What We’re Reading (Week Ending 12 October 2025) - 12 Oct 2025
Reading helps us learn about the world and it is a really important aspect of investing. The late Charlie Munger even went so far as to say that “I don’t think you can get to be a really good investor over a broad range without doing a massive amount of reading.” We (the co-founders of Compounder Fund) read widely across a range of topics, including investing, business, technology, and the world in general. We want to regularly share the best articles we’ve come across recently. Here they are (for the week ending 12 October 2025):
1. GDP’s absurdity – Abdullah Al-Rezwan
To understand the flimsy nature of such belief, we first need to understand the nuances around calculating GDP:
Discourse over GDP is frequently confused because there are actually three different calculation approaches: the income approach, the expenditures approach, and the value-added approach.
Each approach has its uses, but you have to be careful with which you use. What percent of GDP is healthcare? You get two different numbers depending on the approach. With the expenditures approach, healthcare is 17% of GDP, but for the value-added approach only 8%. Why? Because the value-added approach only counts expenditures on hospital and clinic workers toward the healthcare category. Money spent on manufacturing medical devices counts as manufacturing; money spent building hospitals counts as construction. For measuring healthcare’s share of the economy, it is probably better to use the expenditures approach because it is reasonable to include pharmaceutical production and hospital electricity bills as part of healthcare.
GDP is a very complicated statistical construct that is made by government bureaucrats behind closed doors without any ability of the public to replicate, audit, or verify assumptions. Sometimes, these kinds of constructs can be useful for accurately representing real-world phenomena, like manufacturing capacity. But a dive into how the sausage is made makes clear that GDP is not one of them.
So, how is the sausage made here? It is particularly striking to take a look at manufacturing:
If you want to see what percent of the economy is manufacturing, and how that has changed over time, you can only use the value-added approach. Only the value-added approach separates out each step in the economic chain: from mining the iron ore to transporting it to the factory to manufacturing the product to selling it at the store. The value-added approach categorizes each step, so you can sum together just the increase in price from the manufacturing step across all categories of spending.
2. This Is How the AI Bubble Will Pop – Derek Thompson and Paul Kedrosky
Thompson: How do you see AI spending already warping the 2025 economy?
Kedrosky: Looking back, the analogy I draw is this: massive capital spending in one narrow slice of the economy during the 1990s caused a diversion of capital away from manufacturing in the United States. This starved small manufacturers of capital and made it difficult for them to raise money cheaply. Their cost of capital increased, meaning their margins had to be higher. During that time, China had entered the World Trade Organization and tariffs were dropping. We’ve made it very difficult for domestic manufacturers to compete against China, in large part because of the rising cost of capital. It all got sucked into this “death star” of telecom.
So in a weird way, we can trace some of the loss of manufacturing jobs in the 1990s to what happened in telecom because it was the great sucking sound that sucked all the capital out of everywhere else in the economy.
The exact same thing is happening now. If I’m a large private equity firm, there is no reward for spending money anywhere else but in data centers. So it’s the same phenomenon. If I’m a small manufacturer and I’m hoping to benefit from the on-shoring of manufacturing as a result of tariffs, I go out trying to raise money with that as my thesis. The hurdle rate just got a lot higher, meaning that I have to generate much higher returns because they’re comparing me to this other part of the economy that will accept giant amounts of money. And it looks like the returns are going to be tremendous because look at what’s happening in AI and the massive uptake of OpenAI. So I end up inadvertently starving a huge slice of the economy yet again, much like what we did in the 1990s…
…Kedrosky: The market is rewarding [the big tech companies] for investing in AI even though it makes no economic sense to spend at this level because there’s no way they can recoup the value of the capital spending over the next three years. So they’ll be forced to do these kind of wacky shell games where they say, “Well, the building itself will actually be valuable in five years, because it’ll still have energy, it’ll still have water, it’ll still be able to cool things, the walls will still be standing, and I’ll just swap out the GPUs.” But the problem is the GPUs are the majority of the cost. The shell is the thing I’d like to write off, since I don’t want to have to write off GPUs every three years. But they’re the majority of the cost of what we call a data center.
Unlike telecom, unlike the fiber boom, unlike in railroads, there are actually two assets here. One that’s long-lived, a building, which is essentially a small fraction of the cost of the center; and one that’s very short-lived, which is the GPUs, which are the thing we’d like to have last and don’t, yet represent as much as 60 percent of the cost of the data center. So there’s the perversity.
Thompson: I want to talk about how some of this might go badly in the next few years, and I want to preface that discussion by saying that when I talk about AI as a bubble, I think some people see me as being pessimistic about the technology. The railroads were a bubble. There was a panic of 1857, of 1873, and of 1893. There were constant railroad depressions, and also the railroads changed the world. Broadband was a bubble, it also changed the world. Big infrastructure buildouts that changed the world often passed through a bubble phase. So it’s not pessimistic to say that AI is currently in a bubble. You could say it’s actually historically in tune to say that we are very likely in the middle of a bubble, because every industrial revolution passes through bubble phases.
Let’s start here. How close are the hyperscalers—Meta, Google, Microsoft, the big boys—to getting AI revenue to match AI spending?
Kedrosky: Nowhere near.
The hyperscalers are spending as much as 50 percent of income on capital expenditures, which is unprecedented. This doesn’t happen. Normally, if I did that as Microsoft or Amazon, I would be taken to the woodshed and beaten by investors because that’s such an incredible investment on one narrow slice of CapEx. They’re not being punished for that.
What I’m watching is how they’re moving the financing off their balance sheet. That for me is a reflection of not wanting the credit rating agencies to look at what they’re spending. What we’re seeing is these SPVs— special purpose vehicles—being created. Meta has a stake, some giant private debt provider has a stake, and the data center at the end is under Meta’s control, but they don’t “own” it. And so it doesn’t go on their balance sheet in terms of assessing creditworthiness. We’re seeing for the first time over the last six, seven months, the beginnings of a wave of these special purpose vehicles and other more exotic financing structures. We’re seeing the equivalence of some of the old collateralized debt obligations emerge. These are all, for me, the beginning of the sign that the bubble is becoming tired because the market is beginning to punish—at least there’s a perception that the market will punish—if I continue to keep this on my income statement. So I move it somewhere else. And that makes the entire process much more opaque. That’s the thing to watch. How hard are they trying to hide the expenditure?
3. Why Warm Countries Are Poorer – Tomas Pueyo
Societies that live closer to the equator are warmer. Why are they also poorer?…
…Here’s the kicker—I’m so excited about writing this, I have a huge grin on my face right now: We did not evolve in such warm places, and humans in warm countries don’t live where you think they live!…
…Lisbon, the capital of the first global empire of the West, actually gets warmer than Nairobi! Nairobi’s temperature is not that high, and is quite stable throughout the year…
…The answer is obvious when you think about it: The higher you are, the cooler the temperature. Normally, temperatures decrease by ~4–9ºC every 1000 meters higher (2 to 5 °F/1000 ft). Since Bogotá is at 2,600 m of altitude (8600 ft), its annual temperature is 14ºC (25ºF) cooler than Barranquilla, which is farther north from the equator but at sea level, on the coast.
Bogotá was created far inland in the mountains in 1538, only a few decades after the Spanish discovery of America. The colonizers had a much harder time with disease and conflict in coastal flatlands. It was worth traveling hundreds of miles inland and up thousands of meters to survive. That region is agriculturally much better than the sea-level flatlands too, because of the same lack of disease and the soil that doesn’t get leached as much. This logic is true of all three main Colombian cities: Bogotá (12.7M people), Medellín (4.4M) and Cali (4.2M) are all in the mountains…
…Arguably, civilization would have had a much harder time developing in the Americas if the land had been much flatter and low-lying. It’s not a coincidence that the Incan Empire was a mountain empire and was the only independent one in the world to form on the equator!
Even today, the Latin American population concentrates in the Andes!…
…So the trend is clear that, closer to the equator, people tend to live in higher altitudes. What are the consequences of that?…
…Mountains mean people need to travel up and down mountain passes and huge slopes to get anywhere. They mean no navigable rivers. They mean much higher costs of infrastructure, so there’s much less of it. This means transportation costs are much higher…
…This, in turn, means there’s dramatically less trade, and so less money is made, and less wealth accumulated. We’ve seen how these facts have dramatically impoverished countries like Mexico and Brazil, and the generic process in A Science of Cities…
…The other thing that happens with mountains is conflict. As transportation costs are so much higher, people don’t move as much from their valley. There’s substantially less regional integration, and people trust and like each other less. They develop their own independent customs and mistrust those of their neighbors. This leads to more conflict between valleys, regions, and countries.
This process is called Balkanization, for the mountainous Balkans in Europe. But we also see it in Mexico’s and Colombia’s cartels—in fact, nearly all cartels in Latin America are in the mountains. We saw it in Iran, a highly mountainous country that requires a very strong state suppressing dissent to keep the country together…
…The pattern, and its logic, is unmistakable:
- Humans evolved in the African highlands, where temperatures are stable throughout the year, and close to that of spring & fall in temperate regions. This is why we feel most comfortable there.
- Close to the equator, if we’re not in the mountains, the temperatures are too high for us. We can’t think or work properly because we overheat, and our sweat can’t cool us off because humidity is too high.
- We also suffer from many more diseases, more common in hot moist climates, but also because we didn’t evolve there.
- This also affects food, as agriculture is much harder in these hot moist climates, given the pests, the speed of rot, and the work required by crops.
- This prevented maladapted Westerners from efficiently transferring culture and institutions to these hot, humid, low-lying areas, yet another way these regions suffered.
- In order to avoid all that, people close to the equator tend to live higher up, in mountains, where temperatures are cooler and the dew point is lower, allowing people to cool down with sweat when necessary.
- The big tradeoff for this comfort though has been much higher transportation costs, so less trade, so less wealth.
- This also leads to much more ethnic diversity.
- This diversity breeds conflict, which makes everybody poorer.
- Ethnic diversity and conflict also mean institutions are much harder to make and keep.
This is how mountains are the most significant underdiscussed topic in economic development, and how they must be considered to better explain why warmer countries are poorer.
4. How Misleading Headlines Frame the Narrative – Michael Batnick
The Financial Times recently ran a story on pension funds and private credit with the headline, “US public pension funds pare allocations to private credit. Pullback highlights concerns about looser underwriting standards and rising credit risks.”
On the surface, it was about institutional investors growing cautious on the booming asset class. But look closer, and you’ll see something more telling about the way news gets written — and consumed.
The article opens with a small pension fund in Cincinnati that has tapped the brakes on private credit. The narrative builds around skepticism, risk, and pullback. Only at the very end do readers learn that the New York City pension fund — with over $300 billion under management — is fully committed to private credit. In other words, the story’s most significant character wasn’t just positive on the space, but “all in.”…
…For investors, policymakers, and the public, this matters. Media framing shapes how we understand markets, risk, and opportunity. When negativity consistently drowns out proportion, we risk making decisions based on skewed perceptions.
And for society at large, the same forces are at play. Politics, economics, health, culture — the most pessimistic interpretations tend to dominate. Not because they’re always right, but because they’re the most clickable.
5. A Sleepy 5x – Joe Raymond
In my experience, stocks with the following characteristics tend to do well on average over time:
- Boring businesses with long histories of profitability
- Clean balance sheets (more cash than debt)
- Honest insiders (even if they aren’t terribly talented)
- Trading cheaply (say, 5x EBIT or less)
Once in a while one of these sorts of stocks might do poorly. But in aggregate, this group does tremendously well – at least in my experience and based on conversations with many other investors…
…Bryan Steam Corporation (BSC) was founded in Peru, Indiana way back in 1916. The company started out making steam-powered cars and tractors…
…By the mid-1920s, it was clear that gasoline powered engines were winning out over steam in automobiles. BSC switched course and focused on boilers and related steam equipment, rather than vehicles.
And that’s basically what the company did for the next 80 years…
…1993 is the earliest year I have data, so that’s where we’ll start. This was around the time my friend was buying shares…
…Growth was modest and choppy, and the operating margin fluctuated between 5% and 10% depending on activity levels. ROE in most years came in somewhere between 7% and 12%.
These are extremely pedestrian numbers.
Most investors wouldn’t have been excited to sit on the bid and patiently build a stake in Bryan Steam. Sure, it was cheap, but it had single-digit margins and single-digit ROE most years. Growth was lackluster. The dividend yield was a mundane 3%…
…But, if you think about it, what was the risk buying BSC at $30 in 1993?
You were paying half of tangible book value. The balance sheet was net cash. The company had a multi-decade history of profitability. Earnings could be cut in half, and you’d still only be paying 10x profits…
…Bryan Steam grew revenue from $16.4 million in 1993 to $26.2 million in 1998 (9.8% CAGR). Cumulative earnings over the period were $6.5 million, which was more than the entire $5.7 million market cap in 1993.
Book value per share grew from $58.84 to $78.50 (5.9% CAGR). The company also paid $8.45 per share of total dividends over those five years.
These are “good, not great” numbers.
Yet the stock finished 1997 trading for $58.25 (18% CAGR before dividends from the 1993 price of $30). And it still traded for only 77% of TBV and less than 7x earnings…
…In September 1998, Bryan Steam entered into a merger agreement with Burnham Corporation (OTC: BURCA/B).
The price?
$152 per share…
…My friend who bought BSC in 1993 at $30 earned a 44% IRR, including dividends. More importantly, he did it without taking a whole lot of risk…
…What if Burnham hadn’t come in and offered $152 per share?
Remember, BSC had compounded at 18% over the prior four years before Burnham entered the picture. And the valuation was still sub-1x book value for a decent (7-12% ROE) business.
Let’s say there was no acquisition and Bryan Steam kept plugging along at its prevailing pace, compounding book value at 6% for the next 20 years.
By 2018, BVPS would have been north of $250 per share and annual earnings would have been around $25 per share. At 12x earnings, BSC would be worth $300 per share.
This results in a hypothetical 10% annualized return over the 25-year period from 1993 to 2018. Including dividends, the IRR would have been in the neighborhood of 12-13%.
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have a vested interest in Alphabet (parent of Google), Amazon, Meta Platforms, and Microsoft. Holdings are subject to change at any time.
