student loans

WSJ’s Editorial Page Blames Obama for Preventing Student Loan Defaults

I wrote that the WSJ’s reporting on student loans had improved slightly. Its editorial responding to the GAO report on the Department of Education’s cost estimate of income-driven repayment plans, on the other hand, backslides. It’s really more of a rant than an editorial, but here’s a digest of what I think it was arguing:

  • Cutting out banks as middle-men for federal student loans costs taxpayers money, even though it didn’t, and that change had nothing to do with IDR plans.
  • Democrats knew that student loans would never be repaid when it federalized student lending. Again, even if true, this claim has nothing to do with IDR plans, which were authorized by prior administrations.
  • IDR plans keep default rates “artificially low,” which while technically accurate doesn’t explain how debtors are supposed to pay loans they can’t repay. What would the WSJ propose if all these people default instead?
  • The Obama administration allowed borrowers to retroactively sign on to IDR plans, which is true but doesn’t explain how debtors would repay the loans otherwise since they probably would not be able to discharge them in bankruptcy.
  • IDR is an “entitlement” that can be “exploited,” even though there’s no evidence student debtors could repay their loans without it. Assuming the GAO’s report is correct, IDR plans are doing exactly what they are supposed to do. The problem is that too many people have too much debt.
  • The Obama administration is responsible for the shoddy accounting of student loans’ ultimate costs—which I’ll accept—but it doesn’t blame lending programs passed by the Bush II administration that created these unpayable debts to begin with. Seriously, the WSJ threw the 2000s down the memory hole.
  • The Obama administration used costly IDR plans to buy votes. No evidence is given, and didn’t younger voters bail on the Democrats in this election? Nice bribe, Obama.
  • Implicitly, the Republican-controlled Congress bears no responsibility for failing to create more jobs or raise incomes, even though it was more concerned with slashing the budget, shutting down the government, and threatening to default on the national debt despite trifling interest rates.

I feel bad for the reporter who carefully tried to explain the GAO’s report and was just upstaged by an incompetent, partisan editorial. (I hope it’s not the same author.)

There’s much blame to place at Obama’s feet regarding the value of college education and student loans. One of these days I’d like to summarize my coverage of him to gauge my fairness towards the outgoing administration. Hopefully, I’ve been consistently non-partisan in my analysis, but perhaps not. However, if the best the WSJ can do is blame Obama for preventing defaults on loans that could not be repaid given the Congresses he had to work with, I’m confident my final assessment will smell like roses by comparison.

WSJ’s Student Loan Coverage Improves: More Facts, Fewer ‘Deadbeats’

And not just facts, neutral facts, which is how reporting is supposed to be. I’ve criticized The Wall Street Journal‘s student loan coverage, but its most recent article on the topic, “U.S. to Forgive at Least $108 Billion in Student Debt in Coming Years,” is a start in the right direction.

Okay, the title could use some work. More accurately, it should be something like: “GAO Projects U.S. Will Forgive $108 Billion in Student Loans in Coming Years.” It’s 76 characters, which is too long for most SEO-obsessed editors, but it doesn’t characterize a possibility as a certainty.

Conversely, the WSJ neglects to cite another GAO study on the subject of student debtors’ earnings. Its data are nearly two years old, but they show that 72 percent of people on income-sensitive repayment plans were earning $20,000 annually or less. Not even 10 percent of IBR and PAYE participants (157,000) made more than $40,000 per year.

Thus, the WSJ’s reasoning still follows a shaky line of reasoning:

(1) IBR participants’ debts are high,

(2) High debts are only feasible for grad students taking out Grad PLUS loans,

(3) Graduates tend to find jobs with high incomes and have low unemployment rates,

(4) So the benefits of IBR go to high-income people.

The prior GAO study pokes holes in (3) and (4). Income is the independent variable, not debt, and incomes are low. Still, the WSJ’s reporting this time inserts enough adverbs to qualify these claims that I’m going to give this an earned “C.” There is no grade inflation on this blog.

Oddly, in its haste to cover the GAO’s attacks on the government’s accounting for student loans, the WSJ neglects to include immanent compensating factors that will raise student debtors’ incomes: tax cuts, stimulus, job growth, a harried Fed, and 3-4 percent growth in the near future. Things will rapidly get better for America’s student debtors.

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.

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.

Office of Management and Budget: +$1.1 Trillion in Direct Loans by 2026

…Which is down from $1.4 trillion by 2025 as predicted last year.

Every year in July the Office of Management and Budget (OMB) publishes its Mid-Session Review of the budget, which includes the Federal Direct Loan Program, and projects its future. The federal government’s direct loans consist primarily of student loans, but there are a few other programs in there. However, federal direct loans do not include private student loans, but these are a small percentage of all student loans. Thus, the OMB’s measure is both over- and under-inclusive of all student debt, but it covers most of it.

The OMB classifies direct loan accounts as financial assets totaling $1.144 trillion in 2015. According to the office’s projections, by 2026 this figure will grow to $2.213 trillion—93 percent.

Projected Direct Loan Balances (OMB, Billions Current $)

(Source: OMB FY2017 Mid-Session Review (pdf))

As with previous years, the current direct loan balance is below the OMB’s past projections. For FY2012, it predicted the balance would be $1.363 trillion by 2015, $219 billion (19 percent) higher than what actually occurred. Even last year, the OMB’s estimate for 2015 was still high by 4 percent. Here are the OMB’s direct loan projections going back to FY2010.

Direct Loan Balance Projections (OMB Billions Current $)

Because the OMB expects GDP to grow as well over this time period (we’d have bigger problems than student loans if it didn’t), the ratio of direct loans to GDP will level off below 8 percent over the next decade.

The OMB’s measure of direct loans is the net amount owed to the government, and the annual changes to that amount are not the same as the amount lent out each year to students. The Department of Education tracks its lending, and I last discussed it here. As of 2015, fewer students were borrowing from the federal government, so lending appears to be declining. The newly implemented gainful employment rule might further reduce student lending as well. These factors may explain why the OMB’s projections keep falling short. Consequently, I don’t believe student debt will exceed $2 trillion.

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.

**

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.