Author: James Bailey

You Read It Here First

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The subjects of two of our posts from 2023 are suddenly big stories.

First, here’s how I summed up New Orleans’ recovery from hurricane Katrina then:

Large institutions (university medical centers, the VA, the airport, museums, major hotels) have been driving this phase of the recovery. The neighborhoods are also recovering, but more slowly, particularly small business. Population is still well below 2005 levels. I generally think inequality has been overrated in national discussions of the last 15 years relative to concerns about poverty and overall prosperity, but even to me New Orleans is a strikingly unequal city; there’s so much wealth alongside so many people seeming to get very little benefit from it. The most persistent problems are the ones that remain from before Katrina: the roads, the schools, and the crime; taken together, the dysfunctional public sector.

The New York Times had a similar take yesterday:

Today, New Orleans is smaller, poorer and more unequal than before the storm. It hasn’t rebuilt a durable middle class, and lacks basic services and a major economic engine outside of its storied tourism industry…. New Orleans now ranks as the most income-unequal major city in America…. In areas that attracted investment — the French Quarter, the Bywater and the shiny biomedical corridor — there are few outward signs of the hurricane’s impact. But travel to places like Pontchartrain Park, Milneburg and New Orleans East that were once home to a vibrant Black middle class, and there are abandoned homes and broken streets — entire communities that never regained their pre-Katrina luster…. Meanwhile, basic city functions remain unreliable.

I wrote in 2023 about a then-new Philadelphia Fed working paper claiming that mortgage fraud is widespread:

The fraud is that investors are buying properties to flip or rent out, but claim they are buying them to live there in order to get cheaper mortgages…. One third of all investors is a lot of fraud!… such widespread fraud is concerning, and I hope lenders (especially the subsidized GSEs) find a way to crack down on it…. This mortgage fraud paper seems like a bombshell to me and I’m surprised it seems to have received no media attention; journalists take note. For everyone else, I suppose you read obscure econ blogs precisely to find out about the things that haven’t yet made the papers.

Well, that paper has now got its fair share of attention from the media and the GSEs. Bill Pulte, director of the Federal Housing Finance Agency and chairman of Fannie Mae and Freddie Mac, has been going after Biden-appointed Federal Reserve Governor Lisa Cook over allegations that she mis-stated her primary residence on a mortgage application:

Pulte has written many dozens of tweets about this, at least one of which cited the Philly Fed paper:

Now President Trump is trying to fire Cook. Federal Reserve Governors can only be fired “for cause” and none ever have been, but Trump is using this alleged mortgage fraud to try to make Cook the first.

The Trump administration seems to have made the same realization as Xi Jinping did back in 2012– that when corruption is sufficiently widespread, some of your political opponents have likely engaged in it and so can be legally targeted in an anti-corruption crackdown (while corruption by your friends is overlooked).

I’m one of a few people hoping for the Fed to be run the most competent technocrats with a minimum of political interference:

But I’m not expecting it.

Remember, you read it here first.

The Little Book of Active Investing

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Wiley publishes a series of short books on investing called “Little Books, Big Profits“.

I previously reviewed Vanguard founder John Bogle’s entry in this series, the Little Book of Common Sense Investing:

I can sum it up at much less than book length: the best investment advice for almost everyone is to buy and hold a diversified, low-fee fund that tracks an index like the S&P 500.

You could call Bogle’s book the Little Book of Passive Investing; but most of the rest of the series could be the Little Books of Active Investing. That is certainly the case for Joel Greenblatt’s entry, The Little Book that Beats the Market (or its 2010 update, The Little Book that Still Beats the Market).

Greenblatt offers his own twist on value investing that emphasizes just two value metrics- earnings yield (basically P/E) and return on capital (return on assets). The idea is to blend them, finding the cheapest of the high-quality companies. The specific formula is to pick stocks with a return on assets of at least 25%, then select the ~30 stocks with the lowest P/E ratio among those (excluding utilities, financials, and foreign stocks), then hold them for a year before repeating the process. He shows that this idea performed very well from 1988 to 2010.

How has it done since? He still maintains the website, https://www.magicformulainvesting.com, that gives updated stock screens to implement his formula, which is nice. But the site doesn’t offer updated performance data, and his company (Gotham Capital) offers no ETF to implement the book’s strategy for you despite offering 3 other ETFs, which suggests that Greenblatt has lost confidence in the strategy. Here are the top current top stocks according to his site (using the default minimum market cap):

Perhaps this is worthwhile as an initial screen, but I wouldn’t simply buy these stocks even if you trust Greenblatt’s book. When I started looking them up, I found the very first two stocks I checked had negative GAAP earnings over the past year, meaning Greenblatt’s formula wouldn’t be picking them if it used correct data. The site does at least have a good disclaimer:

“Magic Formula” is a term used to describe the investment strategy explained in The Little Book That Beats the Market. There is nothing “magical” about the formula, and the use of the formula does not guarantee performance or investment success.

Greenblatt’s Little Book is a quick and easy way to learn a bit about value investing, but I think Bogle’s Little Book has the better advice.

Why I Started Grading Attendance

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I’ve taught college classes since 2010, but I never graded attendance directly until this year. I thought that students are adults who can make their own choices about where to spend their time, and if they could do well on my tests and assignments without spending much time in class, more power to them.

But I got tired of seeing students miss a lot of class, then fail by getting poor grades on the tests and assignments, or scramble for the last few weeks to avoid failing. Explaining the importance of attendance didn’t seem to help, so I finally turned to the economist’s solution- incentives. This Spring I tried grading attendance in one class, and this successful experiment plus the growth of AI mean I plan to grade attendance in all classes from now on.

The Benefits:

  • Get to know student’s names faster
  • Students feel rewarded for showing up
  • Students show up more, bringing more energy to the room
  • Students show up more, so they learn more and do better on other assignments
  • Physically showing up is one thing I can be sure the AI isn’t doing for them, it will be a while before humanoid robots are that good

The Costs That Turned Out Not to Be Big Deals

  • I thought students would dislike me policing their whereabouts and give me lower course evaluations (which is part of why I waited for tenure to try this). But my Spring evals were at least as high as usual, with none mentioning the attendance policy. When I asked students in a different class about this, most said they wished I would grade attendance if it meant less weight on exams.
  • I thought tracking attendance would be burdensome, but it turns out my main course software (Canvas) already has an attendance-tracking tool built in that lets you just click on names in a seating chart each day and enters grades automatically. It is certainly less burdensome than grading most assignments.

I still had some students disappear for a while due to personal issues; sometimes even the strongest grade incentives aren’t enough to get people to class. But overall I can’t believe I waited this long. I’m currently putting attendance as 10-15% of the course grade, but I dream about someday running a discussion-based class like a Liberty Fund seminar, doing a 100% attendance/participation grade, and not having to grade anything.

Parental Job Lock

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The Affordable Care Act was supposed to make it easier for American workers to switch jobs by making it easier to get health insurance from sources other than their current employer. Mostly it didn’t work out that way. But a new paper finds that one piece of the ACA actually made people less likely to switch jobs.

The ACA Dependent Coverage Mandate required family health insurance plans to cover young adults though age 26, when prior to the 2010 passage of the ACA many had to leave the family plan at age 18 or 19. I thought these newly covered young adults would be more likely to switch jobs or start businesses, but there turned out to be absolutely no effect on job switching, and no overall increase in businesses (though it did seem to increase the number of disabled young adults starting businesses, and other parts of the ACA increased business formation among older adults).

But while the Dependent Coverage mandate seems not to have reduced job lock for young adults, it increased job lock among their parents. That is the finding of a new paper in the Journal of Public Economics by Hannah Bae, Katherine Mackel, and Maggie Shi. Using a large dataset with exact months of age and coverage, MarketScan, allows them to estimate precise effects:

We find that dependents just to the right of the December 1985/January 1986 cutoff—those eligible for longer coverage—are more likely to enroll and remain covered for longer once the mandate is in effect. Dependent enrollment increases by 1.8 percentage points at the cutoff, an increase of 9.2 % over the enrollment rate for dependents born in December 1985. In addition, the enrollment duration increases by 9.7 days (14.6 %). Turning to their parents, we find that parental job retention likelihood increases by 1.0 percentage point (1.8 %) and job duration increases by 5.8 days (1.6 %) to the right of the cutoff. When scaled by the estimated share of dependents on end of year plans, our findings imply that 12 additional months of dependent coverage correspond to a 7.7 % increase in job retention likelihood and a 7.0 % increase in retention duration.

Source: Figure 2 of Bae, Mackel and Shi 2025

I believe in this parental job lock effect partly because of their data and econometric analysis, and partly through introspection. I plan to work for years after I have the money to retire myself in order to keep benefits for my kids, though personally I’m more interested in tuition remission than health insurance.

On top of working longer though, benefits like these enable employers to pay parents lower money wages. A 2022 Labour Economics paper from Seonghoon Kim and Kanghyock Koh found that the Dependent Coverage Mandate “reduced parents’ annual wages by about $2600 without significant reductions in the probability of employment and working hours.” But at least their kids are better off for it.

Is A Music Major Worth It?

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Our new paper concludes that the answer is a resounding “It Depends”.

It depends on your answer to the following questions:

  1. If you didn’t major in music, would you major in something else, or not finish college?
  2. How dead set are you on a career in music?
Source: Figure 1 of Bailey and Smith (2025)

We found that

  1. Music majors earn more than people who didn’t graduate from college, even if they don’t end up working as musicians
  2. Among musicians, music majors earn more than other majors
  3. But among non-musicians, other majors earn much more than music majors

So on average a music major means higher income if you would be a musician anyway, or if you wouldn’t have gone to college for another major, but lower income than if you majored in something else and worked outside of music. The exact amounts depend on what you control for; this gets complex but this table gives the basic averages before controls:

Source: Table 2 of Bailey and Smith (2025), showing wage plus business income for respondents to the 2018-2022 American Community Survey

For better or worse, a music major also means you are much more likely to be a musician- 113 times more likely, in fact (this is just the correlation, we’re not randomizing people into the major). Despite that incredible correlation, only 9.8% music majors report being professional musicians, and only 22.3% of working musicians were music majors.

Sean Smith had the idea for this paper and wrote the first draft in my Economics Senior Capstone class in 2024. After he graduated I joined the paper as a coauthor to get it ready for journals, and it was accepted at SN Social Sciences last week. We share the data and code for the paper here.

Continue reading →

Freedom for Freestanding Birth Centers

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Iowa recently joined the growing list of states where midwives or obstetricians can open a freestanding birth center without needing to convince a state board that it is economically necessary. The Des Moines Register provides an excellent summary:

A Des Moines midwife who sued the state for permission to open a new birthing center may have lost a battle in court, but ultimately, she has won the war.

Caitlin Hainley of the Des Moines Midwife Collective sought to open a standalone birthing center in Des Moines, essentially a single-family home repurposed with birthing tubs and other equipment needed to give birth in a comfortable, home-like environment.

To do so, the collective alleged in its 2023 lawsuit, would have required going through a lengthy, expensive regulatory process that would give already established maternity facilities, such as local hospitals, the chance to argue against granting what is known as a certificate of need for the new facility, essentially vetoing competition.

A federal district judge ruled in November that Iowa’s certificate-of-need law is constitutional, finding that legislators had a rational interest in protecting existing hospitals and health care providers.

But while losing the first round in court, the collective’s cause was winning support in a more important venue: the Iowa Capitol. Iowa legislators in their 2025 session passed a bill, which Gov. Kim Reynolds signed on May 1, removing birth centers from the definition of health facilities covered by the certificate-of-need law. The law will formally take effect July 1.

I’m honored to have played a small part in this as the expert witness in the lawsuit.

If you’d like to get involved in making sure birth options are available your state, a great place to start would be to attend the Zoom seminar Roadmap For Reform: Advancing Birth Freedom on July 23rd. It is hosted by the Pacific Legal Foundation, which represented the midwives pro-bono in the Iowa case.

There is strong momentum here with Connecticut, Kentucky, Michigan, Vermont, and West Virginia also recently repealing Certificate of Need requirements for birth centers, but a variety of other barriers remain. States often require freestanding birth centers to obtain a transfer agreement with a nearby hospital before opening to ensure that the hospital will take their emergency cases, even though hospitals are legally required to take all emergency cases. The problem is that hospitals provide both complementary services (emergency care) and substitute services (labor and delivery), and they often choose not to sign transfer agreements in order to prevent competition from a partial substitute. This whole area would benefit both from more academic study, as well as more investigation from antitrust enforcement.

But for today, congratulations to Caitlin Hainley and to Iowa on their victory.

Writing Humanity’s Last Exam

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When every frontier AI model can pass your tests, how do you figure out which model is best? You write a harder test.

That was the idea behind Humanity’s Last Exam, an effort by Scale AI and the Center for AI Safety to develop a large database of PhD-level questions that the best AI models still get wrong.

The effort has proven popular- the paper summarizing it has already been cited 91 times since its release on March 31st, and the main AI labs have been testing their new models on the exam. xAI announced today that its new Grok 4 model has the highest score yet on the exam, 44.4%.

Current leaderboard on the Humanity’s Last Exam site, not yet showing Grok 4

The process of creating the dataset is a fascinating example of a distributed academic mega-project, something that is becoming a trend that has also been important in efforts to replicate previous research. The organizers of Humanity’s Last Exam let anyone submit a question for their dataset, offering co-authorship to anyone whose question they accepted, and cash prizes to those who had the best questions accepted. In the end they wound up with just over 1000 coauthors on the paper (including yours truly as one very minor contributor), and gave out $500,000 to contributors of the very best questions (not me), which seemed incredibly generous until Scale AI sold a 49% stake in their company to Meta for $14.8 billion in June.

Source: Figure 4 of the paper

Here’s what I learned in the process of trying to stump the AIs and get questions accepted into this dataset:

  1. The AIs were harder than I expected to stump because they used frontier models rather than the free-tier models I was used to using on my own. If you think AI can’t answer your question, try a newer model
  2. It was common for me to try a question that several models would get wrong, but at least one would still get right. For me this was annoying because questions could only be accepted if every model got them wrong. But of course if you want to get a correct answer, this means trying more models is good, even if they are all in the same tier. If you can’t tell what a correct answer looks like and your question is important, make sure to try several models and see if they give different answers
  3. Top models are now quite good at interpreting regression results, even when you try to give them unusually tricky tables
  4. AI still has weird weaknesses and blind spots; it can outperform PhDs in the relevant field on one question, then do worse than 3rd graders on the next. This exam specifically wanted PhD-level questions, where a typical undergrad not only couldn’t answer the question, but probably couldn’t even understand what was being asked. But it specifically excluded “simple trick questions”, “straightforward calculation/computation questions”, and questions “easily answerable by everyday people”, even if all the AIs got them wrong. My son had the idea to ask them to calculate hyperfactorials; we found some relatively low numbers that stumped all the AI models, but the human judges ruled that our question was too simple to count. On a question I did get accepted, I included an explanation for the human judges of why I thought it wasn’t too simple.

I found this to be a great opportunity to observe the strengths and weaknesses of frontier models, and to get my name on an important paper. While the AI field is being driven primarily by the people with the chops to code frontier models, economists still have lot we can contribute here, as Joy has shown. Any economist looking for the next way to contribute here should check out Anthropic’s new Economic Futures Program.

The Ugly Gray Rhino Gathers Speed

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A black swan is a crisis that comes out of nowhere. A gray rhino, by contrast, is a problem we have known about for a long time, but can’t or won’t stop, that will at some point crash into a full-blown crisis.

The US national debt is a classic gray rhino. The problem has slowly been getting worse for 25 years, but the crisis still seems far enough off that almost no one wants to incur real costs today to solve the problem. During the 2007-2009 financial crisis and the 2020-2021 Covid pandemic we had good reasons to run deficits. But we’ve ignored the Keynesian solution of paying back the deficits incurred in bad times with surpluses in good times.

We are currently in reasonably good economic times, but about to pass a mega-spending bill that blows the deficit up from its already-too-high-levels. At a time when we should be running a surplus, we are instead running a deficit around 6% of GDP:

Source: Congressional Budget Office

Our ‘primary deficit’ is lower, a more manageable 3% of GDP. But if interest rates go higher, either for structural reasons or because of a loss of confidence in the US government’s willingness to pay its debts, the total deficit could spiral higher rapidly. The CBO optimistically assumed that the interest rate on 10-year treasuries will fall below 4% in the 2030s, from 4.3% today:

Source: Congressional Budget Office

But their scoring of H.R. 1 (“One Big Beautiful Bill Act”) shows it adding $3 trillion to the debt over the next 10 years, increasing the deficit by ~1% of GDP per year.

I already suspected this gray rhino would eventually cause a crisis, but this bill and the milieu that produced turn it into a near guarantee- nothing stops the deficit train until we hit a full blown crisis. That crisis is no longer just a long-term issue for your kids and grandkids to worry about- you will see it in 7 years or so. Unfortunately, that is still far enough away that current politicians have no incentive to take costly steps to avoid it. In fact, deficits will probably make the economy stronger for a year or two before they start making things worse- convenient for all the Congresspeople up for election in less than 2 years.

Here are the ways I see this playing out, from most to least likely:

  1. By around 2032, either the slowly aging population or a sudden spike in interest rates forces the government to touch at least one of the third rails of American politics: cut Social Security, cut Medicare, or substantially raise taxes on the middle class (explicitly or through inflation).
  2. We get bailed out again by God’s Special Providence for fools, drunks, and the United States of America. AI brings productivity miracles bigger than those of computers and the internet, letting GDP grow faster than our debts.
  3. We default on the national debt (but this is a risky option because we will still want to run big deficits, and lenders will only lend if they expect to get paid back).
  4. We do all the smart policy reforms that economists recommend in time to head off the crisis and stop the rhino. Medical spending falls without important services being cut thanks to supply-side reforms or cheap miracle drugs (GLP-1s going off patent?).

I’m hoping of course for numbers 2 and 4, but after this bill I’m expecting the rhino.

Excluding “Non-Excludable” Goods

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Intro microeconomics classes teach that some goods are “non-excludable”, meaning that people who don’t pay for them can’t be stopped from using them. This can lead to a “tragedy of the commons”, where the good gets overused because people don’t personally bear the cost of using it and don’t care about the costs they impose on others. Overgrazing land and overfishing the seas are classic examples.

Source: Microeconomics, by Michael Parkin

Students sometimes get the impression that “excludability” is an inherent property of a good. But in fact, which goods are excludable is a function of laws, customs, and technologies, and these can change over time. Land might be legally non-excludable (and so over-grazed) when it is held in common, but become excludable when the land is privatized or when barbed wire makes enclosing it cheap. Over time, such changes have turned over-grazing into a relatively minor issue.

Overfishing remains a major problem, but this could be starting to change. Legal and technological changes have allowed for enclosed, private aquaculture on some coasts, which provide a large and growing share of all fish eaten by humans. Permitting systems put limits on catches in many countries’ waters, though the high seas remain a true tragedy of the commons for now.

While countries have tried to enforce limits on catches in their national waters, monitoring how many fish every boat is taking has been challenging, so illegal overfishing has remained widespread. But technology is in the process of changing this. For instance, ThayerMahan is developing hydrophone arrays that use sound to track boats:

Technologies like hydrophones and satellites, if used well, will increasingly make public waters more “excludable” and reduce “tragedy of the commons” overfishing.