Category: Education
How big is your chance of dying in an ordinary day?
A Micromort can also be compared to a form of imaginary Russian roulette in which 20 coins are thrown in the air: if they all come down heads, the subject is executed. That is about the same odds as the 1-in-a-million chance that we describe as the average everyday dose of acute fatal risk.
That is from Michael Blastland and David Spiegelhalter, The Norm Chronicles: Stories and Numbers About Danger, which is an interesting book about the proper framing and communication of risk.
The Rise of Artificial Intelligences
Here is a well done video from PBS on artificial intelligence(s). Robin Hanson is excellent and is featured around 3:27-5:30.
Is there a Flynn effect for dementia?
It seems so:
A new study has found that dementia rates among people 65 and older in England and Wales have plummeted by 25 percent over the past two decades, to 6.2 percent from 8.3 percent, the strongest evidence yet of a trend some experts had hoped would materialize.
Another recent study, conducted in Denmark, found that people in their 90s who were given a standard test of mental ability in 2010 scored substantially better than people who reached their 90s a decade earlier. Nearly one-quarter of those assessed in 2010 scored at the highest level, a rate twice that of those tested in 1998. The percentage severely impaired fell to 17 percent from 22 percent.
From Gina Kolata, there is more here.
Bryan’s breakdown on my break down
Re: my post immediately below on signaling, Bryan thinks I haven’t answered his question about the importance of signalling. But I have, he is just confused because I don’t use the exact same normalization as he does. In any case, I postulate the wage return to signalling as going away within five years, in say a career of forty years, then with the measure adjusted for the presence of capital and resource income. You can express that in terms of totals, variations, percentages, as you wish but the point remains that signaling is only a temporary factor, and overall only somewhat of a marginal factor (5-10%?) in explaining the overall evolution of wages. That is why it has lost ground to human capital approaches, all the more so with increasing inequality. (One can believe all of that and still think, as I do, that we could organize current education more efficiently and at lower cost.) I also stand by my points that insisting on the break down is missing the more important points about indeterminacy and nestedness and those points too can be applied to any normalization of the units. It would be more useful if Bryan would outline where he disagrees with my assessment, as the entire chain of reasoning is laid out pretty explicitly.
By the way, the easiest way to boost the contribution of signaling is to invoke the “you got your first job by signaling and then from that job quickly gained persistent extra human capital” argument, but even then that increment can, under traditional measures, be assigned to human capital. (You don’t want to rule out all human capital influences, on the grounds that signaling helped create them, any more than you wish to classify gains from signaling as human capital, if the human capital helped you get into the position to signal. But if that doesn’t convince you, revisit the earlier point about indeterminacy, as you can see that the marginal products for human capital and signaling will sum to well over one hundred percent.)
How much of education and earnings variation is signalling? (Bryan Caplan asks)
On Twitter Bryan asks me:
Would you state your human capital/ability bias/signaling point estimates using my typology?
He refers to this blog post of his, though he does not clearly define the denominator there: is it percentage of what you spend on education or explaining what percentage of the variation in lifetime earnings? I’ll choose the latter and also I’ll focus on signaling rather than trying to separate out which parts of human capital are from birth and which are later learned. My calculations are thus:
1. I don’t wish to count “credentialed” occupations, where you need a degree and/or license, but you are reaping rents due to monopoly privilege. It’s neither human capital nor signaling (it’s not about intrinsic talent), though you could argue it is a kind of human capital in rent-seeking. In any case, let’s focus on private labor markets without such barriers.
2. Most capital and resource income is due to factors better explained by human capital theories or due to inheritance. That is more than a third of earnings right there. Note that the higher is inequality, the less the signaling model will end up explaining. That is one reason why the signaling model has become less relevant.
3. Depending on job and sector, what you’ve signaled, as opposed to what you know, explains a big chunk of wages in the first three to five years of employment. Within five years (often less), most individuals are earning based on what they can do, setting aside credentialism as discussed under #1. Here is my earlier post on speed of employer learning.
Keep in mind that everyone’s wages change quite a bit over their lifetime and that is mostly not due to retraining (i.e., changes in the educational signal) in the formal sense, as most people stop formal retraining after some point. The changes are due to employer estimates of skill, modified by bargaining power. In this sense all theories are predominantly human capital theories, whether they admit it or not.
To be generous, let’s give Bryan the full first five years of income based on signaling alone, out of a forty year career. And let’s say that on average wages rise at the rate of time discount (not true as of late, but a simplifying assumption and I think Bryan believes in a claim like this anyway.)
How much of income is explained by signaling? I’m coming up with “1/8 of 2/3,” the latter fraction referring generously to labor’s share in national income. That will fall clearly under ten percent, but recall I’ve inserted some generous assumptions here.
Bryan wants to call me “a signaling denialist,” yet I see signaling as still very important for understanding some aspects of the labor market. But it’s far from the main story for the labor market as a whole, especially as you move into the out years.
That all said, this “decomposition” approach may obscure more than it illuminates. Let’s consider two parables.
First, imagine a setting where you need the signal to be in the game at all, but after that your ingenuity and your personal connections explain all of the subsequent variation in income. Depending what margin you choose, the contribution of signaling to later income can be seen as either zero percent or one hundred percent. Signaling won’t explain any of the variation of income across people with the same signal, yet people will compete intensely to get the signal in the first place.
Second, in a basic signaling model there are two groups and one dimension of signaling. That’s too simple. A signaling model implies that a worker is paid some kind of average product throughout many years, but of course the reference class for defining this average product is changing all the time and is not, over time, based on the original reference class of contemporaneous graduating peers. For the purposes of calculating your wage based on a signal, is your relevant peer group a) all those people who got out of bed this morning, b) all those people in the Yale class of 2012, or c) all those who have been mid-level managers at IBM for twenty years? This will change as your life passes.
So there’s usually a signaling model nested within a human capital model, with the human capital model determining the broader parameters of pay, especially changes in pay. The employer’s (reasonably good but not perfect) estimate of your marginal product determines which peer group you get put into, if you choose to invest in additional signals (or not). The epiphenomena are those of a signaling model, but the peer group reshufflings over time are ruled by something else. Everything will look like signaling but again over time signaling won’t explain much about the variation or evolution in wages.
Seeing the relevance of those “indeterminacy” and “nested” perspectives is more important than whatever decomposition you might cite to answer Bryan’s query.
The faculty are unhappy
Here is one recent report of falling salaries in public institutions, and, on the bright side, universities are having trouble filling some of those slots:
Public university professors don’t enter the profession to get rich. But some faculty are having trouble paying bills, and have even qualified for foods stamps, Olson said. “For somebody to go five to seven years beyond college to obtain a Ph.D. degree and to realize that you are in need of federal assistance to make ends meet — and that’s for a tenure-track position –” is devastating.
Adding what some view as insult to injury, a recently published database of public employee salaries shows that some professors earn less than their colleagues at local high schools without doctorates.
Yet how would they feel about actual poor people? The article focuses on University of Wisconsin, Stevens Point, and serves up the following numbers:
Faculty salaries averaged $67,000 for full professors; $57,100 for associate professors; and $51,900 for assistant professors during the 2012-13 academic year.
The prisoners’ dilemma with actual prisoners
This is from a new research paper by Menusch Khadjavi and Andreas Lange:
We compare female inmates and students in a simultaneous and a sequential Prisoner’s Dilemma. In the simultaneous Prisoner’s Dilemma, the cooperation rate among inmates exceeds the rate of cooperating students. Relative to the simultaneous dilemma, cooperation among first-movers in the sequential Prisoner’s Dilemma increases for students, but not for inmates. Students and inmates behave identically as second movers. Hence, we find a similar and significant fraction of inmates and students to hold social preferences….
The blog post and link to research is here, hat tip goes to @Noahpinion.
The market speaks
Should Oregon fund college through equity?
Here is the latest proposal, which seems to stand a chance of actually happening:
This week, the Oregon Legislature approved a plan that could allow students to attend state colleges without paying tuition or taking out traditional loans. Instead, they would commit a small percentage of their future incomes to repaying the state; those who earn very little would pay very little.
I’m all for this as an experiment, but I’m not sure how effective it will be. Here is one more detail:
The plan’s supporters have estimated that for it to work, the state would have to take about 3 percent of a former student’s earnings for 20 years, in the case of someone who earned a bachelor’s degree.
Twenty years is a long time and I fear the implied selection mechanism embedded in that time horizon. At the margin I would expect this to attract people who don’t have a vivid mental image of the distant future. Furthermore the terms of the program discriminate against those who expect high earnings or for that matter those who expect to finish. In other words, the drop out rate of the marginal students here may be relatively high. And what are the payback terms for dropouts? Do they get off scot free? Pay proportionately for what they finished? Pay much much less to reflect their lower expected wages? The six-year graduation rate at Oregon State is only about 61%. This is not a small question.
Funding education through debt or through family-based crowd-sourcing may serve up a better mix of students. By the way, this source says the repayment period is over 24 years, not 20. Again, keep in mind that “the rate of return for the marginal student” is not the same as the “rate of return for the marginal student who would be attracted by these terms.”
And is this a better or worse deal for the median student at say Oregon State? If most students take this offer, I fear that the university’s incentive to improve the quality of education will not stay intact at the margin. I do understand there is a version of this plan where the tuition revenue simply comes from a state program rather than from the student, but more likely than not Oregon would end up with a “complex formula” which weakens the incentives of the institutions at the relevant margin. (On the state side of the equation, there is an incentive to conserve on cash and make the marginal tuition “free,” rather than pay the same amount of cash to the school the student would have paid.) Alternatively, if most students do not take this offer, one has to wonder what is wrong with it and adjust one’s estimate of the adverse selection problem accordingly.
Let’s assume, for the purposes of argument, that the 3% future “tax” won’t hurt labor supply at all. How is this program so different from moving to the European model, where higher education is free or near-free and general taxes on the population are higher? Yet the European systems of higher education are generally worse than those in America, so why should we be trying to copy them or move toward them? If anything, they are trying to move closer to American models.
At the end of the day, I am willing to let Oregon make a likely mistake to find out how this works. Go ahead guys, do it, we are all watching.
I thank several loyal MR readers for the pointer.
Differential Pricing in University Education
Traditionally universities have charged every student the same tuition/price regardless of major. Under budget pressure, however, differential pricing is becoming more common. Differential pricing is tending to reduce the peculiar cross-subsidies that currently exist as pointed out in a new working paper by Kevin Stange (earlier version):
Higher education in the United States is heavily subsidized, both through direct support for institutions by state governments and private donors, and through federal and state support
directly to students. There are also substantial differences in the extent of subsidization across
institutions and sectors, with students at selective private institutions more heavily subsidized
than those at less selective institutions(Winston 1999). Less commonly noticed, however, is that
there are also large cross-subsidies between students within the same institutions due to the
conventional practice of charging similar tuition fees to all undergraduate students regardless of
the cost of instructing them. The cost of instruction differs tremendously between upper and
lower division coursework and across programs even within institutions. For instance, recent
analysis of cost data from four large state post-secondary systems (Florida, Illinois, New York‐
SUNY, and Ohio) indicated that upper division instruction costs approximately 40% more per
credit hour than lower division instruction, and that upper-division engineering, physical science,
and visual/performing art was approximately 40% more costly than the least costly majors
(SHEEO, 2010). In fact, an earlier but more extensive cost study found that more than three-fourths of the variance in instructional cost across institutions is explained by the disciplinary
mix within an institution (U.S. Department of Education 2003). The consequence is that lower division students subsidize upper-division students and students in costly majors are subsidized
by those in less expensive ones.This pattern of cross-subsidization generally runs counter to differences in post-schooling
earnings and ability to pay. Lower division includes many students who eventually drop out,
while students that have advanced to upper division are more likely to graduate and earn more.
Engineering, science, and business majors tend to earn more and have higher returns than
education and humanities majors, even after controlling for differential selection of major by
ability (Arcidiacono 2004).
I have argued for targeting education subsidies to the majors that are most likely to have the greatest positive spillovers. Differential pricing moves prices closer to costs which opens up the possibility for more rational pricing but notice that it can in some cases move prices away from optimal subsidy levels.
Hat tip: Dubner at Freakonomics.
Why are there not more science majors?
There is a new paper (pdf) by Ralph Stinebrickner and Todd R. Stinebrickner on this topic, and here is their bottom line conclusion:
We find that students enter school quite optimistic/interested about obtaining a science degree, but that relatively few students end up graduating with a science degree. The substantial overoptimism about completing a degree in science can be attributed largely to students beginning school with misperceptions about their ability to perform well academically in science.
What is the most ridiculous thing someone has ever tried to convince you of?
Here is a Quora forum on that topic, with some good answers.
I liked this response by Shivang Agarwal:
That Windows is trying to find a solution to the problem just occurred.
*World War Z*
I was surprised how serious a movie it is and also by how deeply politically incorrect it is, including on “third rail” issues such as immigration, ethnic conflict, North Korean totalitarianism, American urban decay as exemplified by Newark, gun control, Latino-Black relations, songs of peace, and the Middle East. Here is one (incomplete) discussion of the Middle East angle, from the AP, republished in el-Arabiya (here is a more detailed but less responsible take on the matter, by a sociology professor and Israeli, spoilers throughout).
The movie is set up to show sympathy for the “Spartan” regimes and to have a message which is deeply historically pessimistic and might broadly be called Old School Conservative, informed by the debates on martial virtue from pre-Christian antiquity. But they recut the final segment of the movie and changed the ending altogether, presumably because post-Christian test audiences and film executives didn’t like it. Here is one discussion of the originally planned finale. It sounds good to me. The actual movie as it was released reverts to a Christian ending of sorts. My preferred denouement would have relied on the idea of an asymptomatic carrier or two, go see it and figure out the rest yourself.
By the way, for all the chances taken by the film makers, they were unwilling to offend the government of China (see the first link), in part because you cannot trick them easily with subtle, veiled references. Such tomfoolery works only on Americans — critics included — which I suppose suggests a lesson of its own.
Here is a Times of Israel review of the movie, interesting throughout, and it notes that the Israel scenes are simply translated to “the Middle East” for Turkish audiences.
A good film, I liked it. How many other movies offer commentary on Thucydides, Exodus, Gush-Shalom, Lawrence Dennis, and George Romero, all rolled into one?
Let’s detect and undo one of the most popular intellectual fallacies ever
As a case in point, consider my recent post arguing that Andrew Sullivan is the most influential public intellectual of the last twenty-five years. Such a claim will raise the status of Sullivan. While I am happy to see his status raised, that is not my point. My point is merely that he has been very influential, and in the sense of changing actual real world outcomes, a claim which most other public intellectuals of high status cannot even begin to make. The comments on the post are mostly weak, especially those comments critical of Sullivan. Some people are arguing that Sullivan does not in fact deserve higher status. And that in turn is causing them to misjudge, or fail to judge at all, the claim about his influence.
If you can avoid this fallacy consistently, and unpack the positive claim from any and all implications about changes in status, you will think much better and learn much more. I find also that very smart people are not necessarily more protected against this mode of fallacious reasoning.
Many blogs of course pander to this very fallacy. Why not be more explicit? One could put a post up with the person’s name and photo and simply write: “OK people, let’s argue in the comments whether this person deserves a higher or lower status.” But that would be too explicit, and it would lower the status of the blogger and commentator, so something else is written and the same debate ensues.
Amish arbitrage fact of the day
Eight percent of one sample (n = 112) of Lancaster county Amish have sought medical care in Mexico.
That is from Donald B. Kraybill, Karen M. Johnson-Weiner, and Steven M. Nolt, The Amish, which is an excellent social scientific look at what we outsiders know about Amish communities.
I also learned that the Amish strongly frown on home schooling of children and consider it possible grounds for excommunication. The requirement to use the internet has pushed many Amish out of public school systems, and the Amish are experts at making apprenticeship systems work. Inequality of wealth seems to be rising among the Amish.