Universal Basic Yosemite and the Parton Fertility Rate

Joy BuchananLeave a comment

A Twitter(X) exchange caused me to revisit my post from 2020 Affording a second child

A childhood friend and Facebook contact of mine pleaded to her friends, “How do people afford multiple children?”

I checked up on her and saw delightful pictures of a second child who, one way or another, they are now financially supporting along with that firstborn girl, in 2026. I obviously won’t post her family photos, but they took a summer trip to Yosemite National Park that looked something like this

Image by Grok

Based on how she felt about supporting a second child, I would be surprised if they have a third, a “big family.” Two is about where most people can still afford to take trips across the country in the summer.

This caused me to reflect on Dolly Parton, who we all miss. The U.S. flag is at half-staff in recognition of Dolly’s passing.

Part of her charming narrative is the fact that she was born into poverty. Famously, Dolly grew up with 11 siblings in a two-room Tennessee cabin. I doubt their family made it out to Yosemite.

So, with some help from ChatGPT, I inquired about the Total Fertility Rate of those Parton children. In one generation, everything dramatically changed. The number of children born to the Parton clan ranges from three to zero. Chat writes:

Dolly and her five sisters appear to have had only about six biological children among them—an average of roughly one child per woman. Dolly herself had none. Including their brothers, the twelve Parton siblings seem to have produced only about sixteen children altogether.

The Parton family therefore compresses a major American demographic change into just two generations. Avie Lee had twelve children; her daughters averaged about one each.

Income By Major (ACS 2024)

Zachary Bartsch7 Comments

A chart showing the average income by major was recently making the rounds on social media. So, I tried to replicate it. It turned out that some of the college majors were omitted. That part actually makes sense. The 2024 American Community Survey includes 174 degree fields – which is way too many for a clearly labeled bar chart. So, for local advertisement, I used only the majors and their equivalents that are offered at my university.  That chart is below (unweighted).

These are just raw average earnings by college major for employed adults. They all have decent sample sizes. Below is the cumulate distribution of sample size for each major. The smallest sample size is 45 (Military Technologies) and only 3% have sample sizes below 100. Only 34% have sample sizes below 1k.

You better believe that my colleagues and I show this chart to every single one of our classes. Obviously, it’s truncated from the full 174 majors, but it’s the relevant chart for us. If we use the full sample of college majors, Economics ($170k) drops to 3rd highest income, behind “Petroleum Engineering” ($173k) and “Health and Medical Preparatory Programs” ($183k). To be perfectly honest, those latter two sound a lot more difficult and have surprisingly little pay bump in compensation. Being more difficult is also consistent with the smaller sample size Economics=13k, Petroleum Engineering=343, and Health and Medical Preparatory Programs=1,099.  

One challenge that I’ve heard about the chart is that top business schools, such as Wharton, have Economics majors and various business concentrations. So, those top performing financiers are getting categorized as Economics in a way that is a bit misleading to young students elsewhere who are trying to decide on a major. If that’s true, then we should see Economics drop in the rankings if we omit the top-most earners.  After all, the criticism is that they’re pulling up the average.

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Should Immigrant Doctors Have to Retrain?

James BaileyLeave a comment

The United States has long answered this question “Yes- they need 3+ years of retraining unless they are from Canada”. But that has been changing rapidly since Tennessee began allowing foreign doctors to practice without years of retraining in 2023.

Doctors can’t start practicing independently right after getting their MD- they need 3 to 6 additional years of supervised on-the-job “residency” training first (even graduates of US medical schools). Most developed countries have similar systems of on-the-job supervised training for junior doctors. But until recently the US didn’t recognize training from any country besides ourselves and Canada. Doctors were required to re-do a US residency before practicing here even if they had been successfully practicing for decades in one of the dozens of countries with life expectancies higher than the US.

I’ve been pointing this out to my health economics classes for years as one of many quirks of the US system that keeps healthcare expensive and hard to access. But since Tennessee offered a faster pathway for trained foreign doctors with HB 1312 in 2023, dozens of states have rapidly follow suit:

Source: The Match Guy, May 2026

I think the impact of this change has been limited by the fact that states still tend to have other requirements for foreign doctors, like spending a year or two under supervision at ACGME-accredited programs. This still serves as a shorter quasi-residency, and these programs are exactly the ones that tend to have plenty of doctors anyway- big urban hospitals, not small rural clinics. Immigration rules present their own high and rising barriers; most foreign doctors can’t come here in the first place.

That said, I’m still happy to see policy experiments from states attempting to address our doctor shortage. These state laws waiving residency retraining requirements are so new and so numerous that the present an excellent opportunity for research on their effects; I’m adding this to my ideas page.

I noticed the rapid expansion of these laws when doing research for a talk I’m giving at Creighton University at 4pm today (if you’re in Omaha, maybe see you there); thanks to Creighton for the inspiration.

Nicholas Polson Has Written Over 200 Academic Papers in 2026 (so far)

Jeremy Horpedahl3 Comments

UPDATE: I stupidly didn’t realize my co-blogger Mike wrote about this too. My bad! I skimmed last week’s posts, but it didn’t click in my head. Be sure to read his thoughts.

ALSO: lots of the papers by Polson seem to have vanished from SSRN since I wrote this blog post… yesterday. Everything after August 14th has been taken down. That brings his count of papers in 2026 down to a mere 168 papers. Still essentially several lifetimes of output from a typical academic.

For most academics, writing papers that may be eventually published in peer-reviewed journals is an important part of what we do. For some academics, it is the main thing they do (others have more emphasis on teaching courses at their university). Most academics always have a few projects they are working on, with perhaps a goal of finishing 2 or 3 a year, and thus having a regular pipeline of a few publications every few years. But some academics are much more prolific.

Take Daron Acemoglu for example. He has long been considered extremely prolific. So far in 2026, according to his Google Scholar page, he has had 15 papers that have either been published this year or come out as new working papers (that’s the bulk of them). In the past year (2025 and 2026), he has had publications in the Quarterly Journal of Economics, the American Economic Review, and the Journal of Economic Literature, among others (the AER paper was his Nobel lecture). For lower tier academics, that’s almost a lifetime of publications in 12 months or so. Acemoglu is extremely productive.

But I just discovered an economist that is, apparently, even more productive than Acemoglu, at least as measured by working papers. Nicholas Polson has, by my count using his SSRN page, already written 258 working papers in 2026 alone. He’s already written (or at least published to SSRN), six papers today, August 26, 2026. In the month of August 2026, he has written and posted to SSRN a total of 104 papers — and counting, since the month isn’t quite over.

These aren’t just short notes. Most of the papers are of normal academic length: 32 pages, 27 pages, 58 pages. The papers are both theoretical — involving complex math in some cases — or empirical, with regressions. Read any single paper, and it feels like just a normal academic paper, the kind of thing that an academic might work on for a few months. He even has a frequent co-author, which is common for economics papers (and helps to be more productive), a systems engineering professor named Vadim Sokolov, who is a co-author on a little over 100 of the papers this year.

What is going on here? Obviously the research productivity of Polson and his co-author Sokolov is aided by AI. Who isn’t using AI to increase their writing and research productivity these days? But I don’t think I have seen any academic, at least not in economics, that has really pushed it to the limit.

Presumably, many of these papers will get submitted to academic journals. I can imagine the editors of journals have a very hard job these days, as the number of papers submitted has likely increased significantly, while the time that referees have available has not increased much (of course, AI is likely making referees more productive too, though many journals ask you not to upload the paper into an AI program as a referee, since it is unpublished work when you are reviewing it).

I really don’t know where academic publishing goes from here. AI has made us all more productive in terms of output, but are we better at answering important questions in our science than pre-AI? Probably, though it is hard to know. Journals and the peer review process has traditionally been the filter to sort real contributions from gibberish. I don’t know how the peer review process continues in its current form given the massive increase in output (much of it good!) that we are seeing from academics. Dr. Polson is just a leading example of a growing challenge for academia.

Bond Market Blows Off Treasury Bond Buyback; Gold and Bitcoin Soar

Scott BuchananLeave a comment

Scott Bessent used to be a serious financial player. When he was with George Soros’s fund, he helped them make a billion dollars in 1992 by betting against the British pound, and $1.3 billion in 2013 with a bet against the Japanese yen. He also ran his own hedge fund, with as much as $5 billion under management. In 2023-2024 he hitched his wagon to the fortunes of Donald Trump, becoming a large campaign contributor and fundraiser. He was rewarded by being made Treasury Secretary. On January 27, 2025, the U.S. Senate voted to confirm Bessent’s nomination. (The same day, a man with multiple Molotov cocktails and a knife who intended to murder Bessent was arrested at the United States Capitol, an event seemingly lost in the noise of all the attempted assassination attempts against this administration).

The current administration has continued the policy of the previous administration of profligate peacetime federal deficit spending, some 6% of GDP annually, well above the 50-year average of about 3.8%. The only way to finance this spend is to sell more and more Treasury debt. But the more of that debt is out there, the more interest needs to be paid on it. By the mid-2030’s, interest payments will balloon to the point that they, plus mandatory transfer payments like Medicare/Medicaid/Social Security, will consume 100% of tax revenues, with nothing left for discretionary spending (including defense). Being the cabinet officer responsible for financing this mess now is sort of like being CFO of Lehman Brothers in 2008.

Which brings us to the ignominious market response to Bessent’s attempt at bond market intervention last week. As it has become more and more clear to the rest of the world that the U.S. has no intention of reining in its deficit, but instead hopes to deal with it by inflating away the value of the dollar, the market has started to demand greater compensation for holding long-term U.S. debt. If you are wondering why you now have to pay 6.65 % for a 30-year mortgage, wonder no longer. These high interest rates are making it all the more painful for Treasury to fund the deficit.

Secretary Bessent made a surprise announcement last Wednesday that his department would double its maximum purchase of older, less-liquid long-term bonds, from $2 billion per week to $4 billion. The stated purpose of this long-running buyback program is to retire hard-to-trade bonds and replace them with newer, more-liquid bonds. That’s fine, but this snap announcement shortly after its quarterly refunding plan broke with Treasury’s long-held strategy of making ‘regular and predictable’ announcements, and (together with statements by Bessant threatening further intervention) was widely seen as an attempt to talk down the long-term rates.

It worked for about one day. Long term yields initially dipped Wednesday morning by about 0.1%, but by Thursday they were about back to where they were before the announcement. Not only did traders realize the size of the intervention was far too small to move the enormous T-bond market (and would not net decrease T-bonds outstanding), but Treasury’s move became interpreted as a sign of desperation over funding the U.S. deficit. That vibe will not help bring down Treasury bond rates going forward. The value of the dollar dipped on world exchanges, while the price of alternatives such as gold and Bitcoin soared:

That is a chart of Bitcoin price in the past month. HODLers rejoice, the long crypto winter may be over…

Journal Crisis at Games and Economic Behavior

Joy Buchanan1 Comment

I used Grok for this query because economists were discussing the issue on X(Twitter) this week and Grok would have quick access to that discourse. Note that Grok provided links to legitimate web sources, not just Twitter speculation. I am providing those same links in the place where Grok put them. I do not know how much the chatter of the week affected the response below.

Prompt from J. B. on 8/22/26 to Grok: What happened to the economics journal Games and Economic Behavior?

The leading game theory journal Games and Economic Behavior (GEB), published by Elsevier since its founding in 1989, remains active and is still publishing issues (including volumes into 2026), but it is in a major editorial crisis due to a mass resignation of its leadership. (https://www.sciencedirect.com/journal/games-and-economic-behavior)

In late July 2026, Editor-in-Chief Hervé Moulin (who had held the role since January 2021) was informed by Elsevier that his 3-year contract would not be renewed, despite his willingness to continue. Elsevier cited a desire to move “towards a closer alignment with Elsevier strategic priorities and publishing policies.” Requests for further explanation (from Moulin and then collectively from the other six editors) were dismissed; Elsevier simply asserted its contractual right to make the decision and began searching for new editors without input from the existing board. (https://gametheorysociety.org/message-from-herve-moulin-geb-editor/)

In response, by August 14, 2026, all seven editors (Moulin plus Sushil Bikhchandani, Aislinn Bohren, Nicole Immorlica, Roberto Serrano, Emanuel Vespa, and Nicolas Vieille) resigned with the required three-month notice. Nearly all of the advisory editors (the equivalent of associate editors) also resigned in solidarity. The outgoing team is handling papers already under review and new submissions until November 14, 2026 (with some flexibility for papers already assigned by mid-August); after that, they will only finish evaluations already in progress. Elsevier has publicly thanked Moulin for his service. (https://gametheorysociety.org/message-from-herve-moulin-geb-editor/)

The journal continues under Elsevier ownership (it is one of the two official journals of the Game Theory Society, alongside the International Journal of Game Theory). Community discussion has focused on the implications for the field, the role of commercial publishers, and possibilities such as launching a successor journal. Similar recent mass resignations have occurred at other Elsevier titles over governance and editorial control issues. (https://casrai.org/news/2026-editorial-board-mass-resignations)

In short, GEB has not shut down, but its longstanding editorial team has largely departed over Elsevier’s non-renewal of the Editor-in-Chief and related decisions.

Prompt from J. B. on 8/22/26 to Grok: What will be the implications for the reputation of the journal?

The reputation of Games and Economic Behavior (GEB) is likely to face significant short- to medium-term damage, with longer-term outcomes depending heavily on how Elsevier handles the transition and whether a strong successor journal emerges.

GEB has long been viewed as the leading specialized journal in game theory (and one of the stronger outlets in theoretical economics more broadly). Its prestige rests on attracting high-quality, creative work; the expertise and independence of its editorial team; rigorous standards; and community trust. The mass resignation of all seven editors (including Editor-in-Chief Hervé Moulin) plus nearly the entire advisory board in August 2026, following Elsevier’s non-renewal of Moulin’s contract, directly undermines those foundations. (https://gametheorysociety.org/message-from-herve-moulin-geb-editor/)

Short-term effects

  • Loss of trust and submissions: Top researchers often choose journals partly based on the known editors and the expectation of fair, expert handling. With the board depleted (current editors only fully process papers until mid-November 2026), many authors are likely to pause or divert submissions. Community discussion already includes calls for boycotts of the Elsevier GEB and support for alternatives. @Afinetheorem
  • Perception of publisher interference: Elsevier’s stated rationale (“closer alignment with Elsevier strategic priorities and publishing policies”) and its decision to search for new editors without board input have fueled views that commercial priorities overrode academic ones. This echoes other recent mass resignations (e.g., Journal of Approximation Theory at Elsevier, where resigning editors declared the journal “as we have known it has effectively ceased to exist”). casrai.org
  • Operational disruption: Delays in reviews, potential quality variation under interim or new leadership, and uncertainty can further erode confidence among authors, referees, and readers.

Metrics such as impact factor or AJG ranking (currently 3) change slowly and will not immediately reflect the crisis, but subjective reputation in the game theory and economics communities can shift quickly.

Medium- to long-term scenarios

Historical patterns from similar mass resignations offer useful analogies:

  • “Zombie journal” risk: The title, ISSN, indexing, and historical impact factor stay with Elsevier. If the new editorial team is perceived as less distinguished or more aligned with volume/publisher goals, submissions from leading researchers can decline, citation patterns can shift (sometimes toward more geographically concentrated or lower-prestige work), and the journal’s standing within the field can permanently weaken. Cases like Lingua (Elsevier, 2015) and others show that the brand can persist while the scholarly niche contracts. sciencedirect.com
  • Recovery path: If Elsevier rapidly appoints highly respected new editors who maintain rigorous standards and rebuild community confidence, the damage can be limited. Some journals have stabilized after board changes, though full restoration of prior prestige is uncommon when the exit was acrimonious.
  • Successor journal effect: Strong community interest already exists in launching a new outlet (possible names floated include variations on “Theory of Games and Economic Behavior” or society-backed alternatives; comparisons are drawn to how JEEA or other breakaways have functioned). If a credible successor is established—especially one endorsed by the departing editors and the Game Theory Society—and is treated as the “true” continuation by tenure/promotion committees, the original GEB’s relative prestige would likely decline further. Successful breakaways (e.g., Glossa after Lingua, or Imaging Neuroscience after NeuroImage) have often captured much of the field’s attention and high-quality papers. journalmetrics.org

**end of Grok responses **
If you want some chatter, you can put “GEB” into the search bar at x.com, LinkedIn, or BlueSky this week and see some more speculation.

There is a lot happening with publishing, including a huge shock of strangeness from the ability to both write and review papers with LLMs. Tumult will be normal. Read Mike on Will AI kill the research paper? or Mike on The actual AI problem in academic economics or Mike on Academic economists are overcommitted . The real perennial problem is that nothing is free but no one wants to pay.

Lastly, dear reader, you might wonder why so much of my post was AI-generated this week. I see this as burning my tokens so you don’t have to. You can find this with a free web search. Some people predict that “cheap AI” is coming to an end, so we might find it worthwhile to publish responses as well as prompts for each other. Regards, fellow humans and AI readers.

Intellectual Squatting

mdmakowsky2 Comments

So a professor at a major institution wrote 200 papers last year. Unlike other commenters I’ve observed so far, I think this is neither true research nor pure AI fraud. It is likely AI “slop” to varying degrees, but unlike a lot of slop there is probably real value within it. What I have not yet seen ascertained is whether any of it has been vetted, investigated, or curated by the author in a meaningful way. The real question is: what is the actual ambition here? I think the tell is the lack of submission to peer review.

I think this is a form of intellectual squatting. The nice version is it’s putting out a series of half-baked papers in the hopes of establishing a property right to the underlying ideas at an earlier stage of the research process than previously possible. The less generous interpretation is it’s dumping a series of haystacks on the plains and laying claim to the needles probabilistically within each. Imagine you are a person who has highly esoteric, potentially important ideas every day. Many of those ideas you suspect, based on some combination of experience and ego, are new in at least one dimension. You would like to get credit for that newness. For being first. What’s the problem?

The problem is that scholarship remains more perspiration than inspiration. Having a new idea is great, but it takes years to work through the nuance in sufficient detail that you can convince your peers of the coherence and originality of the contribution. During the minutes each day you are not working on this singular project you have the inspiration for other ideas, sometimes multiple within a single day. How frustrating is the proposition that someone else gets credit for the originality of contribution just because they had time to reveal it to the world while you were embroiled in your investigation of what is only one of your many score ideas!?

Ah, but meta-level inspiration has struck you! What if you took each one of those ideas, spent an hour curating a series of prompts around it, and then let Chat GPT (or another LLM) fabricate an entire research paper around it? It might not be good, correct, or even coherent, but it does somethine far more important. It establishes an intellectual property right to the claim of being first. Now, to be clear, you are fully aware of the deficiciency of your paper as an actual scholarly contribution, but if somone else writes a full paper you at least have something to point to and say “I was here first. Cite me. Hell, if I’m close enough you might even have to name it after me. Well, sure, us. But definitely include me. Glory shared via hypenhnation is better than no glory at all.”

Is it a contribution? That’s something that will vary on a case-by-case basis, but I expect far more misses than hits. The work isn’t there. It’s like plopping down a block of marble with a dramatic-ish sketch of a man on an adhered post-it note and claiming that Michaelangelo needs to share credit with you on any subsequent sculptures. It’s like asking people to cite that one cool tweet you did about how DNA is cool but maybe RNA could be useful in vaccines one day. Intellectual property rights trolling via AI blunderbuss.

BTW, I’m not 100% sure this isn’t an AI take on a modern Sokal hoax. An attempt to show how much AI slop is introducing a whole new version of Gresham’s Law to scholarship. But if we treat it as earnest, it’s proof that a very smart person can potentially disrupt the market for scholarship, patents, or any other intellectual property by laying claim to ideas in much the same way that the printing press undermined the market for plenary indulges. Flood the market, leave it to someone else to sort through the ecumenical consequences.

Problems with Price Stability

Zachary BartschLeave a comment

Inflation targeting has been the goal of central banks for decades now, either implicitly or explicitly. Of course, they say that they have multiple goals, but they give most attention to the price level. That’s probably because it is easy to measure and more directly related to their activities than the unemployment rate and private financial activity. Price level targeting and inflation targeting are not quite the same thing – but I’m not in favor of either. This post describes what happens when the central bank targets the price level and offsets other changes in the economy in order to achieve their goal.

Volatile Capital Prices

If consumer prices are constant in the face of productivity shocks, then capital prices adjust instead. Capital is just goods that create other goods. If capital becomes more productive, then that means being able to produce more at given prices or being able to produce given quantities at lower costs. The demand for capital is ultimately determined by how profitable it is. This includes the costs of maintenance, the price of output, and the capital’s productivity. All else constant, changes in the revenue produced by the capital for the firm affect the equilibrium price of capital.  

If NGDP is constant and capital productivity improves, then output rises and consumer prices would fall. With unit price elasticity of output demanded, the total revenue of the firm remains constant and the nominal capital price does too. The 19th century gold standards had plenty of problems. But one feature was that long-run consumer prices fell and long-run capital prices were more stable.

If, instead, the Fed stokes NGDP to prop up consumer prices, then the firm’s revenue rises. Demand for the capital rises and so does its price. The opposite occurs when there is a negative productivity shock. So, capital price volatility is the trade-off for consumer price level stability if productivity changes. We can argue about which price volatility is better in regard to inequality, investment planning, financial stability, etc. But my strong low-hanging fruit point is that consumer price volatility just pushes the equilibrating mechanism to a different set of prices.

Volatile Income

As I said above, if the Fed wants stable consumer prices, then it must offset the impacts of productivity shocks with changes in aggregate demand – its only lever. Negative productivity shocks are offset with aggregate demand contractions.  

People act like they have adaptive expectations. Of course, people differ by how forward-looking they are. So, on average, their expectations are formed by what happened during the prior period or the last time that they observed a similar circumstance. Why does this matter?

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Getting Music On Streaming Is Surprisingly Easy

James Bailey2 Comments

Before recording and broadcasting technologies, there was no way for people all over the world to hear the same music performance- you had to be in the same room as the performer. Even when I was growing up, distributing your worldwide meant getting a record deal, something few could do. But the modern internet allows for music to easily be uploaded from anywhere, to be listened to anywhere.

For artists, this means to problem shifts from just being available, to standing out to listeners among the sea of available music. How best to do this- other than making great music- is a complex and detailed question of marketing. But one crucial early step- getting on the right streaming platforms where artists make their money– is now surprisingly simple and easy.

Source: My image made from Chartlex data

Amateur artists tend to start with what is free- uploading their music directly to Youtube or Soundcloud. But huge numbers of listeners are on streaming platforms like Spotify, Amazon Music, or Apple Music. These don’t allow artists to upload music directly, which can make listeners or new artists think that getting on streaming platforms is a bit like getting a record deal in the old days, where an industry insider needs to approve the artists. In fact, approval for streaming now mostly runs automatically through third-party music distributors.

Adding third parties into the mix sounds complicated, but in fact they are easy for artists to work with, and a single distributor can get your music onto all major streaming platforms at once. Here’s how the page for uploading a song starts at the largest distributor, Distrokid:

There are many distributors; Spotify currently recommends 21 that work directly with artists. Distributors charge artists, but not very much. Some charge by the song or album (CD Baby does this, starting at $10/song or $15/album), others let artists upload unlimited songs for an annual fee (DistroKid does this, starting at $25/yr). Distributors also collect royalties from streams on behalf of artists. To me this looks like a no-brainer for any semi-pro musician who is out there playing some gigs, but also makes sense for stronger amateur artists looking to expand their reach* (for professionals with record deals, of course, the label will do this for you).

For an academic comparison, getting your music out there is now less like hoping an insider likes you or your work enough to invite you to NBER, and more like just uploading to SSRN (if SSRN charged a small fee).

All this is a long way of saying- you can now find my son’s piano compositions on all the streamings (Spotify, Youtube / Youtube Music, Apple Music, Amazon Music).

*At least if you write your own songs- buying the rights to distribute covers costs extra (e.g. $12 per song per year for DistroKid), and on streaming people can listen to the original artist just as cheaply and easily, so there’s not the same niche for cover bands that there is in live music.

Welcome Back to School: Potential College Students are Now Declining

Jeremy HorpedahlLeave a comment

If you have spent any time around higher education lately, you have probably heard of the “demographic cliff” or “enrollment cliff” for years now. Well, it’s finally here. In terms of total number of births, the US peaked in 2007 at a little over 4.3 million births. That’s the highest year ever, even higher than the peak of the Baby Boom (not in terms of fertility rates, of course, I’m just talking about absolute number of births).

Babies born in 2007 turned 18 in 2025. But after 2007, births started to fall. In 2025, there were just about 3.6 million births, a decline of about 700,000 babies since 2007, or a 16 percent decline. The number of 18-year-olds won’t be exactly the same as the number of births in a given year: it’s actually usually a bit higher, as net immigration is much larger than the small number of children that die before they reach 18. For example, the 1982 birth cohort had 3.68 million babies, but 18 years later in the year 2000 there were 4.08 million potential college students.

Historically there have been about 10 percent more 18-year-olds than the birth cohort, but lately (2021-2025) it has only been about 5 percent higher than the birth numbers.

There are, of course, all kinds of social, economic, and political implications of falling births. I just want to mention one that is specific to the industry that I work in: potentially falling college enrollment. And because this enrollment will not be uniform across states and universities, this will cause serious budget issues for many colleges in the coming years.

Some folks in higher ed have lately been asking when the demographic cliff will hit. It’s here: