Will The AI Boom End Like The Railroad Crash Of 1873? — ft. Liaquat Ahamed
58m 17s
The episode draws a historical analogy between today’s AI and data center boom and the 1873 railroad bubble, highlighting key similarities such as overbuilding, excessive debt financing, and market crashes triggered by financing failures. In 1873, the collapse of railroad financing after J. Cook’s inability to fund the Northern Pacific triggered a chain reaction, leading to defaults, credit tightening, and a prolonged depression. Today, similar dynamics are emerging: tech firms are financing AI infrastructure with rising debt, interest rates are climbing, and numerous data center IPOs are being delayed. The financial system is under pressure from a speculative boom, with equity markets now 250% of GDP and a growing risk of a market correction. Historical insights show that such crises develop slowly, with financial authorities facing complex policy dilemmas—like monetary restraint or inflation control—when downturns occur. The episode warns that while AI may be transformative, its current build-out risks overcapacity and declining profitability, and that future crashes could be triggered by financing failures, geopolitical shocks, or sudden shifts in investor sentiment. Ultimately, the takeaway is that financial crises evolve slowly and are hard to predict, but their impact can be sudden and severe—emphasizing the need for caution, diversification, and long-term strategic thinking in the face of technological transformation.
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I'm Anna Garten, and each week on Happy Hour, I invite new and old friends for a drink and a fun conversation at my kitchen table in New York City. On this week's episode, I'm joined by Julia Louis-Dreyfus. We talk all about attending a fashion show in Paris together, throwing dinner parties, and making her Broadway debut in other desert cities. New episodes of Happy Hour are available every Wednesday. You can watch on YouTube or listen wherever you get your podcasts. Cheers! Welcome to ProfG Markets. Another AI data center operator just shelved its IPO. That news, along with a growing number of delayed data center listings, is raising questions about investor appetite for these infrastructure assets. And it's also fueling an even bigger question, which is, is the data center boom actually a bubble? As investors try to make sense of this moment, many are turning to history for comparisons, including the railroad bubble of the 1800s. Ben Carlson called it one of the closest historical analogies to this moment. Derek Thompson published a newsletter titled "AI could be the railroad of the 21st century." In a recent Yahoo Finance article warned, "Don't overlook how this moment is also creeping up on the railroad bust in the late 1800s." But how closely does today's AI build-out actually resemble the railroad boom? What happened in the years leading up to the crash? And are we seeing the same warning signs today? To dig into that question, we are bringing in Pulitzer Prize winning author and financial historian who recently wrote a book all about the railroad bubble. Satin Adella called it "The Book to Read Right Now" and noted all of us are reading this. So here is our conversation with Leachet Ahmed, author of 1873, the Rothschilds, the first great depression and the making of the modern world. Leachet, thank you so much for joining us. You wrote that the year 1873 marked the first, you said, "Truly significant global financial crisis," many have called it the panic of 1873. Let's just rewind a little bit. Let's start with the events that led to this crash. How did this boom begin and how did it turn into a bubble? Let's turn the clock back to 1870. The world has been through a 20-year boom. And it's a boom that is the first era of globalization. GDP doubled in those 20 years, trade went up five times. And fueling the boom was a new technology, the railroads. And that was a truly global phenomenon. There was a railroad boom in Europe. There was a railroad boom in the US. And there was a railroad boom actually around the world, in Argentina right around the world. And making this boom possible was an expansion in borrowing through the bond market. The bond market had been invented essentially to finance governments in the early 19th century. And from around 1850, it shifted to becoming the primary financing vehicle for railroads. And most of the money was borrowed. So the $3 billion a year that eventually went into railroads, three quarters of that was borrowed money. So not equities. So that's the lead up. A giant cloud appeared in 1871. And that was war. The most surprising war in the 19th century started by the French emperor, Napoleon Trois, who was the sort of, how shall I put it, he was a celebrity with no coherent ideology, who came to power through the ballot box and then used his power to make himself emperor. So I don't want you to draw too many analogies today, but he was a character. And he launched the most disastrous war in French history when he attacked his neighbor, Prussia, thinking that this is the way that he would dominate Europe. Instead, he was defeated on the battlefield. The Prussians imposed a giant fine on France of a billion dollars, which is equivalent to one and a half trillion dollars today. You would have thought that would have led to the end of the boom. But in the perverse way of financial markets, it actually fueled a sequence of bubbles. The billion dollars that France raised was ten times oversubscribed. And it awoke everyone to the fact that there was this giant amount of money waiting to be invested. And it fueled a bubble in the German and Austrian stock markets. It fueled all of the money that was destined for Europe, went into the US stock market, and fueled a bubble. Or let's just say a boom, there's not calling a bubble for the moment. And also fueled massive, the London stock exchange became a giant casino. So you had three booms going on at the same time. All would separate causes, but all fueled by too much money. Just some of the players who feature in this story two names that I'd like for you to tell us about. One, the Rothschilds, who feature prominently in your book. And also Jay Cook, who were these people and what roles did they play in these investment booms? The Rothschilds in 1873 were the richest family in the world. They had made their money in the early 19th century as smugglers, helping the British if they, the French blockade during the Napoleonic Wars. They became rich, and they had a network, there were five brothers, and they had a network of connections across Europe. Then after the Napoleonic Wars became the primary lenders to governments, as governments in Europe were reconstructing after the Napoleonic Wars. So by 1850, they were the richest family in the world, all from banking. They almost went under in 1848 when revolution swept Europe. But they were bailed out by the French government, and then shifted focus to the railroads. And by 1873, they were the primary lenders to railroads and other infrastructure projects around the world. The one market that the Rothschilds never were able to enter was the US, or decided not to enter. Back in the 1840s, when the US capital market was in its infancy, the Rothschilds lost a ton of money lending to American states for the canal boom. And they vowed after that, because the states were able to claim sovereign immunity, they were never able to recover their investment in canal bonds. And so they vowed not to ever invest in the US market.
They decided it was a frontier market that was essentially a banana republic. So they became the richest family in the world despite having nothing to do with the most successful country of the mid-19th century, which was the US. Their place was taken by a man by the name of J. Cook. He made his fortune during the Civil War helping the Union government finance its war effort. And essentially what he did was take the innovation that the Rothschilds had come up with, which is the bond market, and democratized it. And essentially, financed the Union government by selling bonds in small denominations to households across the North. And it was a brilliant strategy because he tapped into the inherent patriotism of people in the North and raised $2 billion. By the end of the Civil War, he was one of the two or three richest men in the United States. He was talked about as a Treasury Secretary, he was a friend of the Presidents. And he decides to go into the railroad business, the railroad bond business. The first transcontinental railroad had been completed in 1869, the Union Pacific. He decides to lend his support to a second transcontinental railroad, the Northern Pacific, which was going to take a more northerly route from the east coast to right to the west coast. In the early 1870s, he's committed to raising $100 million, or the equivalent today of whatever $100 billion for this railroad. So that's where we stand on the eve of 1873. And then comes the crash, which triggered an economic depression that lasted for around four years, what actually triggered this crash. It started out in Vienna and Berlin when the stock market, which had gone up 300% collapsed. But it was not the main event of that year. The main event was in September of 1873, J. Cook, who everyone assumed could lay his hands on vast amounts of capital, announces that he is not able to complete the financing of the Northern Pacific. Now the analogy today would be if open AI announced that they had committed to raising whatever a trillion dollars, and they were unable to complete their financing. The psychological impact that that had, that everyone assumed that J. Cook was the friend of the president. He knew every banker in Europe, the fact that he wasn't able to complete the financing, had a giant psychological impact on markets. Every railroad company that was trying to raise capital said, "Look, if J. Cook and company can't raise the money, who am I to try to raise capital?" Within three months, railroad construction had ground to a halt. Within a year, a quarter of the railroad companies in the U.S. had defaulted. And it had this massive cascading effect across the market. What was the economic damage beyond drawdowns in the stock market? How was it that stocks going down led to this economic depression that didn't just last a couple of months, but went on for years? The biggest impact was obviously in the bond market, because the stock market, the U.S. stock market at that time, was $1 to $2 billion, it went down 20%, 30%. The bond market was three times as large, and with defaults in railroad bonds, amounting to eventually $1 billion in nominal terms, probably the cost was $500 million, was significant. It was actually oddly enough, not the biggest factor behind the depression that followed. Because superimposed upon this boom bus cycle, we had a giant mistake in monetary policy. And the history of markets is that the economy is surprisingly resilient to boom bus cycles. And when you impose giant mistakes in monetary and fiscal policy on top of that, that you get what one would call a depression. And in the middle of 1873, Germany decides to abandon silver as a basis for its currency and shift to gold. In the U.S., legislation is passed, which omits to include silver as a basis for the monetary system. The combination of those two things leads silver prices to go down by 30%, 40%. Now until then, there were two metals that formed the sort of solid foundation for the monetary system, gold and silver. And every time there was a panic, everyone would gravitate to one of those two metals. With silver prices collapsing, silver was no longer a safe asset. And all of the sort of flight to safety got concentrated into gold. And as a consequence, you got this tightening of credit around the world, just when you were going through a downturn caused by the collapse of the railroad boom. And that is what transformed what was a normal down cycle into a global depression, which caused prices to fall by 30% to 40%. So the big question we're going to have to ask ourselves when we project forward is, are there any giant mistake in monetary policy waiting to happen at this time round? 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- Tom with Code Prof. Chi. - Are you tired of hearing about business, tech, and finance from the bros? We are the Tiger Sisters, a top business podcast with the Vox Media Podcast Network. Tiger Sisters releases every Monday and we decode money, power, and love. - And who doesn't love all those things? - We are the internet's Wall Street and Silicon Valley big sisters. - Tune in every Monday for late night sister talk meets boardroom strategy. Check out Tiger Sisters on YouTube, Spotify, or wherever you get your podcasts. - Welcome to the Tiger Fam. - We're back with Profty Markets. Well, this is, I think, probably a good place to start making the comparisons. I guess I'll just start with a pretty general question, which is obviously we're seeing a massive data center build out today, I think that the data center would be the analogy to the railroads. Do you think that this is an apt comparison? We'll dig into it more specifically, but on a general level, do you think that this comparison makes sense? - Yes, very much so. Because the key risk in the data center boom is over building and over building finance by debt. Until recently, the bulk of the money going into data center construction was from hyperscalers and it was being financed out of earnings. But the scale of the construction boom in data centers is been so large that the resources of the large tech companies has not been enough and they've turned to financing through debt. And what makes it particularly worrying is that much of this debt is quite opaque. We don't actually know how much debt there is. At the center is a company like Nvidia, which is essentially lending to its customers. It doesn't call it lending, but it is a form of lending. And so we don't really know how much of the construction is being financed by debt. So that's the first sort of comparison. The second is by 1873. It is clear that there has been over building. And it shows up in the form of excess capacity on railroad lines and erosion in profitability of railroad lines. So by the end of 1872, only a quarter of the railroad companies are able to pay dividends. And I suppose the analogy today is all of this data center construction leading to a fall in the prices of their output, which I suppose is tokens and token prices are going down. So that's the second analogy. And then the third is because of a collapse in the stock markets across Europe, not related to data centers, but just related to a stock market bubble. It leads to financing problems for railroad companies that they begin to have to pay up to issue bonds. And until then they've been borrowing at five, six percent, now that spikes up to nine percent. So the combination of over building erosion and profitability and constraints in financing show up at the end of 1872, beginning of 1873. And the question we have to ask ourselves is those three things appearing today? Why was this pervasive problem of over building when it came to railroads? Why was it that the railroad companies couldn't accurately assess the demand for this new technology that was actually transformative and did change the world for the better. But still we say that they overbuilt because they didn't have a business model that made sense and they had to look back and say, okay, we made a mistake here. So why was it that they landed in that position of over building? A few months ago, they are Satya Nadella, who's the CEO of Microsoft. How are you gonna prevent over building? And very kindly he referenced my book and said, everyone's reading this book. And what we're gonna do is be very careful. And I think he got the wrong end of the stick because each individual railroad company in the same way that each individual tech company is trying to be careful. It's the collectivity of their decisions that leads to over building because what it would require to prevent over building, it would require some sort of collective action. And you have something of a prisoner's dilemma here that each one thinks I'm gonna be the one to get on top. So I would be giving up market share if I slowed down my construction. But the problem is you add all of their individual decisions up and you end up with an over building boom. Is there a solution to this? Probably not. I mean, I think it's just inherent in the competitive situation that everyone wants to be one of the two or three companies that comes out on top. Does that essentially mean that whenever a new technology comes along that is transformative, that there will inevitably be a crash at some point? There have been four or five private investment booms in U.S. history. The 1870s, which by the way was actually three mini booms and buss. So there was one in the 1870s, there was another one in the 1880s, and there was another one in the 1890s. So the railroad boom was actually three booms and buss. The 1920s, when private investment jumped by 5% of GDP for a few years, the dot com bubble of the late 1990s, the real estate bubble of the mid 2000s, all of them led to a jump in private investment of two to four percent of GDP. All of them lasted two to four years. All of them ended up with excess capacity. And all of them, interestingly, ended up with a spike in interest rates, as everyone was competing for capital in the final stages of the boom. And all of them ended up with a crash. Will this time be different? You know, I'm answering, that's a rhetorical question. I guess the question then becomes timing. When would it all unfold if we believe that this is just what happens? You have technology booms and then suddenly, there's over capacity and we all look around and we suddenly lose confidence and it crashes. Just looking at what happened during the railroad boom, leading up to the crash, based on some of the data in your book, more than three quarters of railroad construction was financed with debt leading up to the crash. You mentioned that there is a lot more debt being issued to build data centers and to fund the AI build out. But I don't think it's that high, am I correct? And if so, then perhaps we have more room to run. The data center boom has been going, let's say, for two years. We've had booms go on for four years. So we could be halfway through the process. So, you know, there is almost nothing in history that allows you to pinpoint the timing. I can't be any more precise than that. They, the size of the private investment booms were anywhere from two to four percent of GDP. In fact, in 1873, it reached five percent of GDP. This current boom is not at five percent of GDP. With, you know, next year, we're projected to put in, I don't know, one and a half trillion dollars, that's probably. 4% of GDP, 3% to 4%, we're not at the sort of extremes that we've experienced in the past. Why is it that we should be looking at percentage of GDP as a metric for whether we're at the top? Like, what is it about that measurement that makes it relevant and important in terms of predicting crashes? You get a series of knock-on effects of these private investment booms. Essentially, it starts crowding out all other forms of investment. And we're already beginning to see the stock market is overwhelmed by AI. It's become the one story. It's actually become a global story. It also causes this sort of limited capacity to finance more than 3% to 4% of GDP in one go. And you're beginning to see that in the form of the spike in interest rates, interest rates have risen whatever, 150 basis points in the long end in the US, even more in other countries. And that's what you typically get. It shows up because these booms absorb such a large percentage of the world's savings that it causes interest rates to spike up, which causes all sorts of knock-on effects in terms of default rates on other things. So we have interest rates rising. It appears that we are going into a rate hiking cycle, of course, yields are soaring to levels that we haven't seen in decades. We've also seen some smaller signs that might be predicting that perhaps we're about to enter the correction. For example, a lot of these data centers that were supposed to go public are now delaying their IPOs in some cases they're just deciding we're not going to go public at all. There was an AI startup recently that filed for bankruptcy. I guess when you look at today and you compare it to 1873, what were some of the warning signs that appeared before the crash? And to what extent do they mirror any of the red flags that we're seeing today? I don't want to be mechanical about it because history is full of random effects. But one of the factors that caused Jay Cook and company to not be able to complete his financing was his railroads ran into the wars against the Indians. And the Sue and sitting bull and all of those sort of his goal to complete the Northern Pacific ran slap up against a war in the Northern territories. I suppose the modern day equivalent is the political protest against the construction of data centers. So it's not sitting bull, but it's a lot of people not wanting local communities exactly. So, you know, there's always sort of some random effect that actually adds a little more color to the story. So that's one of the things I would worry about. And I've never quite got my head around how what the how you measure the output of these data centers. But the other big factor is the erosion of profitability. And I don't know how you measure that, whether there is an erosion of profitability, whether the demand for tokens is inexhaustible. But, you know, that's where I would start looking for trouble. Yeah, it appears at least thus far that none of the large language model companies have demonstrated an ability to become profitable at least at any point in the near future. It appears that the entire build out is currently being financed with, I mean, first with the cash flows of already profitable companies, but now increasingly not because now they're cash flow negative. So now increasingly debt. And so I guess the question becomes like, at what point do they run out of capital? It seems like a race to sustain your own business with your own profits before capital becomes too expensive. Is that essentially what happened in the railroad boom as well? Well, yes, one of the most quoted lines in Hemingway is one one person asked another, how did you go bankrupt and the other person replies two ways slowly and then suddenly. And there's an adage in economics, which is these financial crisis go on, they take much longer to happen than you imagined. And when they happen, they happen much faster than you thought they could. And that essentially reflects the sort of inherent uncertainty of the timing that, and you think back on 2008, you think back on 2000, you think back on 1929, no one was, no one was able to forecast the timing. And for the longest time, people were predicting this is going to go, this is going to get into trouble. And for the longest time, they were wrong until they proved to be right. So that's the only lesson that you can draw from history, which is that these things go on for longer than you imagine and they went once they happened, they'll happen much quicker than you thought they could. Are there any winners coming out of the railroad crash? Was there anyone who navigated it correctly and came out on top? I mean, in Europe, the Rothschilds were brilliant. They had become rich by avoiding fads. So they avoided any of this. But in the US look, there were plenty of people who became rich once the crash had occurred, because they were able to scoop up cheap assets at a, you know, at bargain basement prices. Morgan was one of them. He inherited the mantle of Jay Cook and became the most powerful banker in the US. There were other people who scooped up the sort of bankrupt railroad companies in the, in the middle of the crisis and, and became very wealthy as a consequence. There will be, there will be winners who pick picking up the pieces. We'll be right back and for even more markets content, sign up for our newsletter at profgmarkets.com. Support for the show comes from fair. It's a busy time for shopkeepers. 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The economic boom that has become self-sustaining in the last two years is in part fueled by wealth effects from the rise in equity prices. And that has not been a factor in the past. In 2000, the equity market was half the size relative to GDP. And the worrying thing is, if the equity market takes a tumble, what will be the wealth effects of equities going down on consumption? So that's the first thing, and it's hard to see how the Federal Reserve is able to navigate that. We've got a budget deficit that's at 6% of GDP. We probably run out of bullets in terms of fiscal policy. If they try to ease, I suppose the second big worry is that a trillion dollars has gone from foreigners into the US equity market in the last 12 months. If that turns tail, and there's a flood of money out of the US dollar, what does the Federal Reserve do? Because if the dollar starts going down, it poses a big challenge for the Federal Reserve. If they ease, do they risk exacerbating the fall in the dollar, which then causes prejudices their inflation goals? So I can see a whole series of scenarios or dilemmas that the monetary and fiscal authorities will face in the next downturn, but that they haven't faced in the last couple. The IMF said that an AI market correction was the top risk to the financial system today. They said that this week, a weaker AI investment and profits could be a shock that triggers a market correction. Do you agree with that analysis that of all of the things that might cause problems in the financial markets today that AI is number one? Yes, and I would go a step further, which is until now, we've always relied on the financial authorities to flood the zone, if you like, in a financial market crisis. Have we run out of bullets? Oh, that's probably not the right analogy for flooding the zone. But whatever, have we run out of water to flood the zone in a financial crisis? And, you know, I don't know the answer to that. I don't think anyone does. We'll see where we end up. We spoke to Andrew Ross Sorkin last year after he released his book about the 1929 crash and all that ensued thereafter. And we were discussing this idea of are there parallels to the crash, then, to potentially and the boom that led up to it to today? Is there a crash? Is there a boom bust cycle that you think most resembles today? Is it 1873 in your view? Why is it more similar or less similar than 1929? What do you think is the most opt analogy? I think 1873 is a pretty good analogy, but just look, every, you know, every boom bust cycle is different and every boom bust cycle has elements that can be analogized to the next one. So, yeah, I can see lots of analogy with 1929. At that point, everyone was constrained in what they could do on monetary policy because they were all tied to the gold standard. And they felt they couldn't ease. And that made the crisis much worse. This time round, no one's tied to the gold standard, but are we tied to keeping inflation under control? Does that make the knock on effects much worse? So, yeah, your guess is as good as mine. You mentioned earlier that when we were talking about J. Cook and how he was, you know, financing this build out and he was the largest finance of the build out. And then suddenly one day he says, I actually don't have the money to do this. And suddenly there's a crisis of faith. And you made this connection between J. Cook and OpenAI who have, of course, said that they're going to be spending somewhere around a trillion dollars on various commitments with various companies in order to build our AI infrastructure. And I mean, there's debate as to how real that number is, whether they meant it, how locked in it is. Either way, you made the connection. When you look at some of the players in AI today, OpenAI, Nvidia, Anthropic, maybe Google, maybe Microsoft, are there any characters in the 1873 story who you think make perfect analogous links? If I were to write a book about today, you know, who would be J. Cook? I don't know whether it's Anthropic. I don't know whether it's OpenAI. I do think there is a sense of hubris that is sort of just astounding in markets. And the hedge fund, I'm blanking on its name, but it went under. Yeah, Ash and Brenner, situational awareness. Yes, I mean, that was a perfect example of someone just, you know, having no sense of where this thing could end up. So I think we've got plenty of examples of crazy magical thinking that permeates the whole financial market. If an AI executive were listening to this, let's say the CEO of one of the big tech companies or someone who's high-up at Anthropic or OpenAI, say they're listening to this and they agree with you that this is the cycle. What is there to do about it? Like, is there anything that you can do to protect yourself or to maybe alleviate whatever damage may or may not be inevitable? I mean, what are we supposed to take away?
from history here. I mean, first of all, it depends whether you think AI is a transformational technology that will transform, you know, the way businesses operate and so that's the first and, you know, I have one day, I think one thing, one day, I think the other. But then, presumably, there is a company, and I don't know whether it's Apple, which can say to itself, look, we feel confident enough in our ability to pick up the pieces after the whole thing has shaken out and utilize that opportunity to sort of go to the next stage. So the equivalent of the JP Morgan of this era, and I'm not sure you have to have a lot of self confidence to say, I'm going to sit this one out and that I'm going to let everyone else get themselves into trouble. And then I'll be, I'll be around to pick up the pieces. Do you believe that the current market environment is frothy, that it is speculative? When you look back at the railroad boom, you know, presumably, there was a moment where it made sense and then things started to get out of control. There was too much debt, there was too much speculation whereabouts in that cycle do you believe we are in this moment? Or is it too hard to tell? We're definitely in the manic phase. I mean, I, you know, 1871 was maybe the point at which you could have said, you know, this is perfectly rational and it's, it's reasonable by 18, by the end of 1872, we'd exceeded all, all, all bounds. So I'm sure that we have entered the manic phase now. Could it, as I said, I think it could go on for another year, two years until 1927, the stock market went up, but so did earnings. It was perfectly rational until 1927 to believe there had been a transformational change. It took another two years and another hundred percent in the stock market for it to transform itself. So I'm certainly not smart enough to figure out where exactly we are. But these things, I go back to the adage that I, these things take much longer to play out than you imagine. How do you imagine a crash might play out? What are some of the things that you think would take place if we saw something happen to AI similar to what happened to the railroads? One of the major players will face financing problems, you know, will it be oracle? Will it be open AI? You know, who among these will face will suddenly, you know, will suddenly not be able to raise the capital. So that's one thing. And so I think that will come as a giant shock across the market. Will there be competitive pressures from, I don't know, open models produced by the Chinese that suddenly causes a mass erosion and profitability. So that's another source. And then, you know, don't discount geopolitics. In 1870, you know, the 1870s, the wild card was the war between Prussia and France. In 2008, a potential wild card was wild, wild, Hank Paulson, the Treasury Secretary was in, was in Beijing for the Beijing Olympics. He heard a rumor that the Chinese, that the Russians had approached the Chinese and said, let's collectively sell all of our agency bonds and bring the US down to its knees, just when it's down. Could some geopolitical wild card intervene? I don't know. I mean, history is way too exciting to be able to predict everything. Well, Leaket, we really appreciate your time. Just my final question, you have experience in financial markets as an investment manager, you're also a financial historian. I personally love history, and I'm always looking for reasons to say why it's important to understand it. I'd like to hear from you, what drew you to history and how has it informed your perspective on the world and on the markets? What drew me to history was losing a ton of money in the Asian crisis. So, God, it seems like a, you know, 30, 1997, 1998. And I thought, God, I should read up about past financial crises and what happened then was that a time magazine ran a cover story with Larry Summers, Bob Rubin and Alan Greenspan on the cover, the committee to save the world. And I thought there was just such a wonderful frame for telling a story about a financial crisis. So, that's what drew me to my first book and finding a way to tell a giant macro story through individuals is what I find fascinating. We are at Ahmed is a financial historian with degrees in economics from both Harvard and Cambridge universities and over two decades of professional experience as an investment manager. His previous book, Lords of Finance, The Bankers who broke the world was awarded a 2010 Pulitzer Prize. Ahmed is the board chair of the Sun Valley Writers Conference, a trustee of the Putnam Funds and a trustee emeritus of New America Foundation and the Brookings Institution. His new book, 1873, The Rothschilds, The First Great Depression and the Making of the Modern World is available now. Leachet, thank you so much for your time. Thank you, Ed. Spend a lot of fun. This episode was produced by Claire Miller, and Alison Weiss, and engineered by Benjamin Spencer. Our video editor is Jorge Carty. Our research team is Dan Shalan, Cristino Donahue, and Measel Vario. Jake McPherson is our social producer. Drew Burrows is our technical director and Catherine Dillan is our executive producer. Thank you for listening to Profty Markets from Profty Media. If you liked what you heard, give us a follow and join us for a fresh take on Markets on Monday. [Music]
Podcast Summary
Key Points:
The data center boom is being compared to the 1873 railroad bubble due to overbuilding, rising debt, and erosion of profitability.
Historical lessons from the 1873 crash show that financial bubbles often result from excessive debt, speculative investment, and monetary policy mistakes.
Key parallels include the collapse of railroad financing after J. Cook’s failure to fund the Northern Pacific, mirroring current concerns over OpenAI or Nvidia’s financing commitments.
Today’s market shows signs of over-leveraging, with AI-related debt growing opaque and interest rates rising, signaling possible financial stress.
The 1873 crash was compounded by a shift in monetary policy—abandoning silver—leading to credit tightening and prolonged depression.
A major warning sign today is the delay or cancellation of data center IPOs, reflecting loss of investor confidence.
Winners in past crashes, like J.P. Morgan, emerged by acquiring distressed assets, suggesting similar opportunities may arise in a future AI correction.
History shows financial crises unfold slowly, with a sudden crash once triggered, and current markets may be in a speculative, manic phase that could last years.
Summary:
The episode draws a historical analogy between today’s AI and data center boom and the 1873 railroad bubble, highlighting key similarities such as overbuilding, excessive debt financing, and market crashes triggered by financing failures. In 1873, the collapse of railroad financing after J. Cook’s inability to fund the Northern Pacific triggered a chain reaction, leading to defaults, credit tightening, and a prolonged depression.
Today, similar dynamics are emerging: tech firms are financing AI infrastructure with rising debt, interest rates are climbing, and numerous data center IPOs are being delayed. The financial system is under pressure from a speculative boom, with equity markets now 250% of GDP and a growing risk of a market correction. Historical insights show that such crises develop slowly, with financial authorities facing complex policy dilemmas—like monetary restraint or inflation control—when downturns occur.
The episode warns that while AI may be transformative, its current build-out risks overcapacity and declining profitability, and that future crashes could be triggered by financing failures, geopolitical shocks, or sudden shifts in investor sentiment. Ultimately, the takeaway is that financial crises evolve slowly and are hard to predict, but their impact can be sudden and severe—emphasizing the need for caution, diversification, and long-term strategic thinking in the face of technological transformation.
FAQs
The AI and data center boom is compared to the 1870s railroad boom due to overbuilding, excessive debt financing, erosion of profitability, and rising interest rates. Both periods saw massive private investment driven by speculative confidence and a lack of accurate demand forecasting.
The crash began with a stock market collapse in Europe after a war between France and Prussia, which led to massive financial inflows. This fueled speculative booms globally. When J. Cook, a key financier, failed to complete funding for a railroad, it triggered a loss of confidence, halting construction and leading to defaults and a prolonged economic depression.
In both periods, a significant portion of construction was financed through debt. In the 1870s, over three-quarters of railroad financing was borrowed; today, data centers are increasingly financed through debt, especially as tech companies face cash flow shortages and rely on debt to fund expansion.
Yes—signs include delayed or canceled data center IPOs, declining token prices, rising interest rates, and struggles of AI companies to become profitable. These mirror the 1873 signs of overcapacity and financial strain in the railroad sector.
Yes—such a failure could trigger a market-wide crisis of confidence, as J. Cook’s inability to raise funds halted railroad construction. A similar failure by a major AI player would signal a breakdown in trust and could lead to a broader market correction.
Yes—rising interest rates and a shift in global capital flows could exacerbate a downturn. Past booms were worsened by monetary policy mistakes, such as abandoning silver or restricting currency flexibility, which may repeat today if inflation or capital outflows become unmanageable.
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