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 BaileyLeave a comment

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:

WWII Strategic Initiatives 6. Fort Commander’s Lonely Decision Saves Norwegian Government from Capture by Germans

Scott BuchananLeave a comment

At 4:21 a.m. on April 9, 1940, a 64-year-old Norwegian colonel six months from retirement had about ninety seconds to decide whether to start a war.

Birger Eriksen, who entered Norwegian military service way back in 1893, commanded Oscarsborg, a sleepy coastal fortress on a rocky island in the Oslofjord, armed with three 28cm (11 inch) Krupp guns dating to the 1890s – – plus a secret weapon the Germans didn’t know about: torpedo tubes from 1901. His garrison was mostly reservists conscripted a week earlier. Out of the pre-dawn dark came six unlit, unidentified warships steaming toward Oslo.  Norway had assumed that its diligently neutral stance would avert any foreign attack, and so was lax about maintaining coastal surveillance. The ships could have been British. Firing on the wrong flag meant international catastrophe; not firing, if they were German, meant the capital fell before breakfast.

Colonel Birger Eriksen, the commander of Oscarsborg on 9 April 1940.

Eriksen had no orders from Oslo and no time to ask. He gave the command anyway, reportedly saying: “Either I will be decorated, or I will be court-martialed. Fire!”

The lead ship was the Blücher, a brand-new 16,000-ton heavy cruiser packed with troops, Gestapo officers, and administrators meant to seize the king, the government, and Norway’s gold reserves in one stroke. Two shells from the fort tore into her at point-blank range, followed by torpedoes into her flank. Within ninety minutes she rolled over and sank, taking hundreds of men down with her. The German attack on Oslo was not completely averted, but it was significantly delayed and hampered.

German Heavy Cruiser Blücher (Image by Bundesarchiv)

That single decision to attack the invading fleet bought Norway’s government just enough hours to flee Oslo by train with King Haakon VII — and to load 53 tons of gold bullion onto trucks barely ahead of the advancing German columns. The gold made it out to Britain via a harrowing overland and sea relay; the government reached London and kept functioning as a legitimate exile authority, which gave the Norwegian resistance something to fight for rather than just against. Also, Norway had an enormous (~1000 ships) merchant marine fleet, and the intact, legitimate Norwegian government in exile ordered it into the service of the Allies, right when Britain desperately needed ships and sailors to transport cargo to stay in the war.

The strategic hangover lasted five years. Hitler, rattled by the loss of the king and by ongoing Allied fake Scandinavian invasion plans, garrisoned Norway with somewhere around 300,000–400,000 troops for the rest of the war. This was a staggering commitment, sitting largely idle when they could have made a decisive impact elsewhere. One old colonel, one hunch, one order — which tied down a whole German army guarding a country it barely needed.

This is the sixth in a series of occasional blog posts on individual initiatives that made a strategic (not just tactical) difference in the course of the second world war, an event that gave us the world of the second half of the twentieth century. Here are previous posts:

WW II Key Initiatives 1: FDR Prodded the Navy to Convert Cruisers to Carriers, Just in Time

WW II Key Initiatives 2: “Thatch Weave” Tactic to Counter More-Agile Japanese Fighter Planes

WW II Key Initiatives 3: Kurt Tank Gives Germany a Superior Fighter Plane, the Focke-Wulf 190

WW II Key Initiatives 4: Building Hundreds of Small, Slow, But Cheap Ships to Counter the U-Boat Threat

WWII Key Initiatives 5: General Zhukov Helped Save USSR By Mastering the Pincers Counterattack

First Derivatives

mdmakowskyLeave a comment

Lebron James is obsessed with golf. His new YouTube channel is what is getting the most attention, but this has been a publicly known fact for a while. There’s even a (largely unevidenced) theory that he chose to play his potentially final season in Philadelphia for it’s proximity to elite golf courses.

I just want to take this time to deconstruct why Lebron’s golf obsession is interesting. It’s a reminder that first derivatives often matter more than both absolute values and higher order derivatives. Let me explain.

Lebron at 41 years of age, in the face of history, experience, and logic, is still one of the 20 very best human beings at basketball in the world. So, in terms of absolutes, playing basketball should still give him immense satistfaction. The problem, of course, is his personal reference point (how good he used to be) and the rate of decay he is experiencing from that reference point. This is a person who spent more than two decades getting better and better at something, who arrived at a point where they were literally the very best in the world at it, only to then at some point in time arrive at the awareness that they were in fact getting worse at it. To be clear, that rate of decay is far slower than anyone could have predicted, but it remains decay nonetheless. And it’s not just “getting worse”. It’s getting worse at something that you are orienting your every day around. Your meals, your sleep, your family life, everything, all in dedication to something you are getting worse at.

I’m now going to generalize from my own lived experience, but I think the emotional returns to dedication are always stronger when the first derivative is positive, but no amount of work can guarantee it. You can work harder and increase the positive gains or, failing that, slow down the decay, but at some point the decay is inevitable (i.e. the work shows up in the second derivative). And no matter how much you slow it down, decay just isn’t as satisfying as the day-to-day lived experience as improvement or even plateauing.

And this is where golf comes in. Golf is a sport that has much lower athletic barriers to entry and, for Lebron or anyone who is starting out, a vastly lower reference point for quality. It is entirely likely that every time Lebron has ever picked up a golf club he is better at golf than he was the previous month. It is the 100% inverse to what Lebron has experienced playing basketball for at least 7 or 8 years now, likely longer. The relief he must feel, directly experiencing and observing the returns to his efforts.

Coming to terms with being past your prime is a standard trope in narrative fiction of all formats, but from an actual mental health point of view, I don’t think it is given enough attention, particularly for those at the tops of their field. There are vanishingly few purely natural elites in any profession, vocation, or craft. Most have had to sacrfice whole avenues of life experiences to achieve such levels, and when they do begin to decay they either have to endure public scrutiny bordering on censure, or the quiet tragedy of being alone in their ability to discern just how much they have lost. The latter is almost worse. Almost.

As a final tidbit, let me make a loose connection to technological innovation and AI specifically. Obsolescence hurts. A negative first derivative hurts. But what hurts even more is an unexpected shock that accelerates that decay. Injuries are mentally hard for athletes, in part, because of their often discontinuous nature. They were still improving, the rate at which they were improving was accelerating, until they weren’t. There are professions that are wrestling with this right now. There are professionals who reasonably expected to have another half decade before the decay began. That timeline is now in question. And most of us don’t have the luxury of being a generationally great athlete who can immediately become great at something completely new.

Predicting Social Media from 1997

Joy Buchanan3 Comments

At a rummage sale, I picked up a book by cartoonist Scott Adams called The Dilbert Future: Thriving on Stupidity in the 21st Century published in 1997. I thought I might find a clever prediction about the future, which we can now verify from the standpoint of 2026.

The text of the book is mostly dumb. I get the impression that Scott Adams was making easy money with a guaranteed humor book contract. I don’t recommend the book to anyone.

HOWEVER, with my paper copy I kept skimming ahead to see if any of his predictions about the future were impressive. Finally, on page 200 I found something.

Recall, the internet only became publicly available in the early 90’s. Respectable newspapers might have started to lose out to cable news in the mid-90’s. Blogs did not start until after Adams’ book was published. Social media proper (marked by the launch of Facebook) started in 2004. (Let millennials quietly walk away from Xanga journals and pretend that never happened.)  So, my interest in this passage hinges on the fact that this book has a publication date of 1997.

The following is copied from Adams’ humor book.

I predict that news outlets will try to compensate for the loss of relevant news by focusing on stories that are more shocking and depressing than ever. At least that way they’ll get your attention and sell advertising even if the stories aren’t “news” in the traditional sense.

This will limit the reporting to a few stories per year about famous people who are killing other famous people. And if there are not enough of those stories to sell advertising slots, the media will…

Prediction 51: In the future, the media will k*** famous people to generate news that people will care about.

The end of traditional news outlets will not limit people’s access to information. Thanks to the ubiquity of video cameras and the Internet, every citizen will be a reporter. If something happens in your neighborhood, you’ll tape it, stick it on the Internet with your own commentary and make it available to the world… The weather reports will be computer-generated and constantly available by computer, pager, voice-mail… All news gathering will be disaggregated.

Prediction 52: In the future, everyone will be a news reporter.

People will have access to software that constantly combs the internet for “small” news that is relevant to them.

…

your software will be able to do a sort of “credibility credit check” on any person who posts information to the Internet… This won’t be foolproof, but nothing is.

This new model depends on people being willing to take the time to put information on the Net without the benefits of payment. Why will people do that? They will do it because that’s our most basic human nature: People like to talk more than they like to listen.

Joy again: Not bad as predictions go. Notice the quaint terminology, such as “tape it” and pagers. (Pagers use radio networks instead of cell towers.) Attention is scarce, and writing is not (even pre-LLM). Adams predicted what I call poastmodernism.

High Income Rentals are Low Income Rentals

Zachary BartschLeave a comment

Have you heard about the abundance movement? It basically says that we should enact a mix of regulatory and supply side reforms in order to produce more for everyone, especially the least economically advantaged. The reforms extend to the housing market and ensuring adequate housing.

There’s an argument that building any housing, even at the high end, can reduce the cost of shelter for everyone – even people who would never live in the newly built housing. The idea is that high income people switch to the newly built housing and leave less attractive housing. Someone else in that high income bracket snatches up the older place, leaving their prior housing vacant. The vacancy shuffles around high priced rentals until, ultimately, the vacant rental price must fall in order to attract a renter, such as someone further down the income distribution. Then the entire process continues, with the game of vacancy musical chairs working its way down the renter income distribution.

The more overlap that there is between housing consumption choices the quicker there is an impact on lower priced housing.   If you think that high income people consume higher priced housing, then you might think that there is a substantial difference between housing consumption choices and that it will take a long time for this ‘trickle down’ to get to the people who need it most. If income groups compete more for the same housing, then the effects on price will occur sooner for the lower income people.

How much Rental Overlap is there?

Miami, Florida has some of the highest housing costs in the US. Below is a histogram of annual rental costs in Miami by household income quartile (ACS 2024).   I restricted the data to positive incomes and rents and the highest rents are censored down to $98.4k annually. First, we can definitely see that the highest incomes (quartile 4) have the most censored annual rents and that the 1st income quartile (lowest) has the most annual rent payments nearer to zero. So, the histograms make sense in that way. But I was surprised by how much overlap there is. Different income quartiles are consuming many units in the same price range!

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Bubble Worries Mean Diversify…. But How?

James Bailey1 Comment

Mike is concerned that US stocks could be a bubble, as are many others:

if we take parallels to the past seriously, there arises the question of whether a 40 year old with a 100% index fund portfolio should consider hedging/reallocating their portfolio a decade sooner than they planned on becuase, well, just look at that [CAPE] chart.

But what to do about it?

So, seriously. Are we hedging? And what are we hedging into? Asking for a friend. Who is an economist. And also me.

My answer: I’m diversifying into global stocks, which tend to be much lower-priced: 

Source: The Idea Farm, Global Valuations Update July 2026

But how do you practically do this?

A simple and cheap way to get a highly diversified basket of global stocks is VEU (Vanguard ex-US). Over 3000 stocks from around the world, P/E of 19, rock-bottom fees. One disadvantage for diversification purposes is that its biggest 5 holdings make up 12% of the index and they are all AI-related.

If you’re willing to make more concentrated and specific bets in order to get even cheaper, here are some other foreign indices I like:

  • FRDM (Freedom 100 Emerging Markets ETF): Invests in emerging markets with the highest economic freedom ratings. I love the theory & it’s performed very well for me & its overall PE is a reasonable 17, though it’s largest holdings are in Taiwan and South Korea, so not a good way to get away from AI.
  • ILF (iShares Latin America 40): Invests in large Latin American companies. P/E 11 with low AI exposure.
  • FYLD (Cambria Foreign Shareholder Yield ETF): Invests in high-yielding companies in developed countries outside the US. Measures yield using stock buybacks in addition to dividends. This serves as a value screen that keeps PE low (currently 13) and avoids expensive sectors like AI.
  • EYLD (Cambria Emerging Shareholder Yield ETF): Same idea as FYLD but for emerging markets. Current PE 12

I also hold single-country indices for Japan (FLJP, PE 20), Poland (EPOL, PE 13), and India (EPI, PE 17). These are probably riskier than the broad indices above, but still fairly diversified across companies.

While foreign stocks are my preferred hedge, there are many others. For US stocks there are small-cap or value indices, or just buying individual stocks you like (not necessarily crazy). The 20- and 30-year US treasury bonds are intriguingly yielding over 5%, though between my age and my inflation concerns I don’t own any. TIPS are much more attractive, yielding 2-3% over inflation, I don’t own any yet but I’m considering it. Gold indices like IAUM are another good hedge.

Of course this isn’t necessarily a bubble that will pop any time soon, or at all- AI is a real technological advance- so between that & general efficient market principles I don’t think the answer is to sell everything & go to cash, much less short the market. But Mike is right to ask how to hedge, and I think anyone holding ~100% US stocks should consider diversifying.

Disclaimers: Not investment advice, I hold some of the indices named.

Everything At the Grocery Store is On Sale Relative to 1980

Jeremy Horpedahl1 Comment

Back in May 2024, I wrote about grocery prices in 2024 compared to 1980. Relative to average wage increases, almost everything was more affordable — the one exception was bacon.

Grocery prices have continued to climb since 2024, but so have wages. What does the comparison look like now? Well, I have good news for bacon lovers:

Figure 1

The chart shows the change in relative affordability, as measured by how many minutes of work at the average wage it would take to purchase the item (using consistent product sizes and weights). As I wrote in that 2024 post, these are not items that I cherry picked. These are all 24 grocery items where BLS has price data in both 1980 and 2026 (out of about 150 items total). Perhaps there is some survivorship or selection bias as to which items are available in both years, but looking at the list this seems like a pretty reasonable shopping cart for a typical consumer (well, maybe there aren’t buying all the meats every week, but probably every month). The prices are updated through July 2026, with the CPI data just released this morning.

While I have used average wages here, that isn’t a trick. We don’t have a median wage for 2026 yet, but using a measure of median earnings you can see that average wages and median weekly earnings increased at exactly the same rate since 1980.

But consumers probably aren’t thinking about prices relative to 1980. Their time horizon is likely shorter. What if we made the same comparison to 2026 using the 2019 prices, which is right before the pandemic and within most shopper’s recent memory:

Figure 2

Relative to 2019, things do look quite as rosy. Some items are “on sale” in terms of affordability, but a lot of items aren’t, especially a lot of proteins. And no doubt many consumers will focus on the items that are less affordable, rather than those that are more affordable (and even for these items, the nominal price is higher, so consumers might still be frustrated).

It is important to note that this basket of 24 items isn’t a perfect representation of all the items consumers purchase. Compared to the CPI “food at home” index, average wages have actually increased more since the beginning of 2019. But consumers are right to feel that beef and few other items are much less affordable than 2019, even if over the long run they are more affordable.

Figure 3

Boy Wonder Leopold Aschenbrenner Blows Up His $45 Billion Situational Awareness Hedge Fund

Scott BuchananLeave a comment

Leopold Aschenbrenner is a very bright guy. Born in Germany to physician parents, he skipped enough grades to graduate from high school at age 15, allowing him to enroll at Columbia University in 2017 at that same age. He went on to graduate from Columbia at age 19 as valedictorian with a degree in economics and mathematics-statistics. An econ prof at the time said his “record of scholarship exceeds that of any student in the department in the previous 20 years.” The Mercatus Center, a think tank at George Mason University, recognized his potential, awarding him an Emergent Ventures grant.

Leopold Aschenbrenner, Columbia Class of 2021 Valedictorian

After graduation, Aschenbrenner moved into the effective-altruism research and grantmaking world, making notable contributions in various ways. In 2023, he joined the newly created “Superalignment” team at OpenAI, that was charged with making conceptual and engineering progress on aligning systems “much smarter than humans” before such systems were built. The next year he was discharged by OpenAI; the company said it was because of a security leak, but his version (which I find more credible) is that he was ousted as retaliation for circulating an internal memo arguing that the company’s protections against model-weight theft and algorithmic exfiltration were inadequate for AGI-relevant work.

Two months after his departure from OpenAI, he self-published Situational Awareness: The Decade Ahead, which you can download here.    This monograph synthesized scaling-law extrapolations, geopolitical analysis, and AI-lab security commentary into a single forecast: that the largest AI labs, on current trends, will plausibly reach AGI around 2027 and that an intelligence explosion to superintelligence could occur in the subsequent few years. This work went viral on Wall Street, and before you can say “monetization”, he was leading a hedge fund named, appropriately enough, Situational Awareness. There he put into practice his convictions that the demand for compute would be voracious, and would be limited by physical constraints such as electricity and chip fabs.

Thus, in his fund he went long companies like SanDisk (memory fab), Bloom Energy (makes solid oxide fuel cells), and Nebius (builds whole data centers). Very long, in fact, with leverage reportedly as high as 400%. He tried to hedge this long book by shorting software companies which are viewed as vulnerable to disruption by AI. This strategy worked fabulously for a while. His assets under management (AUM) climbed to $45 billion, with returns in the first 6-7 months of 2026 approaching 400%. Not bad for a 25-year-old.

But then, genius failed (yet again)- -in a stunning reversal, the market rebelled in late July against big AI capex spends, dumping memory fabs and infrastructure, and bought into the maligned software (SaaS) sector. So, BOTH his long and short legs went against him, followed in due course by the dreaded margin calls. Aschenbrenner’s $45 billion shrank to a measly $10 billion in a matter of days, as he was forced to sell off his public equities at a discount to those friendly capitalist sharks at Citadel. Wise old heads wagged, saying, yup, this sort of Black Swan event always happens sooner or later, and you then get carried out on a stretcher if you run a highly leveraged bet that is not truly hedged.

Down, but not out – – The word on the Street is that folks with money to invest are already lining up to entrust more bazillions to our altruistic wizard. We have not heard the last of Leopold Aschenbrenner.