footnote 13:

For both men and women, the coefficient was zero (and sometimes even negative) [in] the self-revelation model.13

[footnote:] 13 This lower return to college selectivity for women is consistent with other literature. Results from Hoekstra (2009), Black and Smith (2004) and Long (2008) all suggest that the effect of college selectivity on earnings is lower for women than for men.

Table 4 shows that attending a college with higher SAT scores clearly lowered the wages of women 17-26 years after starting college (in 1976) — a school with a 100-point higher average SAT score reduced earnings by about 6-7%!  The two estimates there are significant at ~0.01% level! (The other three, for other periods after starting college, are significant at the 5% level.)

One obvious explanation is that women at more elite colleges married richer classmate men, and so felt less need to earn money themselves. Why don’t the study’s authors want us to hear about that?

The new study conflicts with the earlier one in finding no significant effects of college higher tuition or Barron’s selectivity rating on later earnings. The authors attribute those differences mostly to the earlier study using reported earnings, while this new study used Social Security Administration data. So do elite college folks do earn more, but hide it better from the government, or do they just lie more about their income? The relevant section from the new paper on this conflict:

[Regarding] the Barron’s Index and the log of net tuition … estimates …are statistically insignificant at the 0.10 level. These results are partly a contrast to Dale and Krueger (2002), in that the earlier analysis of self-reported earnings data showed a statistically significant relationship. … When we estimated the same regression for the same sample, but used SSA’s administrative earnings data … over the full study period (1983 to 2007) the coefficient on net tuition was generally between 0 and .02 (and never greater than .033) in the self-revelation model based on earnings drawn from SSA administrative data as the outcome measure.

Added 8a: I started college in ’77, so this cohort is pretty much my cohort.

The ’98 D&K working paper nearly as large a sample, but didn’t see any sort of negative effect for women. Suggests something isn’t reliable here.

Thorfinn has a nice long post, where he points out that 1) this new data ignores capital gains income, 2) the point estimates for tuition and selectivity imply high rates of return, 3) those estimates would be be more significant if the data were pooled across future earning years, and 4):

The results do subset among full-time earners, so it’s unlikely that this [fem earning less] result is being generated by women withdrawing from the workplace altogether.

Added 9a 24Feb: The authors respond below:

The return to college selectivity was not significantly greater than zero for men or for women. In a handful of specifications, the return was less than zero for women, but in the vast majority of specifications that we examined it was not statistically different from zero, so any explanations about why the payoff may be negative for women is pure speculation, and probably unwarranted. The most likely reason for the occasional negative payoff for women is that it was due to random sampling error.

The only estimates presented in your new paper are in Table 4, which considers five time periods, and these are the five t-stats – the second row is using robust errors.

-3.08 -2.27 -3.28 -3.45 -1.67
-1.61 -1.79 -3.69 -4.31 -1.94

You really attribute a t-stat of 4.3 to sampling error?!  Even the lowest entry here, -1.61, is noteworthy.  What are the “vast majority” specifications where t-stats are much lower?

Added 1p 24Feb: The authors respond again saying that in models tried but not mentioned in the paper,

The estimated return to school characteristics was generally not statistically significant for women.

Thorfinn notes:

I was surprised by their comment, “The paper is not about gender differences from college selectivity, and we have little reason to suspect that there are such differences.” Well, all three drafts of this paper that are online emphasize the results for attending College on various subgroups — for instance, by race, parental education, and parental income. Surely gender is an equally interesting subgroup.

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  • Buck Farmer


    Lowering the opportunity income cost of cutting back on a career to have children and increasing the opportunity genetic cost of not having kids seems a plausible arugment.

    But it would have to swamp and difference in ability, drive, networks et cetera.

    Anecdotally, I’ve a hard time imagining most of the elite college fems I know settling for a lighter career while marrying a higher-earning mate.

    • Eric H

      “Anecdotally, I’ve a hard time imagining most of the elite college fems I know settling for a lighter career while marrying a higher-earning mate.”

      I have no problem believing it. My high school had about a 95% college grad rate (not a typo – private college prep), but I was surprised that many of the girls dropped out of the labor force by about our 15 year reunion. In talking to them, I discovered that many of your volunteer-led organizations (PTA, soccer, etc.) are probably run by these highly educated, highly motivated supermoms.

  • Buck Farmer

    What about the effect of winner-take-all economics? Men seem to win more tournments as the stakes get higher, while women seem to beat out men in the middle-class.

    Could it simply be that elite colleges have more people entering these sorts of tournments and so the gap is getting magnified?

  • “Anecdotally, I’ve a hard time imagining most of the elite college fems I know settling for a lighter career while marrying a higher-earning mate.”

    I’ve seen it dozens of times.

    • nw

      I’ll defer to authority. Michael Lewis can say it better than I can.


      • siduri

        That article is ridiculous in its obliviousness. Lewis starts with an unexamined assumption–that the traditional “women’s work” of managing a household and raising children is trivial, worthless work–that leads him into a hilarious befuddlement when faced with what’s actually a completely straightfoward arrangement.

        The confusion vanishes if you revise the assumption. Start with a belief that managing a household and raising children is real and valuable work, and of course it makes sense that a successful man would “hire” the most intelligent, capable woman he can find for the position. It also dissolves the mystery around her willingness to accept the role–she’s not “embarrassed by her situation” because she knows the value of the work she does. This woman is not lounging around eating bon-bons and watching soap operas. She’s managing the servants, overseeing her husband’s personal health and quite possibly his personal finances as well, maintaining the social relationships that will be invaluable to him in his career, almost certainly continuing to serve his company in what amounts to an unpaid advisory capacity, *and* she’s caring for his children and overseeing their education. She’s busy, and both she and he know that the work she does is important.

  • On the other hand, it’s also worth considering one could make too much of the substantive significance of this result.

    First, it’s unclear to me that the result is clearly statistically significant. From Table 4, looking a the self-revelation models for conditional medians of women’s earnings, the cluster-robust standard errors only have a statistically significant negative slop for 1993-2002. The others aren’t significant at alpha=.05, as far as I can tell…

    Second, my reasoning might run in the other direction: this might be a further reminder that the causal conclusions we want to try depend on ignorability, and even with the included covariates, this likely isn’t satisfied.

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  • I could provide all sorts of just-so theories, but the truth is this is counterintuitive to me too.
    In my microsocial world elite fems seem to me to be out-earning non-elite college fems, including on-the-books earnings.

  • Emily

    I’m curious as to what’s up with the use of (what seems to me) the very weird word “fems” here. It’s even been adopted by the commenters. I’ve seen it before, but I think possibly only on OB. Is it distinguished from “women” in some way?

    • Robin uses a lot of abbreviations, “fems” for females, “tech” for technology, “ems” for emulations. Like a lot of nerds, I see the value in the efficiency of such abbreviations, but I also think they distract many people from the content of Robin’s writing.

    • Millian

      “fems” is a pretty poor abbreviation for “women”, which suggests that something else is causing this extremely odd choice of language. It’s almost dehumanising.

      • Jess Riedel

        I think if you read more of his posts, you’ll see he does this with all sorts of stuff. Examples: “med” , “docs” , “shoulds”, “wants” and, importantly for your concern, the gender-specific “cads” and “dads”.

  • Robert Wiblin
  • OhioStater

    There was a controversial article about this in the New York Times a few years ago.


    It was controversial because the author is implying women either go to “Miss Fairley’s finishing school” to become a wife, or go to Yale Law and try to make partner.

    Sort of like having cake and eating too, many women saw no problem with going to Yale Law to meet a man that would become partner.

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  • cournot

    Razib’s points are also good about net effects of tuition. I think that weak statistical significance is coming from sample sizes and by focusing only on those areas which show significance, the authors are making the McCloskey derided mistake of confusing statistical and substantive significance. It seems more likely that there are a variety of school effects that matter but the authors are concentrating on the favorable ones that hit the significance level while not properly digging into the large tuition /income correlations etc or other measures of elite influence that might be harder to tease out or weren’t so clearcut.

    For example, what would a study confined to the US News top ten vs schools outside the top 50 show?

    And what about non pecuniary outcomes? Aren’t there papers looking at superstars in academia? Supreme Court? Fields Medal?
    Nobel Prize? Prob of becoming a billionaire? President of forbes 500 company? These are big tournaments with few winners and where status is as important as money but I bet the elites are disproportionately represented there.

    The authors treat someone earning 250K in a low status job the same as someone earning 250k in a high status job.

  • cournot, to an economist job status is only measured by job income. There is no such thing as a low status job that earns a lot of money. There is no such thing as a high status job that doesn’t.

    Interesting that the obvious reason is not even mentioned, namely that elite women don’t prioritize high income as much as all these economists think they should, and that the jobs that these elite women choose to do are not the highest paying jobs.

    What this tells me is that our compensation system is FUBAR. It is not rewarding those with the most ability, it is rewarding those with the largest greed and the greatest willingness to use whatever ability they have to extract as much value-added as possible from everyone else.

    It is like politics in places like Libya, North Korea and Zimbabwe. The person who is the “leader” is not the person with the most ability at leading, it is the person who uses their ability to thwart the ability of anyone else to lead, usually by killing them.

    Taking a larger cut of an already existing pie always takes less ability than making the pie bigger. When you don’t leave enough pie to continue to feed the pie makers, the economy goes into a death spiral like in Libya, North Korea and Zimbabwe. Liquidation and expropriation of existing resources (oil in Libya for example) may stave that decline off for a while.

    In the US, the resource that is being liquidated and expropriated is the “good will” of the American people through appeals to hope, patriotism and xenophobia. That “good will” is being liquidated by selling debt to fund tax cuts and foreign wars to enrich the wealthy and the war profiteers. People who have figured out how to game the system to extract ever bigger pieces of pie.

    • Millian

      You have clearly never read The Wealth Of Nations

  • The author of the other post you link to was me, not Razib. Just sayin’.

  • Anthony

    If I’m reading this right, a woman with a given SAT score will make less money if the college she went to had a higher average SAT. Robin has not mentioned what statistical effect the woman’s (or man’s) SAT score has on future earnings. My guess is that women (possibly more than men) who go to schools where there are lots of people smarter than they are more likely to major in departments which don’t provide meal-ticket degrees.

  • Stacy Dale and Alan Krueger

    Hanson misinterprets our research, and weaves the popular coverage of our studies into a grand conspiracy. While nothing sinister is going on, there is quite a bit of confusion, as Hanson mistakenly combined our published abstract with results from our original working paper and drew conclusions from the wrong column of estimates.

    While we did report a 23% return associated with attending the most selective colleges (according to the 1982 Barron’s ranking) in our earliest working paper, these results were from our basic model–which does NOT adjust for student unobserved characteristics. The numbers Hanson emphasizes are the straw man that we were seeking to test. In our matched applicant model – which was the new contribution of our research — the return was much smaller and statistically insignificant for men and women. Our final published paper (in the Quarterly Journal of Economics)—and the abstract Hanson links to–did not focus on the original Barron’s result because we later obtained three additional years of the Barron’s index from the late 1970s (when the students in the sample entered college), and only the version from 1982 suggested a possible relationship between the Barron’s index and earnings. And even this one outlying Barron’s result appeared to be extremely sensitive to how one or two colleges were categorized in the Barron’s index. In the published version of our paper, we specified the Barron’s Index in the same way as Brewer, Ehrenberg and Eide did, and we found that attending a higher ranked school according to the Barron’s Index was not related to subsequent earnings once similar students were compared.

    The goal of our current paper is to see if our earlier results are robust over the course of student’s career and to extend our estimates for a recent cohort of students. After controlling for student’s unobserved characteristics, the return to college selectivity was not significantly greater than zero for men or for women. In a handful of specifications, the return was less than zero for women, but in the vast majority of specifications that we examined it was not statistically different from zero, so any explanations about why the payoff may be negative for women is pure speculation, and probably unwarranted. The most likely reason for the occasional negative payoff for women is that it was due to random sampling error.

    • Thanks for responding. I’m happy to accept that the 23% figure is misleadingly high, for the reasons you suggest.
      On the differing effect on women, see my added to the post.

  • Stacy Dale and Alan Krueger

    You are right that we only reported five estimates for women in the paper, two of which are significant. However, as is common in empirical research, we estimated models that are not reported in the paper to probe the robustness of the results (for example, regressions with different measures of school quality, with different minimum wage thresholds, for the 1989 cohort, for specific years, etc.). The estimated return to school characteristics was generally not statistically significant for women. Also, as is common in research, we did not mention the results from every model we estimated in the paper. Rather, we discussed those results that were robust to a wide variety of specifications and most central to the paper. The paper is not about gender differences from college selectivity, and we have little reason to suspect that there are such differences.

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  • cournot


    It is simply not correct that economists only measure job quality by income. To see the absurdity of the statement, ask yourself how many top professors can be lured away to lower level departments by a mere ten or twenty percent salary raise. Economists have long understood the role of compensating differentials. It is you who are mistaken. The fact that good jobs are correlated with high incomes does not mean that tradeoffs don’t exist and are well understood by the profession. So while I accept that income measures are a good first cut, ignoring the boost to the status (as well as comfort, location, flexibility, etc.) aspects of job search understates the potential benefits of the elite schools. Dale and Krueger acknowledge this in their earlier version but don’t treat it at all in the new paper.

  • cournot, I was referring to job status, not job quality. To the extent that money buys status (which it does in the USA), salary determines job status.

    In your example you talked about high status and low status jobs with a $250K income level. I don’t think there are any low status jobs that earn $250K as you suggest. I would like to see a few examples of jobs that earn $250K that are low status.

    I can see someone exchanging marginal income for marginal status, and maybe to those making $2.5M income perceive all $250K jobs to be low status, and maybe those making $250K feel like they have low status compared to those making $2.5M, but do they feel they have low status compared to anyone making $25K? I don’t think so.

    I don’t know if Robin posted about it, but Paul Krugman did.


    Job status is about status relative to other jobs, and status is a social measure that has been monetized in todays economy. The more money you have, the more status you have. Maybe there are some exceptions, but as far as I can tell, essentially no one really says that except the wealthy when they are trying to justify why wealth should not be important to the poor, and then they are simply being disingenuous.

    • It’s sad to complain about the rich. It makes you look like a loser.

      • I am not complaining about the rich, I am complaining about the rich complaining about being poor.

  • halfassured

    It sounds as though they’re generating p-values for a lot of different groups. Are the low p-values on the factors you’re looking at isolated, or did you use a multiple comparisons correction?