# Where is the money going in academia?

Feb 19 JDN 2459995

A quandary for you:

My salary is £41,000.

Annual tuition for a full-time full-fee student in my department is £23,000.

I teach roughly the equivalent of one full-time course (about 1/2 of one and 1/4 of two others; this is typically counted as “teaching 3 courses”, but if I used that figure, it would underestimate the number of faculty needed).

Each student takes about 5 or 6 courses at a time.

Why do I have 200 students?

If you multiply this out, the 200 students I teach, divided by the 6 instructors they have at one time, times the £23,000 they are paying… I should be bringing in over £760,000 for the university. Why am I paid only 5% of that?

Granted, there are other costs a university must bear aside from paying instructors. There are facilities, and administration, and services. And most of my students are not full-fee paying; that £23,000 figure really only applies to international students.

Students from Scotland pay only £1,820, but there aren’t very many of them, and public funding is supposed to make up that difference. Even students from the rest of the UK pay £9,250. And surely the average tuition paid has got to be close to that? Yet if we multiply that out, £9,000 times 200 divided by 6, we’re still looking at £300,000. So I’m still getting only 14%.

Where is the rest going?

This isn’t specific to my university by any means. It seems to be a global phenomenon. The best data on this seems to be from the US.

According to salary.com, the median salary for an adjunct professor in the US is about \$63,000. This actually sounds high, given what I’ve heard from other entry-level faculty. But okay, let’s take that as our figure. (My pay is below this average, though how much depends upon the strength of the pound against the dollar. Currently the pound is weak, so quite a bit.)

This means that an adjunct professor in the US with 200 students takes in \$760,000 but receives \$63,000. Where does that other \$700,000 go?

If you think that it’s just a matter of paying for buildings, service staff, and other costs of running a university, consider this: It wasn’t always this way.

Since 1970, inflation-adjusted salaries for US academic faculty at public universities have risen a paltry 3.1%. In other words, basically not at all.

This is considerably slower than the growth of real median household income, which has risen almost 40% in that same time.

Over the same interval, nominal tuition has risen by over 2000%; adjusted for inflation, this is a still-staggering increase of 250%.

In other words, over the last 50 years, college has gotten three times as expensive, but faculty are still paid basically the same. Where is all this extra money going?

Part of the explanation is that public funding for colleges has fallen over time, and higher tuition partly makes up the difference. But private school tuition has risen just as fast, and their faculty salaries haven’t kept up either.

In their annual budget report, the University of Edinburgh proudly declares that their income increased by 9% last year. Let me assure you, my salary did not. (In fact, inflation-adjusted, my salary went down.) And their EBITDA—earnings before interest, taxes, depreciation, and amortization—was £168 million. Of that, £92 million was lost to interest and depreciation, but they don’t pay taxes at all, so their real net income was about £76 million. In the report, they include price changes of their endowment and pension funds to try to make this number look smaller, ending up with only £37 million, but that’s basically fiction; these are just stock market price drops, and they will bounce back.

Using similar financial alchemy, they’ve been trying to cut our pensions lately, because they say they “are too expensive” (because the stock market went down—nevermind that it’ll bounce back in a year or two). Fortunately, the unions are fighting this pretty hard. I wish they’d also fight harder to make them put people like me on the tenure track.

Had that £76 million been distributed evenly between all 5,000 of us faculty, we’d each get an extra £15,600.

Well, then, that solves part of the mystery in perhaps the most obvious, corrupt way possible: They’re literally just hoarding it.

And Edinburgh is far from the worst offender here. No, that would be Harvard, who are sitting on over \$50 billion in assets. Since they have 21,000 students, that is over \$2 million per student. With even a moderate return on its endowment, Harvard wouldn’t need to charge tuition at all.

But even then, raising my salary to £56,000 wouldn’t explain why I need to teach 200 students. Even that is still only 19% of the £300,000 those students are bringing in. But hey, then at least the primary service for which those students are here for might actually account for one-fifth of what they’re paying!

Now let’s considers administrators. Median salary for a university administrator in the US is about \$138,000—twice what adjunct professors make.

Since 1970, that same time interval when faculty salaries were rising a pitiful 3% and tuition was rising a staggering 250%, how much did chancellors’ salaries increase? Over 60%.

Of course, the number of administrators is not fixed. You might imagine that with technology allowing us to automate a lot of administrative tasks, the number of administrators could be reduced over time. If that’s what you thought happened, you would be very, very wrong. The number of university administrators in the US has more than doubled since the 1980s. This is far faster growth than the number of students—and quite frankly, why should the number of administrators even grow with the number of students? There is a clear economy of scale here, yet it doesn’t seem to matter.

Combine those two facts: 60% higher pay times twice as many administrators means that universities now spend at least 3 times as much on administration as they did 50 years ago. (Why, that’s just about the proportional increase in tuition! Coincidence? I think not.)

Edinburgh isn’t even so bad in this regard. They have 6,000 administrative staff versus 5,000 faculty. If that already sounds crazy—more admins than instructors?—consider that the University of Michigan has 7,000 faculty but 19,000 administrators.

Michigan is hardly exceptional in this regard: Illinois UC has 2,500 faculty but nearly 8,000 administrators, while Ohio State has 7,300 faculty and 27,000 administrators. UCLA is even worse, with only 4,000 faculty but 26,000 administrators—a ratio of 6 to 1. It’s not the UC system in general, though: My (other?) alma mater of UC Irvine somehow supports 5,600 faculty with only 6,400 administrators. Yes, that’s right; compared to UCLA, UCI has 40% more faculty but 76% fewer administrators. (As far as students? UCLA has 47,000 while UCI has 36,000.)

At last, I think we’ve solved the mystery! Where is all the money in academia going? Administrators.

They keep hiring more and more of them, and paying them higher and higher salaries. Meanwhile, they stop hiring tenure-track faculty and replace them with adjuncts that they can get away with paying less. And then, whatever they manage to save that way, they just squirrel away into the endowment.

A common right-wing talking point is that more institutions should be “run like a business”. Well, universities seem to have taken that to heart. Overpay your managers, underpay your actual workers, and pocket the savings.

# The real crisis in education is access, not debt

Jan 8, JDN 2457762

A few weeks ago I tried to provide assurances that the “student debt crisis” is really not much of a crisis; there is a lot of debt, but it is being spent on a very good investment both for individuals and for society. Student debt is not that large in the scheme of things, and it more than pays for itself in the long run.

But this does not mean we are not in the midst of an education crisis. It’s simply not about debt.

The crisis I’m worried about involves access.

As you may recall, there are a substantial number of people with very small amounts of student debt, and they tend to be the most likely to default. The highest default rates are among the group of people with student debt greater than \$0 but less than \$5000.

So how is it that there are people with only \$5,000 in student debt anyway? You can’t buy much college for \$5,000 these days, as tuition prices have risen at an enormous rate: From 1983 to 2013, in inflation-adjusted dollars, average annual tuition rose from \$7,286 at public institutions and \$17,333 at private institutions to \$15,640 at public institutions and \$35,987 at private institutions—more than doubling in each case.

Enrollments are much higher, but this by itself should not raise tuition per student. So where is all the extra money going? Some of it is due to increases in public funding that have failed to keep up with higher enrollments; but a lot of it just seems to be going to higher pay for administrators and athletic coaches. This is definitely a problem; students should not be forced to subsidize the millions of dollars most universities lose on funding athletics—the NCAA, who if anything are surely biased in favor of athletics, found that the total net loss due to athletics spending at FBS universities was \$17 million per year. Only a handful of schools actually turn a profit on athletics, all of them Division I. So it might be fair to speak of an “irresponsible college administration crisis”, administrators who heap wealth upon themselves and their beloved athletic programs while students struggle to pay their bills, or even a “college tuition crisis” where tuition keeps rising far beyond what is sustainable. But that’s not the same thing as a “student debt crisis”—just as the mortgage crisis we had in 2008 is distinct from the slow-burning housing price crisis we’ve been in since the 1980s. Making restrictions on mortgages tighter might prevent banks from being as predatory as they have been lately, but it won’t suddenly allow people to better afford houses.

And likewise, I’m much more worried about students who don’t go to college because they are afraid of this so-called “debt crisis”; they’re going to end up much worse off. As Eduardo Porter put it in the New York Times:

And yet Mr. Beltrán says he probably wouldn’t have gone to college full time if he hadn’t received a Pell grant and financial aid from New York State to defray the costs. He has also heard too many stories about people struggling under an unbearable burden of student loans to even consider going into debt. “Honestly, I don’t think I would have gone,” he said. “I couldn’t have done four years.”

And that would have been the wrong decision.

His reasoning is not unusual. The rising cost of college looms like an insurmountable obstacle for many low-income Americans hoping to get a higher education. The notion of a college education becoming a financial albatross around the neck of the nation’s youth is a growing meme across the culture. Some education experts now advise high school graduates that a college education may not be such a good investment after all. “Sticker price matters a lot,” said Lawrence Katz, a professor of Harvard University. “It is a deterrent.”

[…]

And the most perplexing part of this accounting is that regardless of cost, getting a degree is the best financial decision a young American can make.

According to the O.E.C.D.’s report, a college degree is worth \$365,000 for the average American man after subtracting all its direct and indirect costs over a lifetime. For women — who still tend to earn less than men — it’s worth \$185,000.

College graduates have higher employment rates and make more money. According to the O.E.C.D., a typical graduate from a four-year college earns 84 percent more than a high school graduate. A graduate from a community college makes 16 percent more.

A college education is more profitable in the United States than in pretty much every other advanced nation. Only Irish women get more for the investment: \$185,960 net.

So, these students who have \$5,000 or less in student debt; what does that mean? That amount couldn’t even pay for a single year at most universities, so how did that happen?

Well, they almost certainly went to community college; only a community college could provide you with a nontrivial amount of education for less than \$5,000. But community colleges vary tremendously in their quality, and some have truly terrible matriculation rates. While most students who start at a four-year school do eventually get a bachelor’s degree (57% at public schools, 78% at private schools), only 17% of students who start at community college do. And once students drop out, they very rarely actually return to complete a degree.

Indeed, the only way to really have that little student debt is to drop out quickly. Most students who drop out do so chiefly for reasons that really aren’t all that surprising: Mostly, they can’t afford to pay their bills. “Unable to balance school and work” is the number 1 reported reason why students drop out of college.

In the American system, student loans are only designed to pay the direct expenses of education; they often don’t cover the real costs of housing, food, transportation and healthcare, and even when they do, they basically never cover the opportunity cost of education—the money you could be making if you were working full-time instead of going to college. For many poor students, simply breaking even on their own expenses isn’t good enough; they have families that need to be taken care of, and that means working full-time. Many of them even need to provide for their parents or grandparents who may be poor or disabled. Yet in the US system it is tacitly assumed that your parents will help you—so when you need to help them, what are you supposed to do? You give up on college and you get a job.

The most successful reforms for solving this problem have been comprehensive; they involved working to support students directly and intensively in all aspects of their lives, not just the direct financial costs of school itself.

Another option would be to do something more like what they do in Sweden, where there is also a lot of student debt, but for a very different reason. The direct cost of college is paid automatically by the government. Yet essentially all Swedish students have student debt, and total student debt in Sweden is much larger than other European countries and comparable to the United States; why? Because Sweden understands that you should also provide for the opportunity cost. In Sweden, students live fully self-sufficient on student loans, just as if they were working full-time. They are not expected to be supported by their parents.

The problem with American student loans, then, is not that they are too large—but that they are too small. They don’t provide for what students actually need, and thus don’t allow them to make the large investment in their education that would have paid off in the long run. Panic over student loans being too large could make the problem worse, if it causes us to reduce the amount of loanable funds available for students.

The lack of support for poor students isn’t the only problem. There are also huge barriers to education in the US based upon race. While Asian students do as well (if not better) than White students, Black and Latino students have substantially lower levels of educational attainment. Affirmative action programs can reduce these disparities, but they are unpopular and widely regarded as unfair, and not entirely without reason.

A better option—indeed one that should be a no-brainer in my opinion—is not to create counter-biases in favor of Black and Latino students (which is what affirmative action is), but to eliminate biases in favor of White students that we know exist. Chief among these are so-called “legacy admissions”, in which elite universities attract wealthy alumni donors by granting their children admission and funding regardless of whether they even remotely deserve it or would contribute anything academically to the university.

These “legacy admissions” are frankly un-American. They go against everything our nation supposedly stands for; in fact, they reek of feudalism. And unsurprisingly, they bias heavily in favor of White students—indeed, over 90 percent of legacy admits are White and Protestant. Athletic admissions are also contrary to the stated mission of the university, though their racial biases are more complicated (Black students are highly overrepresented in football and basketball admits, for example) and it is at least not inherently un-American to select students based upon their athletic talent as opposed to their academic talent.

But this by itself would not be enough; the gaps are clearly too large to close that way. Getting into college is only the start, and graduation rates are much worse for Black students than White students. Moreover, the education gap begins well before college—high school dropout rates are much higher among Black and Latino studentsas well.

In fact, even closing the education gap by itself would not be enough; racial biases permeate our whole society. Black individuals with college degrees are substantially more likely to be unemployed and have substantially lower wages on average than White individuals with college degrees—indeed, a bachelor’s degree gets a Black man a lower mean wage than a White man would get with only an associate’s degree.

Fortunately, the barriers against women in college education have largely been conquered. In fact, there are now more women in US undergraduate institutions than men. This is not to say that there are not barriers against women in society at large; women still make about 75% as much income as men on average, and even once you adjust for factors such as education and career choice they still only make about 95% as much. Moreover, these factors we’re controlling for are endogenous. Women don’t choose their careers in a vacuum, they choose them based upon a variety of social and cultural pressures. The fact that 93% of auto mechanics are men and 79% of clerical workers are women might reflect innate differences in preferences—but it could just as well reflect a variety of cultural biases or even outright discrimination. Quite likely, it’s some combination of these. So it is not obvious to me that the “adjusted” wage gap is actually a more accurate reflection of the treatment of women in our society than the “unadjusted” wage gap; the true level of bias is most likely somewhere in between the two figures.

Gender wage gaps vary substantially across age groups and between even quite similar countries: Middle-aged women in Germany make 28% less than middle-aged men, while in France that gap is only 19%. Young women in Latvia make 14% less than young men, but in Romania they make 1.1% more. This variation clearly shows that this is not purely the effect of some innate genetic difference in skills or preferences; it must be at least in large part the product of cultural pressures or policy choices.

Even within academia, women are less likely to be hired full-time instead of part-time, awarded tenure, or promoted to administrative positions. Moreover, this must be active discrimination in some form, because gaps in hiring and wage offers between men and women persist in randomized controlled experiments. You can literally present the exact same resume and get a different result depending on whether you attached a male name or a female name.

But at least when it comes to the particular question of getting bachelor’s degrees, we have achieved something approaching equality across gender, and that is no minor accomplishment. Most countries in the world still have more men than women graduating from college, and in some countries the difference is terrifyingly large. I found from World Bank data that in the Democratic Republic of Congo, only 3% of men go to college—and less than 1% of women do. Even in Germany, 29% of men graduate from college but only 19% of women do. Getting both of these figures over 30% and actually having women higher than men is a substantial achievement for which the United States should be proud.

Yet it still remains the case that Americans who are poor, Black, Native American, or Latino are substantially less likely to ever make it through college. Panic about student debt might well be making this problem worse, as someone whose family makes \$15,000 per year is bound to hear \$50,000 in debt as an overwhelming burden, even as you try to explain that it will eventually pay for itself seven times over.

We need to instead be talking about the barriers that are keeping people from attending college, and pressuring them to drop out once they do. Debt is not the problem. Even tuition is not really the problem. Access is the problem. College is an astonishingly good investment—but most people never get the chance to make it. That is what we need to change.

# The replication crisis, and the future of science

Aug 27, JDN 2457628 [Sat]

After settling in a little bit in Irvine, I’m now ready to resume blogging, but for now it will be on a reduced schedule. I’ll release a new post every Saturday, at least for the time being.

Today’s post was chosen by Patreon vote, though only one person voted (this whole Patreon voting thing has not been as successful as I’d hoped). It’s about something we scientists really don’t like to talk about, but definitely need to: We are in the middle of a major crisis of scientific replication.

Whenever large studies are conducted attempting to replicate published scientific results, their ability to do so is almost always dismal.

Psychology is the one everyone likes to pick on, because their record is particularly bad. Only 39% of studies were really replicated with the published effect size, though a further 36% were at least qualitatively but not quantitatively similar. Yet economics has its own replication problem, and even medical research is not immune to replication failure.

It’s important not to overstate the crisis; the majority of scientific studies do at least qualitatively replicate. We are doing better than flipping a coin, which is better than one can say of financial forecasters.
There are three kinds of replication, and only one of them should be expected to give near-100% results. That kind is reanalysiswhen you take the same data and use the same methods, you absolutely should get the exact same results. I favor making reanalysis a routine requirement of publication; if we can’t get your results by applying your statistical methods to your data, then your paper needs revision before we can entrust it to publication. A number of papers have failed on reanalysis, which is absurd and embarrassing; the worst offender was probably Rogart-Reinhoff, which was used in public policy decisions around the world despite having spreadsheet errors.

The second kind is direct replication—when you do the exact same experiment again and see if you get the same result within error bounds. This kind of replication should work something like 90% of the time, but in fact works more like 60% of the time.

The third kind is conceptual replication—when you do a similar experiment designed to test the same phenomenon from a different perspective. This kind of replication should work something like 60% of the time, but actually only works about 20% of the time.

Economists are well equipped to understand and solve this crisis, because it’s not actually about science. It’s about incentives. I facepalm every time I see another article by an aggrieved statistician about the “misunderstanding” of p-values; no, scientist aren’t misunderstanding anything. They know damn well how p-values are supposed to work. So why do they keep using them wrong? Because their jobs depend on doing so.

The first key point to understand here is “publish or perish”; academics in an increasingly competitive system are required to publish their research in order to get tenure, and frequently required to get tenure in order to keep their jobs at all. (Or they could become adjuncts, who are paid one-fifth as much.)

The second is the fundamentally defective way our research journals are run (as I have discussed in a previous post). As private for-profit corporations whose primary interest is in raising more revenue, our research journals aren’t trying to publish what will genuinely advance scientific knowledge. They are trying to publish what will draw attention to themselves. It’s a similar flaw to what has arisen in our news media; they aren’t trying to convey the truth, they are trying to get ratings to draw advertisers. This is how you get hours of meaningless fluff about a missing airliner and then a single chyron scroll about a war in Congo or a flood in Indonesia. Research journals haven’t fallen quite so far because they have reputations to uphold in order to attract scientists to read them and publish in them; but still, their fundamental goal is and has always been to raise attention in order to raise revenue.

The best way to do that is to publish things that are interesting. But if a scientific finding is interesting, that means it is surprising. It has to be unexpected or unusual in some way. And above all, it has to be positive; you have to have actually found an effect. Except in very rare circumstances, the null result is never considered interesting. This adds up to making journals publish what is improbable.

In particular, it creates a perfect storm for the abuse of p-values. A p-value, roughly speaking, is the probability you would get the observed result if there were no effect at all—for instance, the probability that you’d observe this wage gap between men and women in your sample if in the real world men and women were paid the exact same wages. The standard heuristic is a p-value of 0.05; indeed, it has become so enshrined that it is almost an explicit condition of publication now. Your result must be less than 5% likely to happen if there is no real difference. But if you will only publish results that show a p-value of 0.05, then the papers that get published and read will only be the ones that found such p-values—which renders the p-values meaningless.

It was never particularly meaningful anyway; as we Bayesians have been trying to explain since time immemorial, it matters how likely your hypothesis was in the first place. For something like wage gaps where we’re reasonably sure, but maybe could be wrong, the p-value is not too unreasonable. But if the theory is almost certainly true (“does gravity fall off as the inverse square of distance?”), even a high p-value like 0.35 is still supportive, while if the theory is almost certainly false (“are human beings capable of precognition?”—actual study), even a tiny p-value like 0.001 is still basically irrelevant. We really should be using much more sophisticated inference techniques, but those are harder to do, and don’t provide the nice simple threshold of “Is it below 0.05?”

But okay, p-values can be useful in many cases—if they are used correctly and you see all the results. If you have effect X with p-values 0.03, 0.07, 0.01, 0.06, and 0.09, effect X is probably a real thing. If you have effect Y with p-values 0.04, 0.02, 0.29, 0.35, and 0.74, effect Y is probably not a real thing. But I’ve just set it up so that these would be published exactly the same. They each have two published papers with “statistically significant” results. The other papers never get published and therefore never get seen, so we throw away vital information. This is called the file drawer problem.

Researchers often have a lot of flexibility in designing their experiments. If their only goal were to find truth, they would use this flexibility to test a variety of scenarios and publish all the results, so they can be compared holistically. But that isn’t their only goal; they also care about keeping their jobs so they can pay rent and feed their families. And under our current system, the only way to ensure that you can do that is by publishing things, which basically means only including the parts that showed up as statistically significant—otherwise, journals aren’t interested. And so we get huge numbers of papers published that tell us basically nothing, because we set up such strong incentives for researchers to give misleading results.

The saddest part is that this could be easily fixed.

First, reduce the incentives to publish by finding other ways to evaluate the skill of academics—like teaching for goodness’ sake. Working papers are another good approach. Journals already get far more submissions than they know what to do with, and most of these papers will never be read by more than a handful of people. We don’t need more published findings, we need better published findings—so stop incentivizing mere publication and start finding ways to incentivize research quality.

Second, eliminate private for-profit research journals. Science should be done by government agencies and nonprofits, not for-profit corporations. (And yes, I would apply this to pharmaceutical companies as well, which should really be pharmaceutical manufacturers who make cheap drugs based off of academic research and carry small profit margins.) Why? Again, it’s all about incentives. Corporations have no reason to want to find truth and every reason to want to tilt it in their favor.

Third, increase the number of tenured faculty positions. Instead of building so many new grand edifices to please your plutocratic donors, use your (skyrocketing) tuition money to hire more professors so that you can teach more students better. You can find even more funds if you cut the salaries of your administrators and football coaches. Come on, universities; you are the one industry in the world where labor demand and labor supply are the same people a few years later. You have no excuse for not having the smoothest market clearing in the world. You should never have gluts or shortages.

Fourth, require pre-registration of research studies (as some branches of medicine already do). If the study is sound, an optimal rational agent shouldn’t care in the slightest whether it had a positive or negative result, and if our ape brains won’t let us think that way, we need to establish institutions to force it to happen. They shouldn’t even see the effect size and p-value before they make the decision to publish it; all they should care about is that the experiment makes sense and the proper procedure was conducted.
If we did all that, the replication crisis could be almost completely resolved, as the incentives would be realigned to more closely match the genuine search for truth.

Alas, I don’t see universities or governments or research journals having the political will to actually make such changes, which is very sad indeed.