Category: Education

Jane Street Capital: What is the smallest number divisible by 225 that consists of all 1’s and 0’s?

I believe it must end with a zero.  And the next to last digit must be a zero.  Keep on going.  Via Chris Blattman, here are some more, along with a few snarky answers.

Yglesias on the inconsistent stories told by the teachers unions.

[there] is a huge consistency problem in the messaging coming out of teachers unions. Sometimes I hear from union-affiliated folks that it’s unfair to attribute differences in student learning to differences in teacher skill, because everyone knows that socioeconomic and home environment factors drive a lot of this. Other times I see the American Federation of Teachers building a messaging program around the idea that its members are Making A Difference Every Day. To me this leads to the obvious conclusion that while socioeconomic and home environment factors do drive a lot of student learning, teachers are also making a difference every day. And it makes a lot of sense to ask which teachers are making the most difference. The teachers who are in the top 20 percent of difference-makers are playing a vital role to the future of America, and we ought to pay them more money and make sure they don’t leave the profession. But the teachers who are in the bottom percent of difference-makers are doing us little good, and we should try to replace them with other people.

Read the whole thing,  he makes a number of good points.

Here is a comment by Matt, and also by Arnold.  Bryan’s response argues that the returns to education tests consider “ability bias” but not “signaling.”  For a lot of the tests that is a distinction without a difference, and indeed you can see this on the first two pages of Angrist and Krueger, which discuss “omitted variables that are correlated with educational attainment and with earnings capacity.”  The tests still discriminate against the signaling model, even if signaling and ability bias differ in other regards.  In a nutshell, artificially or randomly elevated workers fare better in the longer run than the signaling model predicts.

Here’s a parable to illustrate.  Imagine a market situation with wages and different education levels observed for two classes of workers — call the locale Honduras.  Now compare that to another setting — Nicaragua — where education is handed out on some subsidized, randomized basis.  In the latter case some of the low ability group will be induced to get more schooling, and the pool of the educated will contain more low ability individuals in Nicaragua, compared to Honduras.

Now measure the long term earnings and compare.

If the signaling model is correct, the average long-term wage rates of return for the subsidized/elevated group in Nicaragua will be noticeably below the average wage rates of return of the educated group from the separating equilibrium in Honduras.  After all, the subsidy-elevated group adds many more “low ability individuals” to the Nicaraguan mix of the educated than one would find in Honduras.  According to the signaling model, in Nicaragua eventually the lower skill level of the elevated group will be discovered and their wage rates of return won’t stay so high forever.

But the wage rates of return for the elevated groups do not plummet back to earth and generally they are robust over time.  That measures the real learning which went on in school, or so it would seem.  Education is good for more than getting a good first job offer right off the bat.

The modern liberal interpretation (which may or may not be true) is that these poor people were waiting for a helping hand up the ladder, and then they took good advantage of it when it came.  And if the elevated group in Nicaragua has higher long-term wage rates of return than the educated Hondurans (a result which does sometimes pop up in the data), that is because their lower initial margin of education made them an especially potent investment.

The actual tests are more complicated than this, and I use the country names to make the example easy to follow, not out of verisimilitude.  But this example is one way to see some of the intuitions behind why the data do not treat the signaling model so kindly.

One empirical implication is that crude OLS measures of the return to education are much better than they may at first appear.  These results are also one reason why most modern labor economists might object to the arguments of Charles Murray.

Here is a recent Brookings piece on the return to education, I have not had time to go through it.

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.

Director Lotta Rajalin notes that Egalia places a special emphasis on fostering an environment tolerant of gay, lesbian, bisexual and transgender people. From a bookcase, she pulls out a story about two male giraffes who are sad to be childless — until they come across an abandoned crocodile egg.

That’s a preschool, for children from ages one to six.  The school does everything possible to obliterate traditional gender roles, including a refusal to use the words “him” and “her” (that is, their Swedish equivalents).

…she says that there’s a long waiting list for admission to Egalia, and that only one couple has pulled a child out of the school.

Jukka Korpi, 44, says he and his wife chose Egalia “to give our children all the possibilities based on who they are and not on their gender.”

There is even a markets in everything angle:

To even things out, many preschools have hired “gender pedagogues” to help staff identify language and behavior that risk reinforcing stereotypes.

For the pointer I thank Daniel Lippman.

David Leonhardt reports (longer version of the argument here):

The Hamilton researchers — Michael Greenstone and Mr. Looney — also offer a chart on lifetime earnings, which shows that a big part of college’s value is that it brings much larger raises over someone’s career:

Every now and then I give informal talks on how the economics job market operates.  I tell the listeners that they are like an “unwrapped saltine cracker.”  They are wasting assets, to borrow a phrase from options pricing theory.  If a day goes by and they did not accomplish something important, they decline in value.  For most candidates, holding steady is not a viable strategy.  You need either publications or some stellar letters from credible writers, preferably both.  (At the very top level, publications at the job market stage are less important because it is expected they will come and the recommendations are trusted more.)

Unwrap a saltine cracker, let it sit for months, and then try to eat it.  Will you even try?

It’s in Eskisehir, central Anatolia, a long way from home.  And yet the campus looks remarkably like George Mason University.  It has about the same number of students, the same kind of suburban feel, the same kinds of sculptures and fountains scattered around campus, the buildings use steps in a similar way, the cars are parked in similar configurations, there is similar signage, and there are related styles of architecture for the buildings.  Here are some photos.  All in all, it is quite unheimlich.

Both schools have women wearing Islamic head scarves, slightly more here.  The Anadolu campus was designed by an economist, unlike George Mason, and the school is a leader in distance education.

I would describe Eskisehir as the Curitiba of Turkey.  I am told it used to be much worse.

Here is a good recent piece on Eskisehir.