Higher Education

WSJ Has No Idea Who Benefits From IBR/PAYE/REPAYE/ETC

A hypothetical: Jill and Jack live in the same town. Jill has many healthy habits but is a nurse who spends time around infected people, Jack less so. The town is hit with a case of spectrox toxaemia, a dangerous disease. The government offers to immunize people. Jill decides to be immunized; Jack does not. Jill does not get sick; Jack does. So, epidemiologists, did Jill not contract spectrox toxaemia because she was immunized or because of her healthy habits (or luck)?

If you’re The Wall Street Journal, the answer is her habits. Most of us would believe otherwise, given how dangerous spectrox toxaemia is and Jill’s contact with its victims.

Likewise, this line of reasoning animates the WSJ’s opinion of the government’s income-sensitive repayment programs for student debtors, which it claims benefit higher-debt people with better credit scores than lower-debt people who don’t. It’s unintuitive, if you’re the WSJ apparently, but it makes more sense to those of us familiar with the student debt system.

Here’s how it works: People who take out lots of debt might not in fact have the incomes to repay them, so they choose an income-sensitive repayment because the alternative is … Default! Thus, looking at how much they borrow is less important than looking at how much they’re paid.

Last year, in fact, the Government Accountability Office explored this topic and found that most people in income-sensitive repayment programs were earning less than $20,000 annually. So the Jills aren’t so different from the Jacks after all.

Sure, if there were no IBRs/PAYEs/REPAYEs/ETCs, then these Jills with good borrowing habits would be more likely to take deferments and forbearances, but their debts would still not be repaid. That’s because debts that can’t be repaid will not be repaid, no matter what someone’s credit score or how much they borrowed. What matters is what they earn, and college graduates don’t earn much these days.

And if you think the Jills have too much debt, then the problem isn’t IBR/ICR/REPAYE/ETC, it’s that the government lends too much money to people for degrees they don’t need.

High School Grads Get a Big Raise, College Grads? Not So Much

Last week, the Census Bureau published the 2015 edition of its Income, Poverty, and Health Insurance tables. This information is my favorite source for understanding the value of higher education: More young people are getting college credentials, but their aggregate income isn’t rising much, which means they’re not much better off.

aggregate-personal-earnings-by-education-25-34-both-sexes

Indeed, in the mean-average year since 1991, people who didn’t start high school have received bigger raises than any other category. College graduates barely do better than high school grads. Meanwhile, many more people have gone to college and fewer just stop at high school.

earnings-growth-rates-by-education-for-25-34-year-olds-1991

As for 2015, the high-schoolers got a much bigger raise than the college grads.

percent-change-in-earnings-by-education-25-34-year-olds

(The data are highly erratic, but it’s still fun to do the horse-racing.)

That’s all, folks.

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Past coverage:

Council of Economic Advisors: College Pays. Grad School? Sh!

Or, “The Reality Behind AEI’s Reality Behind the Student Debt ‘Crisis'”

Speaking of student loans, I am directed to the American Enterprise Institute’s response to the Council of Economic Advisor’s (CEA’s), “Investing in Higher Education: Benefits, Challenges, and the State of Student Debt” (pdf).

Because I try to deliver early on my post titles rather than bury them, here’s the report’s chart on the crucial but under-emphasized dispersion of earnings by educational attainment for 35-44 year-olds with payroll incomes. (This cohort doesn’t seem so representative to me of recent student borrowers—and not in a good way, but that’s a different issue.)

CEA--State of Student Loans--Figure 5

Eyeballing the chart, more than a quarter of graduate-degree holders earn less than the median 4-year-degree holder in the same age bracket, and the bottom 25 percent of grads earn about $45,000 or less. The B.A.s earn between about $20,000 and $130,000 while the grads make roughly between $30,000 and $170,000. Graduates in between the 75th and 90th percentiles haul in nearly half the total difference. This wide dispersion cries for more analysis because graduate borrowing amplifies student debt loads. High debts and low incomes, even for this small group of debtors, tend to discredit the human capital hypothesis and the purpose of student lending.

But back to the reality behind the reality behind the- etc.

Critical readers should always be on their guards whenever someone characterizes the “student debt crisis.” Frequently it’s a strawman of the crisis writers want to discuss rather than how much of the unpayable debt will be written down in the future. In the AEI’s case, the crisis is, “[T]he macroeconomic impact of high debt levels.” Here, AEI takes this to mean the stock of $1.3 trillion of debt.

The AEI post turns to its education scholars, startlingly Jason Delisle, who perhaps has moved on from the New America Foundation. Delisle focuses first on the claim that “student debt is holding back the economy.” The CEA report attempts to discredit this position in six ways. One, student debt is not as big as the mortgage bubble (which I don’t think I’ve seen anyone argue for a few years now). Two, hardship today will be offset by the future productivity unleashed by education. Three, everyone borrowed student loans when the opportunity costs were lowest, so high debt levels are in step with the economy and not undermining it. Four, student debt is only slightly reducing homeownership among young people. Five, student loans only reduce auto debt for high-balance debtors. Six, student-loan debts reduce small-business formation and their incomes somewhat, but other factors are involved.

The study concludes, “Had the same students received an education without as many loans, the recovery would likely have been stronger, but not substantially so. Most individuals, and the economy as a whole, will benefit from the education made possible by student loans” (56).

In other words, the Obama administration is asking everyone to double down on its hope that all this education will pay off someday and the government won’t have to write down hundreds of billions of dollars in unpayable education debt, whether by forgiveness promises in repayment plans or new legislation. It’s a theme that crops up elsewhere in the report, and it suffers from two problems. One, higher education doesn’t correspond to higher aggregate incomes; rather it seems to be swapping high-school grads with college grads while keeping incomes flat. If college boosts incomes like video-game power-ups, then we’d expect exponential growth in aggregate incomes, but we’re not. And anyone who thinks the payoff will come later must explain why intervening variables aren’t involved, e.g. occupational differences, which would explain the wider earnings dispersions for the credentialed. The CEA gives us no confidence in its education bet.

Problem number two is that the report tends to side against studies produced by the Federal Reserve Bank of New York (especially those by Meta Brown, et al.) in favor of research producing more satisfying results. The impacts might be trivial, but the NY Fed found that youngish student debtors weren’t getting mortgages or were more likely to live with their parents than the unindebted (links buried here). Meanwhile, the report shoos away the Bennett hypothesis by claiming a lack of consensus, with the caveat that there may be some “administrative bloat” in colleges and universities. Consensuses are tough rhetorical animals to wrestle with and should require significant evidence to prove. A few studies here and there will not do it.

So back to AEI. When Delisle writes, “[Advocacy groups] say student debt is forcing people to delay things like buying a house, starting a family, all productive things. This report is pretty clear that isn’t the case,” he’s wrong. The report clearly concedes that student debt is negatively affecting the economy, albeit to a small degree, and thanks in part to wishing away contrary NY Fed studies and insisting that all the education will pay off someday.

To clarify, student debt is a notable if not primary contributor to a generational disaster dominated by the trade deficit or slack aggregate demand—and new student borrowing is declining—but the CEA report isn’t the source to show it. So that’s a strike against Delisle.

He asks:

Why are millions of borrowers flocking to enroll in a program [IBR, PAYE, REPAYE, etc.] that allows them to cap their student loan payments at a small share of their income if the return on an educational investment are large? Something seems amiss there. I’ve done a lot of work showing that the income-based repayment program is too generous as a result of Obama administration changes, which may explain this disconnect.

I’ve answered the first question already: There is no large, aggregate return to higher education. As to Delisle’s work on the changes to IBR, it’s never demonstrated that the programs are too generous because it’s based on lopsided, self-verifying hypotheticals. In fact, according to a GAO study, in 2014 only 2 percent of debtors in IBR or PAYE plans earned more than $80,000, so Delisle’s mythical IBR deadbeat is not a serious policy concern. Amusingly, Delisle’s reaction to the GAO study at the time was to blame debtors for not making enough money, gasping that they’d use IBR plans for long-term rather than short-term debt relief.

AEI then turns to resident scholar Andrew Kelly, who writes, “Lower interest rates [proposed by Democrats] won’t help folks with small balances who aren’t repaying nearly as much as they’ll help those with average or large balances, most of whom have no trouble repaying because they have the highest educational attainment!”

I have problems with the Warrenian interest-rate proposals too, but Kelly makes the frequent mistake of flipping the income and debt variables to conclude that high-balance debtors are deadbeats, even though the CEA report shows a wide income dispersion for graduate-degree holders.

I admit I didn’t give the CEA report a thorough read, but it looks like the AEI scholars didn’t either.

CBO: $1.2 Trillion in New Federal Student Loans by 2026

Each year the Congressional Budget Office (CBO) provides its baseline projections for the federal student-loan program. The projections include the total amount of new federal student loans that the office believes will be issued, future interest rates, and subsidy costs, i.e. whether the government will make or lose money on the loans. This year, the CBO projects that the government will lend an additional $1.2 trillion to students between FY2016 and FY2026. The figure is down slightly since the 2014-2024 period, discussed here.

Subsidy Rates

The CBO uses an accrual-accounting methodology to determine the present value of federal loans. This essentially means discounting the estimated cash flows of student loans against government securities with the same maturities. If student loans make more money than buying government debt would, then the loans are valuable. Accrual accounting does not include the market risk that a private lender would consider when making a student loan, which is why many people advocate fair-value accounting. It’s a surprisingly contentious issue, which I elaborate in the student debt data page, because under fair-value accounting, the government loses money on student loans.

Under accrual accounting, the CBO projects negative subsidy rates for federal student loans; that is, it sees the government making money on its lending. All student loans made in 2015 will make an estimated 13.9 percent return. Of interest to law-school watchers: Unsubsidized Stafford loans and Grad PLUS loans issued in FY2016 will make 19.2 percent and 18.9 percent returns, respectively. Oddly, Parent PLUS loans appear to be the most profitable for the government.

CBO Table 2This year, however, the CBO included fair-value estimates of federal student loans. Under these, the government loses about 12 percent of its investment on student loans every year until FY2026. Unsubsidized Stafford loans and Grad PLUS loans lose about 5 percent in 2016, but the losses increase over the decade. Parent PLUS loans remain profitable.

Note also that the CBO believes the net number of loans will rise during the decade. It’s already evident that federal-student-loan borrowing is declining.

CBO Table 6Under accrual accounting the student loans will net the government $85.2 billion; under fair-value accounting the government will lose $145.1 billion. This isn’t a lot of money for the government, actually, but it could obviously be redirected to better uses.

Interest Rates

A crucial variable affecting subsidy rates, for both accounting methodologies, is the CBO’s projection of future interest rates. Two years ago, the office believed interest rates would rise from less than 2 percent in 2013 to 5 percent in 2018. This year, the CBO estimates that interest rates will rise to only 3.4 percent in 2018 and 4.14 percent starting in 2022.

CBO Table 4I believe the current interest-rate predictions are more plausible than the office’s estimates two years ago. The interest rate on 10-year government bonds has been falling this year, so the CBO may be overly pessimistic again for FY2016.

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In all, I think the CBO is overly pessimistic with these assumptions. Student borrowing is declining, and there isn’t much of a reason to believe interest rates will rise. This doesn’t mean the government won’t make bad loans, or that the skills and knowledge they pay for will make the workforce more productive, but it’ll probably be less than $145.1 billion.

Robots Won’t Take Your Profs’ Jobs

I’m going to weave a few themes together for you today; it’ll make sense by the end.

We begin with a friend’s comment last week about robots taking everyone’s jobs. I called him on the lump-of-labor fallacy—there isn’t a fixed amount of work to be done in an economy and therefore technology only creates jobs. You can argue the fallacy as much as you like, but don’t talk about robots taking our jobs until you’re aware of it.

I wrote about robots in the past, when Paul Krugman popularized it in December 2012. I’ve revisited it and found an interesting exchange between Sandwichman and Nick Rowe that I missed last year.

To summarize: Sandwichman argued that the lump-of-labor fallacy is really Say’s Law in disguise. Say’s Law is to me a confusing, contentious tautology that evades a concise rendition. My crack? An economy’s production supplies it with sufficient purchasing power to consume that production. Thus, under normal circumstances there can be no general surpluses, including labor. Keyensians, including Krugman, reject the strict use of Say’s Law but for some reason still point at the lump-of-labor fallacy.

Rowe countered that technology’s impact depends on people’s preferences and money. People can simply consume more of what they make, or the central bank needs to give them more money to increase their consumption. I didn’t like some parts of Rowe’s model, but his last, parenthetical paragraph closes the issue perfectly: Technology is only a problem if it displaces workers from land.

I’m starting to think that maybe just about all productivity advances substitute for land and not labor, which is good. The converse is rare, e.g. Dutch disease scenarios where technology makes it easier and more profitable to extract oil than pay workers to make stuff. The workers don’t get the benefits, unlike the landowners, and they can’t leave the country. The land question precedes and supersedes any discussion of technology.

Theme number two is “cost disease,” the explanation of higher college tuition costs on lack of productivity improvements in lecturing. The illustration for cost disease is a string quartet, which takes the same quantity of labor to produce as ever. Cost disease came up twice in the legal-education context in the last few weeks. Once by a dean claiming that scambloggers ignore it, and again by a study pointing at federal student lending as the fuel for higher college tuition, aka the Bennett hypothesis.

I chewed on these two ideas while at … the Saint Paul Chamber Orchestra, which was performing Aaron Copeland’s Appalachian Spring with some other stuff for padding. It was a real treat, and right at the finale of Mozart’s Piano Concerto No. 24 in C minor*, it all came together. It was a really rewarding feeling.

(* Mozart only composed one other piece in a minor key. I have absolutely no ear to tell keys, but it was lovely.)

So, what does last year’s lump-of-labor discussion tell us about cost disease?

We can set up a model just as Rowe did for Sandwichman, but instead of labor hours, as a good Georgist I’ll use land. 60 people live and work on 60 hectares; 30 grow apples and 30 grow bananas, one each of everything. (Numbers divisible by 12 are always good.) Nobody wants their own type of product, so they trade for the other. Someone stumbles on an apple-growing process that doubles productivity. One of three things happens:

(a) The apple growers each double their output, leaving the bananas constant. 30 hectares grows 60 apples, 30 hectares grows 30 bananas. The ratio of apples to bananas doubles to 2:1, but bananas’ share of the output has fallen to one third. The apple growers really want those bananas.

(b) Banana growers really want their apples, so 20 apple growers double their output, but 10 apple growers switch to banana cultivation. 20 hectares creates 40 apples, and 40 hectares creates 40 bananas. This situation creates an equilibrium for the ratio of apples to bananas, 1:1.

(c) Same as (b), but the 10 hectares shifted to banana production go to a third commodity. This situation is essentially identical to (a), since bananas are what we care about.

Cost disease says that higher education is like situation (a) (and (c)). Productivity “enables” people to satisfy their preferences for the same stuff when we want it to increase their purchasing power to demand new stuff. Here, the more productivity increases, the more income goes to the unproductive.

Now for the twist: If banana-production technology never improves, and people’s appetite for bananas doesn’t wane, we can say that the supply of bananas is inelastic—insensitive to changes in price. But that’s exactly what proponents of the Bennett hypothesis argue: Higher education is a positional good, so educators absorb money lent to students to buy it.

So what’s the difference between the Bennett hypothesis and cost disease? Formally, they’re the same, so the policy responses should be the same: Lending money to people to buy educations that don’t respond to price changes is no different than increasing their productivity, ergo don’t lend the money. Just as Sandwichman argued that Say’s Law is the lump-of-labor fallacy, so too is the cost disease really the Bennett hypothesis.

The function of cost disease, though, I think is different. It’s raised to neutralize the positional-goods argument implied by the Bennett hypothesis. It’s not that education is a rate race, they argue; rather, it’s that we can’t make the rat race better.

If that sounds like a non sequitur, it’s because it is, but with logic like that we needn’t worry about robots replacing the profs.

NY Fed: Student Debt Delinquencies Still High in 2015

What started in 2012 just isn’t stopping. According to the Federal Reserve Bank of New York’s Housing Debt and Credit Report, the percent of student-loan balances that are 90+ days delinquent was about 11.5 percent at the end of 2015, about where it was a year ago. Delinquencies for all other household debts save credit-card debt fell last year:

Student-Loan Delinquencies (2015)

This year, the NY Fed declined to discuss all those bad student loans, unlike last year.

Between fourth quarter 2014 and and the end of 2015, all non-housing debt grew from $3.15 trillion to $3.37 trillion. Student-loan debt accounted for 31 percent of the $220 billion increase.

Meanwhile, looking through Department of Education data, only 51.74 percent of all $1.204 trillion in federal student loans are in active repayment. 21 percent are in deferment or forbearance, and 9.5 percent are in default. Of the $585.8 billion of direct loans in repayment, forbearance, or deferment, $188.2 billion are on IBR or PAYE. Nearly one-third of all direct loans in repayment are in one of these plans, about 15.6 percent of all student loans.

This just doesn’t end. Until it will.

Anthony Carnevale Has Two Years to Reemploy 15.8 Million College Grads

Two years ago I made fun of President Obama’s ludicrous claim that “more than 60 percent of jobs in the next decade will require more than a high school diploma.” It appeared Obama appropriated the statistic from Anthony P. Carnevale’s paper for the Georgetown Center for Education and the Workforce (GCEW), entitled, “Help Wanted: Projections of Jobs and Education Requirements Through 2018.” It shrieks on page 22 that 63 percent of jobs created by 2018 would require a college education: 33 percent bachelor’s degrees, and 30 percent associate’s degrees or just some college.

As I wrote in January 2014, Carnevale and his colleagues reasoned that the BLS was holding occupational credential requirements constant when they should drift with times. As non-college jobs go increasingly to college-educated workers, we should consider those jobs as requiring college education.

If you’re scratching your head wondering if Carnevale is rationalizing credential inflation, then you have no hope of employment in a D.C. think tank. (Maybe you didn’t go to college?) In the fourth appendix, the authors merely counter-argue, “BLS’ educational and training requirement data undercount postsecondary degrees by 22 million in 2008. This implies that 22 million workers are overeducated. The overwhelming consensus in the literature contradicts this.”

Thanks to the most recent publication of the BLS’s employment projections (tables 1.7 and 1.11), I get 15.8 million people with a bachelor’s degree or higher in jobs requiring a high-school education or less. On the bright side, that’s down 100,000 jobs from two years ago. That backlog won’t clear until the mid-22nd century.

It’s true that occupations can change and benefit from productivity advances, and many occupations do not require a single credential to enter them. However, the question GCEW should be asking is what jobs overqualified workers are taking. The answer isn’t too compelling.

Percent BA's in HS & Less Jobs

These twenty occupations account for half of the 12.9 million bachelor’s-degree holders working in high school or less jobs. These occupations dominate among master’s-degree and doctorate holders as well. Maybe some of these folks over 25 are in these jobs temporarily (they’d have to be for many), but at that age it’s pretty implausible that they’re on track for college-premium-magic careers.

Overall, 19.3 million college-and-higher people are qualified or underqualified for their work, and 27.4 million workers are at least somewhat overqualified, which includes PhDs working in bachelor’s jobs.

In contrast to the GCEW’s forecast, the BLS essentially says that 27.7 percent of the jobs to be created by growth and replacement over the next decade will require an associate’s degree or higher. (BA’s are at 20.5 percent.) High-school and less will account for 64.2 percent. Of the 46.5 million jobs that will be created, here’s a table of the top twenty, accounting for 16 million jobs.

OCCUPATION EDUCATION REQUIRED NO. EMPLOYED (2014) (1,000s) NO. EMPLOYED (2024) (1,000s) NEW JOBS (GROWTH + REPLACEMENT) (1,000s)
TOTAL 150,539.9 160,328.8 46,506.9
Retail salespersons No formal educational credential 4,624.9 4,939.1 1,917.2
Cashiers No formal educational credential 3,424.2 3,491.1 1,523.8
Combined food preparation and serving workers, including fast food No formal educational credential 3,159.7 3,503.2 1,364.6
Waiters and waitresses No formal educational credential 2,465.1 2,534.0 1,255.0
Registered nurses Bachelor’s degree 2,751.0 3,190.3 1,088.4
Customer service representatives High school diploma or equivalent 2,581.8 2,834.8 888.7
Laborers and freight, stock, and material movers, hand No formal educational credential 2,441.3 2,566.4 851.7
Office clerks, general High school diploma or equivalent 3,062.5 3,158.2 756.2
Stock clerks and order fillers No formal educational credential 1,878.1 1,971.1 689.0
General and operations managers Bachelor’s degree 2,124.1 2,275.2 688.8
Janitors and cleaners, except maids and housekeeping cleaners No formal educational credential 2,360.6 2,496.9 605.2
Personal care aides No formal educational credential 1,768.4 2,226.5 601.1
Nursing assistants Postsecondary nondegree award 1,492.1 1,754.1 599.0
Home health aides No formal educational credential 913.5 1,261.9 554.8
Accountants and auditors Bachelor’s degree 1,332.7 1,475.1 498.0
Maids and housekeeping cleaners No formal educational credential 1,457.7 1,569.4 459.4
Cooks, restaurant No formal educational credential 1,109.7 1,268.7 452.5
Maintenance and repair workers, general High school diploma or equivalent 1,374.7 1,458.1 443.7
Childcare workers High school diploma or equivalent 1,260.6 1,329.9 441.3
First-line supervisors of retail sales workers High school diploma or equivalent 1,537.8 1,605.4 411.3

Most of these jobs don’t look like they benefit from more education, but hey, maybe Carnevale will reemploy all 15.8 million college grads into jobs that fully utilize their credentials. He only has two years to make it happen.