bubbel trubbel – Paul Krugman

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A conversation with Jared Bernstein and Jason Furman

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TRANSCRIPT:
Paul Krugman in Conversation with Jared Bernstein and Jason Furman

(recorded 11/12/26)

Paul Krugman: Today I’m talking with Jared Bernstein and Jason Furman, both of whom have been writing, as I have, about AI. Is it a bubble? If it is a bubble, what happens when it bursts? What’s it doing to the economy? All things AI. Hopefully, we can stay off of honeypots for the most part. But is it a bubble? I am surprisingly uncertain in my own judgment here. So, we can talk about the scope of it, but what can we make of this huge, huge investment in a very new technology?

Jared Bernstein: Well, when I’m being disciplined, I describe it as probably a bubble. I should start out by saying almost everything I’m going to say for the next X minutes is going to be speculative. And also, I’d like to underscore that, for all my concerns about a bubble and a bubble bursting, I think AI is likely to be a significant productivity enhancer, perhaps even transformational in that regard. So I don’t want to lose that. But in terms of your basic question, my work on this is with Ryan Cummings, and we started sniffing a bubble in the sector over a year ago, and we had a piece in The New York Times to that effect. We thought that the gap between the spend of the hyperscalers and the labs—the actual spending that they were doing and the expected spending—the gap between that and plausible earnings projections suggested bubble dynamics. So in later work, we were able to roughly quantify that gap. And others did a similar exercise. And I know you, Paul in particular, you’ve written about that. There’s a Brookings paper on this, which further raised our bubble antennae.

Actually, at this point, the diagnosis is pretty widely agreed upon, although there are doubts. And I share yours as well, Paul, with the added worry—now, this wasn’t quite there when we first started writing in October of last year—of leverage, that is. A lot of the spend was initially financed through cash flow. And some of these companies have big cash flows—not the freestanding labs, but the Metas and the Amazons—and now there’s the added worry of leverage because there’s so much more borrowing.

Last point on this: I do think it’s a good question for people who have the position I have as to whether you’ve personally divested in the sector. And I will say that I partially have, in that there is no SpaceX in my portfolio at this point in time.

Krugman: Let me ask you, Jason, for your take. I have some thoughts also.

Jason Furman: Well, first of all, I’ll do the investment advice first. All of my financial assets are basically in Vanguard Global ETF. So I have every single company on the planet Earth, or at least I aspire to have every single company on planet Earth. And so in that sense, I think with the sort of “your money’s where your mouth is” test, I’m implicitly saying it’s not a bubble.

I wake up different days taking different sides of this argument. It doesn’t feel like this is the type of network that previous technologies were—like Google Search becoming the best, or Facebook becoming the best. Everyone basically needed to use it, and they could end up with, in the case of Google, 90% of the search market. For this, I can use Claude, you can use ChatGPT, and I know Jared is just obsessed with Grok—maybe I wasn’t supposed to tell people that, Jared?—but it all works just fine. Moreover, if you go to Claude and say, “The bills are too high, what should I do?” it’ll say, “Try ChatGPT, and here’s a file to download and instructions for how to upload it to ChatGPT.” So there just doesn’t seem to be anything keeping people on these.

Moreover, the more they improve, the more for most purposes you can use older models. It’s like cars that used to go 200 miles an hour and now they go 1,000 miles an hour. For race car drivers, that’s a great thing; they want the latest car. For most of the rest of us, the old one is perfectly fine. So that is the “it’s a bubble” story.

On the other side, though, I have two reasons why I’m cautious about going too far with that. One is, I first personally called the Tesla bubble in April 2017. That is when Tesla’s market cap exceeded both Ford and General Motors. At the time, Tesla was making fewer than 100,000 cars, and these other companies were making like 10 million cars. And it seemed insane to me. It seemed like a massive bubble. Tesla’s up about 2,000% since I made that bubble call. And yes, it may collapse one day, but there’s no collapse that’s going to make me correct in my April 2017 call. And that’s happened over and over again with people.

And then the second thing that gives me pause is small probabilities of infinity, which is: you don’t need that high a probability of Anthropic taking over everything in the world to justify its valuation. So bottom line: I would not be at all surprised if it was a bubble. I would not argue strongly against it being a bubble, but I’m just too humble to believe any of my analysis or act on it.

Krugman: So, I’ll give you my take. I kind of look at the size of the CapEx and the experience that we had from the dot-coms, which was that it was a really big technology, but the big spenders didn’t capture much of the gains. So it is hard to understand the valuations. On the other hand, people who understand the technology better than—well, it’s not hard to understand better than I do, because I understand very little of it, something about matrices—but Azeem Azhar, whom I’ve talked with, has all of these reasons why it actually does make sense.

And there’s a funny thing: I kind of look for the sociological correlates. I’m certainly older than you, Jason, and I remember the late ‘90s when bars had CNBC on the TV instead of sports—that sort of popular enthusiasm. And I remember the housing bubble when there were shows like Flip This House, and I don’t see that now. There doesn’t seem to be the same kind of popular obsession with investing in this stuff. And the actual CapEx is being undertaken largely by established companies, where their cash flow is no longer enough to pay for the investment, but it’s not the little guy in the street who’s driving this.

Sometimes I look at the scale of this, and instead of this being naive individual investors, one possibility is that, except for Jensen Huang and so on, most of the people doing this have been in the tech business and have been billionaires for a long, long time, and sometimes I think that what’s actually happening is just they’re trying to repeat their former glory. One interpretation of the whole AI boom is that it’s basically a tech-bro midlife crisis. But anyway.

Bernstein: I’ll throw a couple of numbers here and take the bubble side of the argument, with the strong caveat that it’s all speculation, and I think we’ve all been clear and will continue to underscore that. So today, the CapEx for the industry basically has been north of $1 trillion. That’s since 2024. And the planned CapEx is around $6 trillion through 2030. And by the way, the chips wear out after five to six years. So this is what we did in some of our analysis. If you assume a break-even of about 10% of the cost of capital, or even a lower hurdle—a 3% to 4% hurdle rate, which is pretty standard—you quickly get numbers like the fact that their revenues so far appear to be a little bit south of $300 billion. And to justify that spend, given the assumptions I’ve mentioned on returns, they need to be $2 trillion to $3 trillion. So they’re off by multiples relative to where they need to be.

If you look at their operating losses, they’re much higher than other firms like Amazon when it started out, or Google, or Uber, or whatever. And so just in historical context. And again, the gap between spend and revenues or earnings—it’s plausible and suggestive of a bubble. And then the other point is just how much economic activity—I know we’ll get into this, because when we’re worrying about the bubble trouble, it’s a simulation of what happens if that activity goes south—it’s so pervasive. It’s playing such a large role in markets, in investment, in growth. A lot of that is imports, as you’ve pointed out, and so you have to net that out. But I don’t think there’s any question that the AI trade is playing a disproportionate role in the broader economy.

Krugman: Okay. I want to come back to that. But Jason, you made a point just now that is something I really had not thought of, which is normally when there’s a sort of catastrophic, far-tail risk out there, it’s something that is a bear case: “this might all disappear.” And you’re saying that actually the catastrophic risk here is that, in fact, AI takes over everything. And so it’s actually a bull case.

Furman: Yeah. No, I think that’s exactly right. And I think we think of rare disasters, and there’s a real disaster here too, right? But there’s a rare boom here, and I don’t think you need a lot of mass there to make sense. And by the way, if that’s right, it might mean that we play the world 80% of the time, 90% of the time, and Jared is right. But on average, he’s still wrong, and it’s worth investing in this. Yeah.

Krugman: And the other part of what you’re saying is—this is very much not, I think, the way that most of the sort of tech guys are thinking about it—but you’re thinking that this does not look like a technology where you get to build moats, that it’s not like Google where everybody uses Google because everybody uses Google, or everybody uses actually pretty bad products like Microsoft Word or Excel. But this is one where…

Furman: I mean, that’s what I tend to think. And I think paradoxically, the better it is, the worse the moats might get. There’s this idea where if I’m the first company to RSI—recursive self-improvement—I get to infinity quickly, and now everyone’s going to be using my product. If somebody is at infinity, half of infinity is still a pretty large number. A quarter of infinity is a pretty large number. You don’t need to use the infinity; you can use just part. So in some ways, the better it gets, the more being behind the curve is fine. Not for everything. If you’re doing cybersecurity, if you’re doing national defense, there are certain things where you’re going to be willing to pay. Maybe Jane Street hedge fund would be willing to pay. But for me? Fable II comes out. I’m pretty intense on these models, and there’s very little in my life that I think Fable II changes very much relative to things that came out a few months ago.

Bernstein: I think I’m a little confused about this part of the rap, and I think you could clarify it for me. So if we’re talking about a sort of winner-take-all—or couple-winners-take-all situation because somebody figures out how to do RSI and get to infinity quickly, then you have this big overbuild and a lot of investors will lose a lot of money, because, just like fiber optics [25 years ago], there are too many data centers. Meanwhile, you’ve got competition from open-source, open-weight models from China, which I also think is a potential competitive problem for our firms. So how does that square with what you’re saying, Jason?

Furman: I was giving your side of the argument. This whole thing—the “no moats,” the better it gets, the more you can switch to other things—is your side of the argument. And intuitively, that seems right to me. Except it also seemed intuitively right to me that Tesla shouldn’t be worth more than GM in 2017. So it’s sort of my humility without being able to explain it versus my rational analysis. But then the one rational analysis I have is the sort of rare boom. And by the way, it might be that one of these companies really is worth nothing, but the other’s worth $10 trillion. And so you invest in all three of them and it’s still worth doing.

Krugman: But I mean, the three companies are the frontier models. And there’s also the hardware. Basically, there’s the compute. And those are somewhat different questions. It could be that we have a world in which there are many open-source models and you don’t need Anthropic, you don’t need OpenAI, but you still need the chips. You still need the data centers. But there’s also a world in which the modeling gets so good that you don’t need that much compute. Does this become both—that the models themselves are a commodity and that the demand for compute is actually a lot less because smaller models can do the work? I have no idea. I mean, I guess we’re all kind of at sea at this point. But it is interesting to think that the considerations are so complicated here.

Bernstein: I guess another point I’d make is that while there are examples and counterexamples, if you think of the big transformational technological advances throughout history, you tend to see bubbles—electricity, the internet, the railroads, all examples of transformative technologies with massive positive productivity implications for future economies. But the overbuilding and the bubble were there. So look, I guess the consensus I’m picking up from the three of us is that there are a lot of question marks, there’s a lot we don’t know, but the bubble possibility is not just zero, but pretty far from zero in terms of probabilities.

Krugman: All right, I want to talk about bubble collapse in a moment. But what are the effects so far? I mean, this is also really quite interesting, quite different, I think, from the dot-com or the housing bubble. The data centers are a huge amount of investment. But do either of you have a good handle on the import content of the data centers?

Furman: I think the import content is probably about 75%. And that includes it being about 10% for the construction side of this, where there’s just a boom in actually building, and then more like 90% or 100% for things like the computers and communications equipment. That’s very, very different than the dot-com. You can look at 1.9% of our GDP right now being imports of computers, telecom equipment, and the like. It was 0.2% of GDP that was imports of that stuff 25 years ago. And that’s a really important part of the direct macro impact of all of this buildout. You put it well, Paul, when you said, if we build a lot less, a lot of that’s going to be felt in Korea and Taiwan. Twenty-five years ago, it really was American-made stuff with a lot of American-made labor, digging holes and putting the fiber in the ground. That’s just not what we’re doing now, where the value, the money, is going to Taiwan and Korea.

Krugman: Yeah. I mean, this is probably unprecedented. You have a massive investment boom where only a tiny fraction actually stays here. So it’s the macro impact.

Bernstein: Correct. I haven’t seen any analysis of the impact of the bubble bursting that doesn’t land where the three of us did just now on the imports. Meaning that the investment side of this is kind of your least worry, because of the import channel. Again, I don’t think it’s zero. And I’ve seen estimates that net out the imports and argue that the AI buildout is adding maybe three-tenths to growth, but that might actually be a bit high.

Furman: And three-tenths is about what I have. That’s so much smaller than the gross amount of investment, though.

Bernstein: Correct. So yes, the wealth effect is the main factor. And in our analysis, we argue that its damage could be twice as big as what happened in the wealth effect from the dot-com era, having to do with how much those assets have appreciated. I can talk numbers there, but just the market cap: Paul, you had a graph in your piece showing that at the dot-com peak, the market cap was about 150% of GDP, and now it’s 100 percentage points above that. So that’s what we’re talking about there.

And then there’s the financial channel, which is a problem. In our model, we have that as part of the drag on growth. I think Jason doesn’t put that in his. And that’s a perfectly legitimate form of disagreement here. But I will note that when the dot-com bubble burst, financial conditions tightened a lot. And that’s a concern of ours.

Krugman: When I was trying to talk about this with Nathan Tankus—just talking with different people from different lanes—they think that even if there’s a collapse here, it’ll be more of a rotation where people move into other stocks. I actually haven’t done the homework to figure out whether I believe that or not.

Furman: So, yeah, I mean, two things. Starting with what I’ve published on this—and I’ve done other work that I haven’t published—it’s just: what has the effect of the boom been? You don’t want to assume that if the boom goes away, you just put a minus sign in front of everything and you get the answer. So, Jared, when I don’t have the financial channel, that’s not an important part of understanding the contribution the boom has made to the economy. But if you have a bust, then you need to bring in the financial channel. So it’s not that I think it’s zero; it’s just a different question.

And in terms of what the boom has done, it’s mostly a wealth effect, right? It’s how much faster has GDP growth been over the past year than if this thing wasn’t happening? I think about six-tenths, seven-tenths. And more of that is the wealth effect than the direct effect of the buildout. That’s also based on the Federal Reserve’s large-scale macro model, FRB/US. One thing to know about FRB/US is it makes everything smaller than you’d think. And their wealth effect is more like 1% of spending out of wealth. My back-of-the-envelope would have been 3% spending out of wealth. So I would have gotten a larger number than what their model spit out. So yes. Is it the majority? I think it’s a wealth effect. But, I don’t think wealth is adding—

Bernstein: Jason, let me just interject one thing. I just looked at Mark Zandi’s estimate, and it’s exactly the same as yours: seven-tenths.

Furman: Seven-tenths. And the wealth effect, though, I find a bit reassuring. I mean, you don’t go from 2.5% growth to a recession after a wealth effect that added seven-tenths or three-tenths or whatever number of tenths it is. I take it that GDP is higher, though. A bit more of that is owned by foreigners—that’s a small point compared to the increase. There’s the hedging: the software stocks have suffered. And that matters, by the way, not just for the stock market, but for some of the lending. A lot of the private credit losses are to software companies. And if some of the AI stuff doesn’t pan out, maybe those loans will be paid back because the software companies will have a business model after all.

And then there’s just the stock market busts where nothing happened. In 2022, we lost almost as large a percentage of GDP in stock wealth as we did in the Nasdaq bubble in 2000. At the same time the Fed was raising rates, the economy was basically fine. There’s 1997, which to me is the closest exogenous stock market decline, and we did the experiment on it and the economy grew just fine. Almost all of the other stock market declines associated with recessions are basically because there was a recession—there was a stock market decline as opposed to the stock market decline causing it.

So I am worried about the financial system, and I want to come back and talk about that. But the stock market part of it feels to me contained, not the difference between us and a recession.

Krugman: You’d need some amplification elsewhere in the system to get yourself to a recession. And this is actually kind of wild, given how basically everything on the front page of the Times or the Journal that isn’t about politics is about AI and the AI boom. Talking just retrospectively, what it’s done so far is probably a fraction of the standard deviation in normal growth rates, right? That’s just really not a big deal.

Bernstein: Well, I definitely wouldn’t call it not a big deal. So if I’ve given that impression, I should correct that. I think when you have seven companies that are responsible for 40% of the increase in the stock market, that’s a big deal. And if you view those companies’ financing as fragile as I speculatively think they might be, that’s also a big deal. And look, I mean, if we’re just talking about some isolated part of this breaking—if it’s just the investment part, which is relatively small given the imports, or if it’s just the wealth effect, and I want to say a little bit more about that—if you’re really growing at, I don’t know what true GDP trend growth is, probably 2.5%, maybe 3%, if you take even a point off of that, you’re not in a recession. So, we have some macro space there.

But if you put it all together and you add in financial—a risk premium that goes up or some clogging of the financial system, basically tighter financial conditions—then you can have a real problem. So I don’t want to sound more optimistic than I feel. It’s just that when you talk about isolated parts, you kind of, by definition, avoid their interactions.

I did want to get back to the wealth effect for a second. So look, I mean, if you look over a couple of years, the market cap is up $28 trillion. And if you multiply that by three cents, you get numerous points of GDP. So it’s Iike we should all sort of put on the table (and mine is not $28 trillion) but what is the part of the wealth effect that you think goes away here? If it’s a bubble and if it bursts, do you think it’s just the AI wealth appreciation or do you think it’s the broader market?

Furman: I don’t have a strong view. In some of this, you’d look at like a Shiller CAPE, which is backward-looking—it compares the price now to what the earnings were—and it’s extremely high. But then you look at measures that look at the price relative to expected earnings, and it’s roughly 18x. That’s roughly the average it’s been. You don’t see anything like the craziness of a Cisco or a company like that where you had forward P/E ratios of like 100 during the dot-com bubble.

Krugman: For listeners who may not quite know, P/E is the price-earnings ratio. CAPE-Shiller was a way of trying to figure out if they were unreasonable, which would compare today’s stock prices with past earnings. And forward P/E is trying to use forecasts of future earnings, which, of course—

Furman: And I get that. I am giving that caveat. But yeah, Cisco was 100. Nvidia yesterday was 14. I haven’t checked what it is today. And it’s the same thing with the fiber. Back then, most of the fiber that was being built out wasn’t used; dark fiber was the majority of it. Now, every chip we have right now is being used absolutely to the max—maximum demand. That’s not saying there’ll be demand for all the chips people are planning to install next year or the year after, but at least to date, revenue in these companies is rising rapidly—

Bernstein: Hold on. Aren’t you assuming away overbuilding in that kind of analysis?

Furman: Back then, the building was based on, “build it and they will come.” Right now, the demand for this is massive. Is the demand massive enough for the building they’re planning two years from now? I don’t know. Is it enough for the building that’s already happened? Absolutely, yes.

Krugman: But now we’re back to looking at the bubble. I want to do the financial transmission.

Furman: I mean, the biggest thing that gives me the biggest calmness about the transmission through the financial system is that we’re having this conversation, and that these conversations have been happening for at least a year now, which is to say, people know that this is super risky. And financial crises largely happen when people think something is money—they think it’s completely safe—and then, oops, it’s not: “I can’t get my money out of the bank. My money market mutual fund is not worth a dollar. The triple-A security I was using as collateral, almost as if it was cash or a Treasury, turns out to be very different from cash and a Treasury.”

So it’s that “oops” moment when you discover your money is not money that is the most dangerous moment in an economy. Here, the bonds we’re talking about already have high interest rates. The CDS spreads—the insurance you have to pay against the risk of default—are already very expensive. The people investing in this know that they’re taking a risk. If it doesn’t pay off, they will be poorer. They will spend less and that will hurt the economy. But the type of amplification of when riskless stuff turns risky, to me, feels absent here.

Bernstein: So let me respond, Paul, if I could. There are two things I would push back on a bit. The first is this thing where you just said, well, that’s a bubble question. And I think it’s really important, the bubble question here—

Furman: I just thought we had solved it, so I was trying to move on.

Bernstein: Oh, okay. Thank you. Yeah. So the argument that there’s a lot of demand for X and therefore, like, it must be sort of okay doesn’t move me at all because there was a lot of demand for railroads that ended up being useless, and a lot of demand for fiber optics that ended up taking years to be put into service. One definition of a bubble is, “excessive exuberance leading to overbuilding and excessive demand.” And there are those who look at this sector—and I’m one of them—and see that as a problem.

Secondly, on the financial thing, I think what you just said is important and I’m also glad we’re talking about it. And maybe it is a positive sign, except in one area, which is in the leverage place. So, there are those who have made the argument—some of them are market folks with pretty good vision into this—that moving from cash-flow financing, which is how the hyperscalers were supporting the buildout, to leverage, to borrowing, is creating some non-transparency in the system, which is a characteristic of past financial bubbles that has led to the kind of financial problems that I worry about. And I don’t have good sightlines into that either. And I take your point that if it’s just private credit and some of it goes bust, maybe it’ll be okay. But that seems to be making some more knowledgeable market people than me nervous about the future.

Furman: Look, I don’t want to defend opacity. There should be more transparency. I think we need more insight into things like private credit; these off-balance-sheet vehicles that a lot of these companies are using are making me nervous too. But there’s a really big difference between Meta doing things off-balance-sheet, which might work out really badly for Meta, and major money-center banks doing things off-balance-sheet, which works out really badly for all of us. So to some degree, the question I’m trying to ask is the propagation question. And when you have banks that are just quite healthy in terms of the amount of capital they have—and some of that we should actually take a little bit of a victory lap for; we actually have more and better regulation than we had 20 years ago, and parts of the financial system really are safer—because of that, the Fed and the Bank for International Settlements and the IMF, they sort of all have to say “blank might be a worry,” but I read them as sort of largely reassuring, and not terrifying.

And the other thing is we have to also avoid being miscalibrated. Neither of you are one of these, but I have another friend who is constantly citing things with a 30% chance of happening. And for any event, you can say that. And ex post you can’t say whether you’re wrong or you’re right. Once you say it ten times and the thing only happens zero or one times, you actually were wrong; it wasn’t a 30% chance. And I think there are a lot of people who don’t want to be that person. That doesn’t mean it isn’t a risk.

If you look at the Survey of Professional Forecasters, when they say there’s a 30% chance of negative growth a year from now, do you want to guess what fraction of the time there’s negative growth a year from now? It’s 0% of the time when they’ve said 30%. So I want to avoid being the person who’s constantly talking about risks at a magnitude that doesn’t materialize.

Krugman: I do want to remind everybody of 2022 and the infamous Bloomberg pronouncement that the chance of a recession next year was 100%.

Furman: And to my credit, I don’t think I ever went above 45%. And so you can’t prove that I was wrong, but if I have ten recession forecasts at 45%, at that point I think you are going to find that I was wrong, and that was a mistake. I mean, in some sense, my recession forecast in any given year is 15%, the unconditional probability. And I now try not to let myself be talked out of a 10% to 20% range, because I think we just don’t know. And in fact, in the Survey of Professional Forecasters, if their recession forecasts were the baseline, they would be more accurate than them trying to know.

Bernstein: So I mean, I sort of agree with what you’re saying, and there’s a lot of sage counsel in there. But if the sort of rule of discourse should be like, unless you think the probability of something for good reason is well north of 50%, you should sit on your hands, I don’t think that’s where I’m at or particularly helpful. And one of the things that Ryan and I have tried to be disciplined about is like, I don’t say anything about the probability of doom because, like, I just don’t understand it. I hope it’s wrong, but I don’t have the knowledge to speak of it. But in our work about “Is there a bubble?” we’ve been very quantitative. We’ve looked at the trillions, we’ve plugged in discount rates, and we think that for these companies to hit a kind of plausible profitability such that investors will have the patience to hang around, their revenues would have to grow between 5x and 10x of what they currently are, at least. And that just strikes us as a risk. And I don’t want to assign a probability to it. Like I said, I think we all agree it’s non-zero and we all agree it’s not 80%. But it does seem to be, especially given the magnitude in the economy, it just seems to be kind of prudentially correct to raise these concerns, which is probably why the three of us are talking.

Furman: And as I said, I think in some ways raising the concerns makes me feel a little bit better.

Krugman: If you remember 2008—which it’s hard for me to believe was 18 years ago, but anyway—the fall of Lehman was shocking and a big deal. But it was actually like three days later when we realized that AIG was the core of it. All of these CDS basically were offered by AIG. And AIG was a quintessentially solid business, an insurance company with real cash flow, except it turned out it really wasn’t. What it was was a gigantic, overleveraged shadow bank. Is there anything like that in the current landscape? Because there is this complex, opaque financing, and I wonder, just, are we going to discover, I don’t know, that Meta or someone is somehow at the center of a vast network of promises that everybody assumes are good because Facebook is profitable?

Furman: I think if we look back on this and something terrible happened, the place I would have gone wrong is that there was the sort of unknown unknown tucked into all of this. And so I am worried about that. I’m not that worried about if they actually literally start building less; I’m not worried about that at all, basically because of the imports. The stock market falling is, to me, a contained thing—not plus or minus two percentage points, it’s like plus or minus two-tenths of a percentage point. But I am worried about the things we don’t know. And in terms of the sitting on your hands, Jared, more transparency, some more regulation, etc., I would be completely fine with. So it might be that we have the same recommendation.

That being said, Paul, I don’t want to say just because I don’t know something, there’s like a big chance of it happening, and again, it’s sort of CYA to constantly say there’s something out there that might blow up. I do think a lot of the private equity firms—I don’t know that their market cap is going to make sense, and they’ve already fallen—but, they’re not banks. They match the maturity of their liabilities and assets. They put riskier pools with riskier investors. They have gates on how quickly retail investors can withdraw so no bank runs, etc. So I mostly feel good.

But yeah, I wouldn’t tell you there’s a 100% chance it’s all fine. But there’s one other totally different issue which is sort of related to this, which is: if stuff goes bad, what would rescue us? I do think there are some things out there, not that they’re fast and large enough to avoid a bad case. And for me, the tail risk is more like the 2001 recession—not 2008. But 2001 is not my base case; that is the tail risk. If the bubble bursts, probably we’ll be fine. But if the bubble bursts and I’m wrong, we get 2001.

Krugman: Jared and Ryan were basically saying 2001 was more like a base case.

Bernstein: Yeah. So a couple of things. Just first on Paul’s question, I agree with what Jason said. And we had a paragraph in the op-ed we just published a few weeks ago about the damage that a bursting AI bubble could do to the macroeconomy—wherein we said kind of, we’re less worried about this channel, for the reasons Jason raised and not least of which, again underscoring something he said earlier, because we’ve actually done something in that space.

And I think the capital buffers, for example, that were part of Dodd-Frank are still helping us. However, that said, I am, as I’ve said and as others have said, worried about what I can’t see. I will say, in terms of the people who are always running around warning about stuff, I think this is the first time I’ve ever gotten ahead of a bubble and said, “I think there’s a bubble.” I didn’t say it around housing. When my friend Dean Baker was hammering on me that there was a housing bubble, I didn’t say, “You’re wrong, Dean,” but I didn’t join him in that. And so to the extent you want to discount people who are always yelling “bubble,” that’s not me.

I think the other point on the financing is the circular financing part, and I think that is concerning. I have my Wall Street Journal from today in front of me. TSMC, which is the Taiwan Semiconductor Manufacturing Corporation—they’re by far the main manufacturer of all these chips—“TSMC will invest in Anthropic and OpenAI $1 billion, giving a shot of confidence to the markets.” That is your dealer buying from you. It’s circular financing, which should also make us a little concerned.

On the 2001 point, one thing to remember about that was, while GDP barely fell at all, it was a real problem in the labor market.

Krugman: Yeah, it was a really long period of a depressed labor market. And people have kind of forgotten that, and they think of it as a mild recession. But as late as 2004, we were still saying, “Well, why aren’t we getting a real recovery in the labor market?” And my point always on this is that we were actually better positioned to deal with that kind of thing then, because we came in with interest rates at 6.5% and at a balanced budget. So there was just much more room for monetary and fiscal stimulus than we have now.

Furman: So first of all, there’s: how do we get out of it? Residential investment is quite low. So we could have another housing bubble to get out of this bubble. That’s what we did coming out of the dot-com. Obviously, I wouldn’t go all the way to a housing bubble. Long rates are pretty high; they have a lot of room to go down. Yes, the fed funds rate can’t be cut too much, but we are going into this with a lot of inflation, so the real interest rate you have can be lower. So some of the liquidity trap stuff—that stuff you know so much better than me, Paul—but I sort of look at our inflation rate and have a hard time getting worried about it. But you should explain to me why I’m wrong, because I’m sure you can.

Krugman: I would have said that there’s inflation in what people buy, but the real rates should be computed in terms of what people produce, and that’s not so good. So it’s actually not clear to me if that helps very much. But anyway, that’s a wonky discussion that goes way beyond—

Furman: Sorry, but then the last thing I’ll say is that my existential fear in all of this is that a lot of historic job loss with new technology doesn’t happen year after year after year in a smooth way. It happens in a very discontinuous way, where people get laid off in a recession and don’t get rehired. That might be—I’m not sure if it was, but it might have been part of the slow recovery from dot-com, because we had very high trend productivity growth at that point in time. And so here, if we have a recession, this becomes the time when all the predictions, which have been wrong to date about the impact on labor markets, suddenly become true and stay true. That terrifies me.

Krugman: We’re running a little long but let’s get to that—just this whole productivity, job loss aspect. Where are we on that? My read is that it’s surprisingly invisible in the macro numbers so far. Do we just think that that’s lag?

Bernstein: I don’t think it’s invisible. I just think it’s hard to see. But if you squint, you can see something. Now, if you squint too much, you can see things that aren’t there. But I disagree with some of my colleagues who say there’s nothing there. And I definitely disagree with people who say AI is killing jobs for every college graduate.

If you look at the work of Goldman Sachs economists on this—Joseph Briggs and Sarah Dong—you see they consistently plot these scatter plots with AI exposure on the x-axis and some measure of labor market activity on the y-axis. And those slopes were very flat, and now they’re a little less flat. And if you look at the extent of the difficulty that young college graduates are having, you can see a bit of a correlation there with AI exposure. It’s actually true that some who aren’t exposed are also having trouble. So it’s foggy, but I think there’s something there.

I think that the point Jason made is one that I’ve argued and want to amplify. Historically, recessions have been a force multiplier for technological unemployment. If there is a way for an employer to figure out how to not hire you back after she’s laid you off—if there’s a potential technology that might enable them to do so—they get a lot more interested in that technology post-layoffs. And there is good evidence that recessions that coincide with potentially labor-replacing technology could be problematic in exactly the way Jason said. So that’s a worry of mine as well. Yeah.

Krugman: Historically, I tended to say technological unemployment is the last refuge of scoundrels—that whenever there’s a recession, people say, “Oh, it’s technological unemployment,” which was very much true in the ‘30s. And might I actually be right this time?

Furman: Yeah, I’m not super worried. I mean, look, in general, higher productivity growth is correlated with more job growth, not less. That’s when the economy’s doing really well, the stock market’s booming, there’s lots of demand. I hate being a person who sees something happening over and over again and now says the exact opposite is going to happen this next time. So, first of all, people who want to work have been able to work. And yeah, in the short run, productivity has been good, not bad, for employment. At this point, though, do I think there’s at least a 15% chance that those past relationships don’t hold? Absolutely. Is that terrifying to me? Absolutely. And I think it’s probably more than a 15% chance. And we’re super early here. I mean, agentic AI is basically one year old; businesses and individuals still haven’t nearly explored the capabilities the current systems have.

And those of us that don’t listen to the people in Silicon Valley about what’s coming and just roll our eyes because they sound like a bunch of weirdos—well, those weirdos have been a lot more right about the capabilities, not about the impact. Just don’t hold them to the dates in their forecasts of the economy.

Bernstein: So I agree with all of that. But I also have this other scary concern, which kind of is on the other side of the axis, which is that I think I might be channeling some of the work of Alex Imas here, which is that there’s a combination of Jevons paradox and Baumol effects—I’ll explain what I mean by those—that get you to a place where actually AI, like other advances, creates a lot of new jobs. It’s just that they’re crappy jobs, and what you end up with is a lot more wealth inequality than we have now. And we already have a boatload of wealth inequality. And this is the idea that AI starts doing a lot of work that people are already doing, but because it lowers the cost of all the things that it can do—and look at Jason’s Econ Vitals software, if you want to get a good example of that—then it opens up a lot of space for people to hire new relational kinds of workers, to be chefs, to be therapists, to be personal trainers, to entertain their kids.

And there’s a dark world where we have a lot of jobs supporting the whims and the entertainment of our tech overlords. And that’s the Jevons paradox. But the Baumol effect part is that there’s no productivity gain from playing the three-minute waltz in two minutes, right? You can do it, but it’s inherently, like, not good. And so in these kinds of jobs, AI probably doesn’t replace them because they’re relational or, as I think Imas puts it, mimetic, which I’m not 100% sure what that means. But the idea is that you just have more of a bifurcation, which feeds into the inequality story, which is already exacerbated.

Krugman: The idea that we’re quite a long ways from bots being able to empty bedpans—and given our demographics, we’re going to need a lot of people emptying bedpans. But, on the other hand, if all the new jobs are people emptying bedpans, then that’s your functional world.

Furman: Yeah. And I see three different sources of inequality. One is how much income goes to capital and how much goes to labor. If I had to bet, more is going to go to capital and less is going to go to labor under this, and a wide range of models predict that. I think it’s a relatively robust thing. Within labor—which has been the big story in inequality in the last decades—there, I’m not sure. It could be that it takes somebody who is less skilled and improves their skills and you’re willing to pay them more, and if you’re super skilled, it doesn’t add much to you. Or it could be a force multiplier for people that know how to use it well. So I could tell labor-inequality-up and labor-inequality-down stories when it comes to this technology. But almost all of it is capital-inequality-up stories.

Bernstein: Yeah. Let me pose the last question, because I know we’re late in the game here. What do you guys think will be the fiscal policy response if the AI bubble bursts and generates some measure of a downturn?

Krugman: That’s a really good question. But I would say if it bursts within the next two years, nothing. Because there is nothing on which the White House and the incoming Congress will be able to agree. But that’s a very sort of contingent forecast. And then after that gets interesting because I’ve always been a huge deficit dove and debt non-worrier, but I keep on thinking about the fact that, fiscally, the US and France are twins, and I do worry about it.

Furman: I rather think the US and France are twins in two important respects. The numbers are pretty similar in terms of the debt, the primary deficit, etc. The other thing is the political system: if it hits a shock, how do we recover from it and fix it? I can’t quite figure it out in France or the United States. The UK fiscal situation is actually better than either of our countries, but even if it wasn’t, they have a somewhat functional political system that can fix it in a hurry. All that being said, if the bubble bursts in the next two years, I am not going to go out on a limb and try to predict what Donald Trump will do. He is an unbelievably unpredictable person. COVID was a huger thing; he acted in a big way there. George Bush did stimulus as a lame duck in 2008. He might want his name on the checks, and Democrats might be willing to let him put his name on the checks so they can have more checks. So I wouldn’t write off a fiscal response to this. But yeah, beyond that, I am worried less about our numbers and more about our political system’s ability to respond and change in response to those numbers.

Bernstein: Yeah, I’m sympathetic to the point that one definition of a Keynesian is a Republican in a recession. I’ve seen that lots of times. That said, we’re basically running recessionary-level deficits right now. I mean, our deficit is north of 6% and it should be half of that given the economic growth. It’s just that we’ve debauched our revenue function with all these ratcheting tax cuts to the point where there’s just this very structural disconnect. So, I would be concerned.

I will say the following, just putting on my fiscal hat: it isn’t the temporary stuff that hurts you in the long run; it’s the structural stuff. So, yes, if we were to go from a 6% of GDP deficit to 8% or 9% because we had to, that would show up as even higher debt going forward than we’d like, but it would go into the system and go out of the system. So I would advocate for fiscal responses. I’m sure we all would, whether that would be met by deaf ears, I don’t know.

Krugman: What I take from this is we all kind of think it’s probable, but not certain, that it’s a bubble, but are less concerned than you might be about the bubble bursting because this is such a weird form of investment where most of the money is going overseas, and we’re worried about wealth effects, but those don’t look enormous.

I mean, my take on this is that extra spending, even a higher level of debt, wouldn’t necessarily be a problem. Britain came out of World War II with debt of 250% of GDP, but no crisis, because everybody said, “They are a reasonable, responsible country that will in the end do what needs to be done.” And my question is, do we look like a reasonable, responsible country at this point? That’s where I get hung up.

Bernstein: We look more reasonable and responsible than we did a week and a half ago.

Krugman: Yeah, true.

Bernstein: Just to end on an optimistic note.

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