Lunch Money with Paul Krugman and Heather Cox Richardson

Power and Geopolitics After Trump

Transcript Hi everyone. Instead of a regular post today, I’m going to put up a video. There are a number of reasons why I feel like doing that instead of the usual. One of them is that this is a dry run for a talk that I will be giving virtually later today. There’s a conference on the economics of digital transformation taking place in Croatia, although I’ll be doing it remotely. And they have asked me to talk about global power, geoeconomics, and Europe. Those are all themes that I’ve been thinking about quite a lot. And today’s miniature talk is an opportunity to try talking through those themes. And the way I want to structure it is as what has changed, at least in the way that we all now understand the world, since, well, basically since Donald Trump returned to power. That’s an American-centric point of view, if you like, but it’s kind of a natural bracket. And of course, everything really has changed, mostly not for the better, under Trump. And it has, as it turns out, big implications for Europe as well. So let me just try to get into that. Start by talking about the world as it seemed to be at the beginning of 2025. There were, and still are, three great economic superpowers in the world: China, the United States, and the European Union, in that order. If we measure GDP in 2024 at purchasing power parity, which is basically just adjusting for differences in national price levels, you had China with a GDP of something like $37 trillion, the United States with something like 29 trillion and the EU with something like 28 trillion. That last bit may be a bit of a surprise — maybe all of it is a surprise to some people — but yes, in terms of the actual amount of stuff it produces the Chinese economy is now substantially bigger than the US economy. And the European economy is almost the same size as the US economy. If you think that Europe is backward and poor and helplessly dependent, it’s not. It is an economic superpower. And in fact, by this measure, Europe has basically maintained this position of being about comparable to the United States for a long time. This is a whole other topic that I’ve been writing about and will continue to write about in the future. In that world, basically, two things were really kind of striking. One is that the United States seemed to perceive itself as being a dominant power, even though China was bigger and even though Europe was about the same size, and Europe acted as if it seemed to perceive itself as not being in the same league, as being not a superpower at all. All of that may be changing, and events are part of the reason, so let’s talk about the events. Now, the most obvious: the United States just lost a war. Just lost it bigly, as Trump used to say. It’s an astonishing story. We went up against Iran, which was definitely not a major military power or a major economic power, a sort of middle-ranked power, if that, and utterly failed to achieve our war goals. In the process, we inflicted a lot of damage on the world economy and depleted our stocks of high-tech weapons that will take years to replace. Altogether, immense damage was inflicted on Iran, but Iran has clearly emerged stronger. The United States has emerged humiliated. The attempts by Trump and minions to pretend that it was a victory don’t help. They only make the United States look not just humiliated but delusional. So that’s a big deal. It has large implications for US power and influence going forward as well. To explain those implications, it’s helpful to talk about one of the other things that really dramatically changed with Trump coming back into office, which was trade policy. The United States began really seriously trying to throw its weight around. Liberation Day, the tariffs on everybody, basically trying to pressure all of the world into giving us various kinds of concessions. Give us what we want or we won’t let you sell in our market and everybody needs to sell in our market. Okay, what we learned from now well over a year of trade war is that U.S. power in that dimension is substantially less than certainly than Trump appeared to believe it was. And just in general, trade, leverage and trade negotiations, leverage in trade disputes has less to do with market access than a lot of people assumed and more to do with supply chains, with getting stuff that you use in your economy, means of production, not in the sense of capital, but intermediate inputs or just inputs in general. The nation that has more ability to strangle its rivals by cutting off supply chains is the one that has the upper hand. So it turns out, and we had already learned this from the trade stuff, that China with its dominant position in rare earths and some other crucial industrial materials actually had a stronger hand than the United States. Yes, we have a big market, but loss of a market can be offset to some extent by domestic stimulus, domestic support programs. Not having crucial industrial materials is not so easy to make up for. So we learned that the power in international trade disputes in a fundamental sense reflects power over supply, not power over demand, which is something economists have always tried to say. The point of trade is not to sell. The point of trade is to get stuff. You sell as a way to pay for things that you get from other countries. But now we have it demonstrated very obviously in real life. So that in itself meant that we’ve had a blow to the perception of US power. It turns out the US market is not almighty; access to the US market is not anything like as powerful a tool as we thought and Chinese strangleholds over key inputs are much more important. And then of course we’ve seen that even more graphically demonstrated by war with Iran and it turns out that Iran’s ability to disrupt traffic through the Strait of Hormuz was a really huge empowering point, and it was the kind of thing that the United States really didn’t think about, and certainly the Trump administration didn’t think about. And it shows the true rules of global economic power, because largely Iran was able to win this war through economic power rather than strictly military action, the rules of economic power are not what a lot of people thought they were. Who benefits from that? Well, obviously China. What we’ve seen now is that in terms of a global power competition, China has demonstrated that they have substantial power over supply chains. They’ve also demonstrated that they can weather a cutoff of oil pretty well. And global power is a zero-sum game. So the United States, by weakening itself, by showing that we don’t have the ability to impose our will militarily, we don’t even have the ability to keep international shipping routes open, has emerged as just a much less formidable player, which means that China by comparison looks better. Add to that the fact that the United States has been erratic and unreliable. Our current leadership just doesn’t understand that a reputation for doing what you promised, honoring your agreements, is itself a source of power, and we have done an enormous amount to undermine that. Not news to anybody. Trump looks much weaker. America looks much weaker. To a certain extent, China is the beneficiary of all that, at least in terms of power. Now, of course, life is not all about power. And in the end, you don’t run a country to maximize global power. Maybe the Chinese do. I’m not sure about that. But in any case, it’s not a zero-sum game in terms of living. But in terms of power, it is a zero-sum game. And the United States share of that power, however you measure it, is clearly down as a result of the war. Europe is a little bit interesting here. Europe played essentially no role in any of this. Europe wasn’t involved, obviously, in the war. Europe didn’t do very much at all except to suffer. Still, one thing that is kind of important is that Europe — at least to some degree, not really through emergency responses but just through the general way that the Hormuz shock played out — Europe demonstrated or some European countries demonstrated that they can be much more independent of global hydrocarbon resources than they have been. Europe is not a major oil producing area. It has some, but not a lot. It’s not a major gas producing area anymore. It’s essentially a very resource poor economy relative to the size of its GDP, relative to its population. But it is an economy that increasingly relies on renewable energy. And those countries that have gone especially far in relying on renewables weathered this really well. That’s the lesson of Spain’s ability to ride through this with very little rise in electricity costs compared with some other countries. Italy, which has very little in the way of renewables and is very heavily reliant on natural gas for electricity generation, Italy did much worse. But Spain has given an illustration of how the renewable energy revolution — solar plus batteries is what really runs Spain now — has made Europe more independent and can make it more independent still in a world economy where control of natural resources used to be really critical and it’s becoming increasingly less critical. So that’s actually a point in Europe’s favor. That’s one piece Another piece of this is that Europe has always, in my lifetime, literally, and from a bit before my lifetime, Europe has always been far less of a global power player than you would expect given its sheer economic weight. Now that’s partly because Europe doesn’t exist as a political entity. though it’s more of one than it used to be; the common market has gradually turned into something more than that and Europe is able in some important ways to operate as one and is finding ad hoc ways of cooperating more. But it was always in a secondary position very much — or tertiary position given the rise of China — largely because the United States in addition to having a big economy was overwhelmingly the dominant military force. Now until just the other day there was never a question that the United States would use its military force against Europe; but Europe depended on the United States. Europe’s defense, its security, all depended on the United States. Okay, now where are we? The United States is quite simply just less credible as a security guarantor, not just because of crazy stuff where we threaten Denmark over Greenland, and not just because we’re erratic all the time, but because we’ve just demonstrated that our military capability is a lot less than we thought it was. The United States could not batter Iran into doing what it wanted. It could not keep the Strait of Hormuz open. So U.S. military preeminence is a lot less intimidating, also a lot less reassuring if you thought you had America on your good side than it used to be. And on the other hand the prospect that Europe might be able to defend itself, achieve its own security without the United States, looks a lot stronger than it did not very long ago. And that’s not just because of the war in Iran but also because of the war in Ukraine. Now, there are many, many horrifying things that have happened under Trump. One of the ones that is particularly horrifying to some of us is the abandonment of Ukraine, the clear tilt towards siding with Putin in his attempt to destroy a democratic nation. The United States basically stopped giving any aid to Ukraine at all. almost as soon as Trump took office. U.S. aid of all kinds, but especially, of course, military aid, is all gone. But a funny thing has happened. Ukraine is still standing. If anything, the war seems to be tilting in its direction. Now, that reflects partly the fact that Europe did step up. particularly with economic aid: Europe has filled the gap, pretty much, that the United States left so the flow of money to Ukraine continues. But it’s also because war has changed. To the extent that the United States appeared to be essential it wasn’t just the money — we knew that Europe could come up with some money — but it appeared that what would what How could Ukraine defend itself without U.S. weapons? Well, it turns out that in this age of drone warfare that Ukraine can mostly defend itself. Actually, what they can’t really stop is Russian missiles that destroy civilian targets, which is horrifying, but it doesn’t appear to really work in terms of altering the military balance. And Ukraine has developed its own suite of weapons, and quite aside from the fact that Ukraine is hanging in there, this says that one of the sources of perceived US superpower status— super duper power? versus Europe is a mere superpower? — was that, well, we had the weapons, that we had the technology, that even if Europe could come up with the money, they needed U.S. weapons to be effective, as did Ukraine. And if the United States cut off the flow of weapons, what could you do? You really could not stand without all of those sophisticated, high-tech weapons that only the United States knew how to produce. Well, those weapons are kind of looking obsolete right now. Not entirely, but we just saw Iran do a lot of damage with drones that the United States didn’t appear prepared to stop. And the United States, with all of its super-duper weapons, was not able to suppress them. We had the spectacle of million-dollar patriots shooting down $30,000 Shaheds. This is not a good look. And Ukraine has become a major arms producer ,has become in many ways the expert in this new age of drone warfare. The Europeans are picking up some of that, and there’s a lot of new cooperation on weapons with Ukraine. But maybe the most important thing to say is that, well, that special U.S. advantage, because we had the weapons and no one else did, it’s not much of an advantage now that it appears that those weapons are largely obsolete. Not totally, of course. The Ukrainians would really love to get more Patriot missiles to stop some of those Russian missiles that are destroying 11th century churches and so on. But the balance has shifted in a way that means that the United States is not indispensable at any level. We’re not indispensable financially, and we’re not even indispensable militarily. It’s like we have the world’s best cavalry in an age of machine guns. What good does that do? Okay the Chinese presumably have immense capacity. Chinese dominance of manufacturing means that on almost any dimension China is the super super duper power, they’re really way out in front. But there’s much more parity between between Europe and the United States than there was because the United States doesn’t really have economic dominance and we don’t have military dominance anymore. We dominated an age of warfare that now appears to be behind us. So where does Europe stand here? In a rational world, the rise of China and the coordinated, concerted, efforts of the United States and Europe to deal with that rise would be the central story of geopolitics in the year 2026. Unfortunately, things are not rational. And so we have a belligerent, erratic United States with Europe largely on its own. But Europe being on its own is not nearly as impossible to imagine as it used to be. This is a world that has tilted towards China. That’s probably the biggest story. But it is also, in effect, tilted towards Europe because it’s tilted away from us here in the United States. Take care. Get full access to Paul Krugman at paulkrugman.substack.com/subscribe [https://paulkrugman.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]

Lunch Money with Paul Krugman and Heather Cox Richardson

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Talking With Azeem Azhar

I last spoke with Azeem, the proprietor of Exponential View, 18 months ago — ancient history on this subject. So we revisited the state of AI. . TRANSCRIPT: Paul Krugman in Conversation with Azeem Azhar (recorded 6/12/26) Paul Krugman: Hi everyone. Paul Krugman back on my usual schedule of recording interviews. And today I’m talking with Azeem Azhar [https://substack.com/@exponentialview], who I spoke to in January 2025, basically centuries ago in AI time. And with AI on everybody’s mind, I thought it would be good to revisit. I should say Azeem is an independent researcher and founder of Exponential View [https://substack.com/@exponentialview], which is one of the top tech Substacks out there. So hi, welcome to another conversation. Azeem Azhar: Yeah, thank you, Paul. And it has been eighteen months, also known as one and a half centuries in AI time since we spoke. Krugman: Yeah. Let me ask sort of the dumbest question: what is this thing called AI? How does it do what it does? I mean, even skeptics have to admit that it’s really impressive how it’s sort of leapt over all of the previous barriers. How is this happening? Azhar: You know, I think we’re still figuring it out. I think of AI ultimately as a machine that does certain things, and it’s been built by passing first millions, then billions, then tens of billions, hundreds of billions of trillions of words of human output through a neural network to give it some sense of how humans have thought about the world. And because it operates at dimensions well beyond the form of space and time, it seems to be able to find relationships between quite complex concepts. And I think we’ve all had that experience, whether we’ve been using Chat GPT or Claude over the last two or three years, that it seems to be able to recognize things that are quite deeply related that don’t immediately spring to mind. And in the last year and a half or so, the labs have started to train the AI models not just on words in books, but actually on tasks, like, “what is the set of things that you do to write a piece of code that does something?” “What is a set of things you do to use a piece of software in an enterprise?” And they’ve tried to train those models on those particular tasks. Essentially it’s aping what we do, and they use various mathematical tools like reinforcement learning where the model notionally gets a reward. Of course it’s not a reward the way you and I think of it because it’s a machine. Paul Krugman: Right. Azhar: And so that’s what it is. It’s sort of reflecting back, but also I think discovering some really deep relationships in the world that we might not spot, you know, prima facie as humans. Paul Krugman: Brad Delong [https://braddelong.substack.com/p/note-to-self-my-views-this-afternoon] calls it “a vast stew of linear algebra,” which makes some sense to me because I think that Pagerank with Google was the last thing I actually understood. And that’s the eigenvector with the largest eigenvalue. Not that anybody needs to know that, but this is like a million times bigger, right? Azhar: That’s basically it. Yeah. Krugman: But it’s sort of not what artificial intelligence was supposed to be, right? Azhar: No, not at all. I mean, I sometimes go back and look at the TV series of the seventies that I grew up with as a child, and they’ll always have an AI in the spaceship. Space 1999 had an AI you could talk to. And it was very precise, it was very clipped, and it did things and got things right. And there was a sense that you could trust it. But you’d never think to say, as I sometimes do now, you know, “Find me five analogies to help make this point.” I use it as a brainstorming partner, or I give it tracts of my book, the book that I’m writing, and say, you know, “How would Paul Krugman criticize this argument?” And I get suggestions that I then work through by hand? I don’t think we really imagined it would look like that. Krugman: Yeah. In sci-fi it would talk in a monotone and would be relentlessly logical. And in fact these models are unpredictable, they’re sometimes temperamental, they’re not reliable. That’s probably one of the big problems. It’s not at all what we imagined. Azhar: It’s not at all and this point about reliability is so complex. A couple of months back, one of the versions of Anthropic’s Claude came out and I found it so sycophantic that it became unhelpful because I like these things to help me on hard problems and to challenge me. So I switched back to Chat GPT, which has always been a little bit less friendly. And what’s going on there, Paul, is that because we don’t really have a good theory about how to build these. They are developed almost like in a petri dish and nudged in particular directions so they take the shape that we expect them to take. And to use an economist term, they improve non-monotonically with every release. So you’ll see the latest release of an Anthropic model, and there are maybe twenty or thirty public benchmarks that they’re measured against, like how well they summarize text and how well they write software code. And the next version of the model won’t necessarily be better at everything than the previous version, because you lose something in order to get it. And that’s the complexity that the labs are wrestling with. Krugman: Wow. Okay. Second naive question. I don’t think I’m a Luddite. I’ve always been happy to adopt technologies, but maybe I’m incurious on some of these things. I tend to pick up things like mathematical techniques, as needed, because I see something that could be useful. Now, I’m using NotebookLM to extract tables from PDFs, that sort of thing. But what should I be doing? I have friends who are using Claude a lot, but I can’t quite figure out what particularly agentic AI should be doing for me. Azhar: You know, I’m really sympathetic to that because I have the same issue. These tools have been developed by software developers in a really particular part of the world, which is Silicon Valley, where the culture really revolves around the art of the programmer. And so if you have a programmer’s day and you think in coding terms and you have programming workflows, it becomes really obvious what you do with a really advanced AI tool. I do a lot of research, some of it qualitative, some of it quantitative, and in such a world, those workflows don’t match the way that I think through problems. And so the way that I get around this is that I do look at things on Twitter or X as it’s called because people are sharing tips. And I often just ask the models, you know, “What could I do with you given that I’m trying to do this thing? I’m trying to solve this problem.” And it will come back and give me a suggestion. And I have had some success with agents. So I have an agent called R. Mini Arnold. So R is a play Isaac Asimov’s robots. They’re all called R. Arnold is after the good Terminator in Terminator 2, played by Arnold Schwarzenegger, who protects humanity. And R. Mini Arnold is available on my WhatsApp and it’s available on email. Krugman: Okay. Azhar: And it has access to a whole set of resources. It can browse the web, it can access LinkedIn, it can access Twitter, it can look at my library of PDFs of research that I’ve downloaded. And I can throw tasks to it a little bit like I would say a pretty decent but slightly temperamental graduate student. So sometimes it just disappears for six or seven hours at a time. And one of the differences between using an agent like that and using Claude is that R. Mini Arnold has a lot of my life’s context. It knows the music I like, it knows the book I’m working on, it knows the investments I’m making, it knows the essays I’m doing, it’s got the calendar of speeches that I’m about to give. And so when it goes off and does a task, it tries to figure out what in my world is this going to be relevant to and where can I draw threads from? And when it works, it is really sublime and it does feel a little bit like science fiction. But I would say it’s incredibly brittle. I mean there’s breaks every four or five days. A specific example was, I was thinking about the Paul David’s research about why electrification took the time it took. And I wanted to understand what were the determinations of determinants of that thirty-five year lag from Pearl Street generation to, you know, productivity growth. What could the levers be? And so I threw that into R. Mini Arnold and it set up a team of sub agents which had personalities of key economists and was able to go off and do research the way the AIs do, but also research on all the academic papers that I have downloaded in the past. I have access to JSTOR, I’m allowed to download a hundred PDFs a month. It can look at all of those and start to compile an answer in a way that perhaps a Chat GPT can’t. And it knows the context of my book and it knows the context of the essay I wrote. So what then comes back is something a little bit more structured that I can then play with. It’s a marginal improvement on doing this on Chat GPT. I’m sure you could probably figure out how to do it. But it’s quick. I use it on my iPhone. I often do this when I’m walking through the airport and I want to solve this and have this result when I’m sitting on the plane. I’ll fire that query out and it goes back and goes out and sorts that out for me. Krugman: Okay, I guess I’m getting it. But obviously you and I are not typical. The people who are using AI the most are going to be middle managers, business people, etc. And I find myself thinking about what I think of as the homemade pasta problem. Azhar: Mm. Krugman: You’re probably too young for this, but there was a time when I when young and we were using stone axes for computing, and there was a big fad of making your own pasta. Little pasta machines were everywhere. And then at a certain point there was kind of a collective, “What the hell are we doing? You know, store bought pasta is actually better. The Italians don’t do this.” And I have to think that for most tasks, the range of agents can’t be that wide. But why wouldn’t they sell that kind of thing off-the-shelf, as it were? Azhar: Yeah, well I think it’s different for an independent person or a small business or a middle manager in a big company. I would imagine that you will start to see people selling specific agents that solve your marketing problem. If you have a barber’s shop and you’ve got four chairs and maybe 30 people a day coming through. Right now what you do is, you go to ChatGPT and you help it write your collateral for your website. That feels like it’s an interim step to somebody delivering the actual finished product. Why haven’t we seen it? I think we haven’t seen it yet because the terrain is still big enough. Beyond Anthropic and OpenAI, there’s a lot of other companies building agents that are these end-to-end workflows for businesses. They still believe that the prize for them is to build the generic platform that is the tool for all tools. Because if you get that right, you have a much, much bigger business than if you’re just a vertical application. And I think we’re only a year or two into these entrepreneurs building such businesses. I think as some of them succeed and some fail, the ones that are not able to succeed in the general space will start to verticalize, which is what we saw in the advent of the internet. We saw it in software as well. But I think within a big company it’s a different set of questions because you have far fewer degrees of freedom as a marketing manager in a large company than you do if you own your own barbershop. You have all these rules, you have all these other teams you have to interface with, you are held to the priorities and the plans of the company as a whole. And in that instance, I think, it’s much harder to see how you use AI to really change the way you work. Krugman: Yeah, I mean, again we’re talking about ancient history here, but you know, everybody still uses Excel, even though it has always been horrible. But the constraints of corporate life mean that everybody has to use Excel. So that means maybe we’ll see quite a lot less coding a few years down the pike because the people will just be able to purchase whatever it is they need. I don’t know. Azhar: I think there’s a balance. You hear people proselytizing heavily, saying, “I think this technology is going to be impressive and have a significant impact.” But when people pitch this, they forget that there are other actors in the market who might respond to what’s going on. Right now, if you’re a large company, you want to be building as much as you can because what you can buy isn’t right for the market. If you think about Henry Ford putting together the Highland Park plant, he couldn’t go to a supply chain and buy what he needed because nobody was thinking in those terms. I think we are slightly at that stage for large corporates now. Whether we’ll be there in five years, I don’t know. The question we have to consider is where the value will reside: between having your own capabilities to design software for your processes, or handing that over to another company designing software for a hundred businesses like yours. Historically, it has made more sense to hand it over to another company, but the cost curves may have changed sufficiently that you’d rather have the nuance and control to do whatever ‘vibe coding’ becomes in 2030. Krugman: I know with healthcare software, organizations like the VA that built their own have done much better than the ones who tried to buy it from Microsoft. So yeah, it might be a story that makes sense. And actually, since we’re talking about going for the models versus something much more specific, how do you think about the Chinese versus the big US AI firms? Azhar: I’ve just spent eight days in China and I was really fortunate. I got to speak to developers and engineers and management from about a dozen of the Chinese labs. In many cases they hosted us in their offices. The main thing the Chinese companies say about the US firms, is that Claude code is brilliant and Claude is the best model that is out there and they really couldn’t get enough of it. The term is, they’re Claude-pilled. They talk about the constraints on getting access to computational power but just in a way that’s a fact of life. I mean there’s no sort of commentary on it other than it’s hard. They have to figure out how to get around that and how to build a culture of efficiency when you don’t have as much [computational power] and I think they have built a culture of efficiency really, really well. I think it’s going to help them over the longer term. They don’t really talk about competition with US labs the way the US talks about competition with China. But they do see themselves competing with each other. And as you know, that’s what the Chinese economy is. It’s mayors in different cities who almost act as venture capitalists who compete tooth and nail with each other to become the electric vehicle hub or the solar hub or the AI hub of the nation. And what I would say is, the models are really, really capable. They’re very efficient, which is why they’re so cheap to run, which makes them very competitive for a whole range of tasks. But at the margin, it’s instructive to note that everyone was using Claude for coding as opposed to the cheaper Chinese version. Krugman: That’s interesting. So you can imagine a future where a lot of businesses are actually using these less comprehensive but much cheaper models. I think what I’m gathering from you and from other people is that a lot of entrepreneurs in the US are still dreaming of the uber-model that solves all problems but that probably is not going the way it all goes. That in the end we’re gonna end up with a lot of specialized models, but also the uber-models will still have a role. Azhar: Yeah, it never made sense to me that you’d have a single model that would do everything because if the single model is going to solve the Riemann hypothesis, it’s gonna require a lot of resources. And if all you need to do is get it to root a bill to the finance department, it seems a bit silly to ask Einstein to come and do that for you. We’ve had segmentation of markets for a long time and it’s like with airlines. There’s a reason why not every seat on an airline is first class. Some passengers don’t want it, don’t need it, won’t want to pay for it. So I do think that the ecology looks like a whole array of much, much cheaper models that are serving by volume lots of corporate needs, and then having more sophisticated, complex models for the more complex tasks. I think you’re already starting to see this. I don’t see it, by the way, as a shock to the industry. I just think this is what happens as an industry matures. You know, you start with one size fits all, then you start to segment your customer needs and you start to serve them in the most profitable way you possibly can. And that just feels to me like the way that the markets have matured. Krugman: Okay. Let’s move to more macro considerations. People have been worrying about a bubble. A lot of us still remember the nineties quite vividly and think about all of that. But you just aren’t seeing the bubble. You wanna talk about that? Azhar: I remember what it was like in the nineties. I lived through that one and also the housing bubble, which frankly was far, far worse and much more terrifying. I have a really simple mantra here, which is that honest customer revenues tend to be the engine that gets you through this, right? You know, what caused the problems with the US railroads in the 1870s and 1880s? It was that the revenues didn’t materialize because the tracks were being laid in places where there were no towns. That was a problem. The same was true in the dot-com era. My team and I realized last year that it’s very hard to get good quality data on how much was actually being spent by American businesses and consumers on AI. So we’ve spent several months building systems and gathering data to give a deduplicated view of what that number is. And just to give you a sneak preview, is $150 billion per annum, annualized at the end of May 2026, and about 90 billion dollars in the previous 12 months, from May ‘25 to May ‘26. So you can see it’s growing, and those are deduplicated numbers. So if you spend a dollar with OpenAI, and they have to pay Microsoft 60 cents to run the servers, we only count that as a dollar. We don’t count it as, you know, $1.60. It’s a much faster revenue growth rate than mobile or the internet. It’s also a small number because the US is a $32 trillion economy. And I think the thing is that at that level of spend, you are able to roughly cover the depreciation on the enormous capital expenditures that have gone into AI just this past year. But next year or the year after, you have to double your revenues again and again in order to cover these increasing commitments. The thing that often pricks a bubble is when financing starts to get a bit smelly. That was clearly the case in the global financial crisis, where synthetic collateralized obligations were magnifying the risk on subprime mortgages—it was all “smelly finance.” In the dot-com bubble, the dot-coms themselves didn’t really have much smell about them. There was a lot of disbelief, but the telecoms clearly had issues with their internal revenue generation. So the other thing that we look at is how bad, poor, or strong or robust is the funding quality. And that funding quality measure is definitely getting worse. It’s worse now than it was nine months ago. But it doesn’t seem from the numbers to be at the level that it has been historically when these things have imploded. Nor does it seem to be the type of exposure that is really systemic, which is what we saw in the global financial crisis. There are companies like Oracle and Coreweave whose debt looks very risky, and it’s harder and harder for them perhaps to raise money, although Oracle just did. But it doesn’t feel like it’s systemic. You know, when the the global financial crisis popped, no one knew who was in trouble, whereas now you’d be able to isolate it with a single company or a single firm. So at the moment we feel that this is still a demand-led boom, that funding quality has definitely gotten worse, but not so bad that I would say that there is an imminent problem on the horizon. Krugman: So at this point, you’re saying that roughly speaking, final demand for this is about half a percent of GDP. What share are AI-related stocks in market value? It has to be substantially larger than that. Azhar: They’re about forty percent of the S&P 500 right now. Krugman: That’s a huge mismatch. Revenues are not the same as profits, but you’re talking about what is still a relatively small business relative to this immense economy, yet it dominates the financial markets. That would be at least a possible source of alarm. Azhar: Let’s dig into that, because a stock price is a reflection of the expected future value aggregated across the market. Forty percent feels high, but if you look at the measure of earnings, these companies actually have a much higher proportion of earnings and earnings growth. If you look at the US stock market in 1900, after the railway calamities of the mid-to-late 19th century, railroad stocks were sixty percent of the capitalization of the US market. We had worked our way through the busts by that point. There’s a fantastic piece of academic work by an American finance professor named Bessenbinder. He looked at the stock returns of 23,000 US stocks from the 1900s through 2022. Those returns are highly concentrated. About two-thirds are concentrated in roughly 30 companies. Those companies are oil, electricity, or car companies—the general-purpose technologies at the start of the 20th century—or they are the IT companies like Apple and Nvidia. The only exceptions were Walmart, a couple of healthcare businesses like Pfizer, and JP Morgan. Historically, you get this concentration of a number of winners when you have a new general-purpose technology, and that is showing up today. I don’t feel we’re overly concentrated from the perspective of risk, and the price does not feel totally out of whack compared to where we were during the dot-com era. Krugman: One last devil’s advocate question. I keep thinking of the California gold rush. If you had looked at the revenue and spending on gold-rush-related businesses as a whole, it probably looked solid. But the trouble is it wasn’t the gold; it was the picks, shovels, blue jeans, women and whiskey that were the revenue streams. Is that a fair question to ask about AI right now? Azhar: It’s a great question to ask. The question is what determines that $150 billion annualized demand? We see that just under 30% of the S&P 500 have pointed to a generative AI project with a quantifiable result in their earnings calls. They are under pressure to say they do this, so maybe that’s what’s going on. But when I talk to executives, like 30 finance businesses in New York, they all plan to spend more next year, even though not a single one could point to even a 10 basis point improvement in their business from the investments made so far. Krugman: Right. Azhar: When we break out that $90 billion, $60 billion of it is in the US. That’s a lot of money for a single company, but spread across thousands of firms, it’s still at the experimental stage. We should consider whether these executives are learning by doing. The messages I get vary from those having success in the tens of millions who want to reach hundreds of millions, to those finding it harder but persisting. We’re slightly beyond pure picks and shovels, but in Paul David’s work, it took 50% of American companies getting electrified before the productivity rise. We’re a long way from that. Krugman: Headlines flashed about a KPMG study with case studies on the usefulness of AI [https://smallpdf.com/file#s=a35e268b-87cf-4380-b3f2-77b78c9e2274&r=read] that turned out to be AI hallucinations. It’s a wonderful thing. Azhar: It is brilliant. One thing that is quite challenging is that the market has talked a lot about bottlenecks. We saw this with railroads when the US couldn’t make enough steel. There are these bottlenecks, and there’s a lot of emphasis on power and getting electricity to the system. There’s more demand than supply capacity for AI right now, but there’s a question of whether there’s enough capital. We may see another few trillion dollars of intention from tech companies to build infrastructure to 2030, which starts to rival the new issuance of the US Treasury at $2 trillion a year. I’m wondering if this capital constraint is going to be an issue or if the market knows how to clear it. Krugman: Ordinarily, we’d expect to see that in prices. Real interest rates are well off their pre-COVID lows. They are higher now, but still substantially lower than at the peak of the nineties tech boom, when they were around four percent. They’re more like two now. It’s surprising, given the AI boom and massive budget deficits, that rates aren’t even higher. Whether this is an actual constraint, Nvidia is not the US Treasury. They need risk-tolerant capital. The possibility that these firms may not be able to raise enough money is something we need to think about. Azhar: Yeah. On that Nvidia point, I saw that credit default swaps on five-year Nvidia bonds—the cost of insurance against default—are currently lower than US Treasuries. Krugman: I saw that, and it strikes me as completely crazy. If you think the US government is not reliable, you shouldn’t be investing in chip stocks; you should be investing in canned goods for your bomb shelter. But anyway. Azhar: Are you telling me that markets aren’t perfectly rational, Paul? Krugman: Good heavens, I can’t say that; they’d take away my economist card. We’re recording this on SpaceX Day, and I’ve been wondering if there are limited pools of capital for cutting-edge investments. I wonder whether Elon Musk is diverting capital that AI might need. A whole lot of meme money is pouring into SpaceX right now. Is that something I should be thinking about? I mean, he’s got what everybody tells me is a crud AI product in Grok, and yet… Azeem: Musk showed his willingness to adapt; his AI product is now being subsidiarized using his capacity to serve customers like Anthropic. He has an incredible following, but people who have worked with him say his ability to relentlessly focus and optimize sets him apart. His first-principles thinking has brought down the cost of space launches faster than anyone in history. He pushes the rate of learning aggressively. For all the challenges and his mercurial behavior elsewhere, that’s generally a good thing because technology has brought down the cost of inputs significantly. We’re going to be much further ahead in space than we would have been if SpaceX had not been successful. It raises questions about how to govern what used to be a commons, but there is a definite benefit from coming down that learning curve so quickly. Krugman: That’s fair. The one time I looked at Musk’s activities and thought he was really onto something was when I realized he diagnosed that the cost of space launches is really the rocket, not the fuel, and recovering it makes all the difference. Being able to make it happen is a real productivity thing. This is all moving so fast that we don’t have time for the technical productivity issues we had in the past. It’s feeling like a Solow moment where people say, “I see the technology everywhere but in the productivity statistics.” Do you want to talk about that? Azhar: It comes up all the time. I wonder if we need things to happen more quickly than we used to. We aren’t seeing it in the numbers yet. Erik Brynjolfsson at Stanford says he thinks it is showing up in the aggregate numbers. How quickly should we expect a technology like this to show up? At $90 billion a year, that’s not much of US GDP. These are early stages where companies are learning. The first $100 million you might spend on AI is about learning, and we’re in that mistake-making phase. The model Paul David and William Devine talked about in electricity is helpful. In the first phases, you’re retrofitting your capital stock and processes with the new technology. It’s not until you depreciate existing capital and change processes—like Ford did at Highland Park—that you see productivity benefits. To put numbers to that, what would we expect to see in the Ford equivalent of Highland Park in terms of output? Krugman: Yeah. Azhar: I thought we might see what happens to revenues per employee in an AI-native firm. Across high-end companies like McKinsey, it’s about $400,000. For Meta or Google, it’s about two to two and a half million dollars. In AI-native firms like Mercor, that number is closer to seven million dollars per employee. For Anthropic, it’s close to ten million. You can measure the enormous commercial productivity of a single employee if a firm is AI-native. We’re talking about a handful of firms, but we can pick up the shape of what’s possible for the productivity of a single employee. It may be hard, it may take time, but it’s possible. Krugman: What would those numbers look like per dollar of invested capital? One worry is that this is an enormously capital-intensive business that replaces labor. The oil refineries of New Jersey have enormous revenue per employee because there are no workers, just monstrous capital installations. Is that a factor? Azhar: Anthropic has raised in the tens of billions rather than hundreds of billions and had a profitable quarter ahead of schedule. What we don’t know is how much of that capital goes into developing the next model versus monetizing previous generations. Their IPO in the next six to nine months will tell us. Chinese companies are using much less capital to build models that are nearly as good. So I think the harder part of your question is that if every model that OpenAI or Anthropic costs ten times as much to deploy and develop, but lasts only a couple of years before it’s defunct because of competition, what needs to be true for that to be sustainable for more than a year or two? To me, that is a really tricky question as well. Krugman: You’ve cited intermediate measures. Rather than revenue, we look at generated lines of code, which has exploded, versus actual usable applications, which hasn’t. Does that tell us anything? Azhar: Lines of code is an odd measure. We’ve made it much cheaper to write code, so less determined people are writing it now. It’s unsurprising the increase hasn’t been met by proportional productivity. Data suggests we’re getting more high-quality code, but also a lot of useless waste. This isn’t the first time a useful input in the economy generated waste. Think of a barrel of oil: we count the whole value in GDP, but two-thirds is thrown away as waste heat. Only one-third is useful energy. Sloppy lines of code are a similar form of waste we’ve been happy to tolerate in other sectors for a century. Krugman: A weird analogy is when widespread word processing came in. Books started getting longer. It was so easy for authors to turn out hundreds of pages. What might have been a two-volume series became five. Azhar: On that front, we’re at an enlightenment moment. In 18th-century France, the battle was over who gets to write and express their story. Men and women produced remarkable works with quill pens that encapsulated a world. Krugman: Right. Azhar: Is it worse that we allow for more expression? We are worse off when that connects to an algorithmic recommendation system that drives constant slop at us. But we aren’t inevitably worse off because we’re giving access to many more people. In reducing costs of access, we might find amazing people. In breaking down silos of knowledge, we might find connections—perhaps something in battery chemistry that is useful in cardiology. We don’t know because we’ve never been able to get those experts to talk. I look at each opportunity discreetly. Krugman: There is a potential book here: The Upside of Slop. This is an unrecognizable scene from eighteen months ago. Wow. Azhar: We could get ChatGPT to write it. Krugman: I started my career writing papers longhand on yellow legal pads. Amazing change. Azhar: I still write everything with a fountain pen. I’m writing my new book longhand and most of my research is too. The computer is turned off because AI does all the boring stuff like PowerPoint and emails, giving me time to apply my brain to things I want to think about. I’d be happy to continue this conversation in a few months. Thank you for inviting me. Krugman: Thanks so much. Take care. Get full access to Paul Krugman at paulkrugman.substack.com/subscribe [https://paulkrugman.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]

A Gesture of Contempt

A quick video, thankfully not from Midtown Manhattan Hi there. Paul Krugman with a very quick update. I haven’t done a regular post today because I’m jet-lagged out of my mind, but I just wanted to weigh in on something that will be happening a few minutes after I record this. Which is that a significant piece of Midtown Manhattan — the area surrounding Madison Square Garden — is about to be closed to all pedestrians. This is because of the Knicks game which is in Madison Square Garden. And Donald Trump is attending the Knicks game. Which means that the game entry itself is going to require enormously strict security. People are forbidden from bringing any kind of bag in there. It means that what should be an exciting joyous occasion is going to become quite hellish with long lines and who knows what else. But what really may not be obvious to many people — you might not know if you’re not a New Yorker — is that Madison Square Garden sits on top of Penn Station. That’s a story in itself, but there it is. And Penn Station is the busiest transit hub in America. It is where 600,000 or so people pass through on their way to and from New York by way of the Long Island Railroad and New Jersey Transit. I’ve spent a lot of my life waiting for trains at Penn Station. And it’s completely insane to ruin people’s day like that. You could say, well, what else are you going to do if you’re going to have to provide security for the President of the United States? And the answer is, Why does he have to go to this thing? The simple way to make several hundred thousand people’s lives noticeably better, at least for today, would be to just not go to the damn game. He can watch it on TV. He can go have a cage match in the ripped up White House lawn, if he likes. It’s not such a small thing. It shows a kind of contempt for ordinary people and a kind of self-aggrandizement — I want this so I’m going to make other people’s lives miserable just to indulge my whim — that is part and parcel of everything else that’s going on. It’s a small thing but my god I would actually have had a problem if I went into my office today because my office is not that far from Penn Station. It’s not in the banned zone but it’s going to be nightmares all around. All right, just another message that the people in charge do not care about people like you. Get full access to Paul Krugman at paulkrugman.substack.com/subscribe [https://paulkrugman.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]

Comments on a Freaky Friday

Hi everybody. I’ve been having an extremely busy week, so no two talking heads conversation this week. Just my head talking alone for a relatively short time. Hi, I’m Paul Krugman. I’m winding down some travel, and I’ve been meeting all sorts of people face to face, so virtual interactions are down. So just to give you some kind of Saturday video, I thought I would talk a little bit about latest economic news, markets — things that I don’t normally weigh in very much because that kind of market commentary is usually something that is best done by business economists who are focusing on the day-to-day stuff talking to market participants. But I think that the latest stuff is interesting enough to warrant some discussion and maybe a way to think about where we are economically right now. So okay, if you’re paying attention to this stuff you probably know that yesterday was a job report day. The report was unusually strong, certainly stronger than almost any of the professional forecasters expected, 172,000 jobs. Predictably, Trump first boasted about this with a lot of talk about how you know we didn’t have this kind of prosperity under Joe Biden. It is kind of odd given how well things are supposedly going how much Trump and his people talk about Biden. If it was really that much better would you need to be constantly comparing yourself and making claims about how much better you’re doing? For what it’s worth you know how often during his 48 months in the White House did Biden preside over job reports that were as good as yesterday’s in terms of job creation? The answer is 37 times. Now, there are reasons why the rapid job growth of the early Biden years, which was coming out of the COVID slump, can’t be replicated. And the fact that immigration is way down means that a normal jobs report is going to be a lower number. But still this was unexpectedly high job growth but not really something that should alter your fundamental view about how the economy works, although the near-term outlook looks stronger than you might have thought. One thing I should say, since there are some people wondering, can we trust these numbers? And particularly pointing out that the unemployment rate did not fall, even though we had a unexpectedly big job creation number and wondering how does that add up, are these books being cooked? The answer is no. You’re not helping by saying that. I’m not saying that the books might not be cooked at some time in the future, but we will know. It will be obvious that this is happening. And it would basically be impossible to do it without there being lots of warning bells, without there being lots of whistleblowers. So far, the Bureau of Labor Statistics is still apolitical, professional — under-resourced, which is becoming a problem — but these are the best numbers they could do. If you’re puzzled by how we can have strong job growth and no change in the unemployment rate, the answer is that these are two different surveys. The unemployment rate is based on a survey of households. The job creation number is based on a survey of employers. Those numbers don’t have to match up. I mean, in an ideal world, they would always tell the same story, but there’s statistical noise, there’s sampling error, there’s just conceptual differences. So this kind of discrepancy is not that unusual. And what it really tells you is, well, is the economy, is the labor market really sort of flat, which is what the unemployment numbers suggest, or are we seeing at least a mini boom in employment, which is what the nonfarm payroll numbers suggest? And the answer is who knows? Time will tell. Over the course of a year there’s not usually a significant discrepancy in the stories these numbers tell; month by month, well, it’s noisy and you shouldn’t overreact. Okay trying to make sense of what is going on — why is the labor market as strong as it appears to be? One important point about the economy right now is that there are three big forces that are hitting us. It would be really great from the point of view of professional economists if just one thing would happen at a time. But unfortunately, that’s not how it works. So there are three things happening. First, we are still feeling the effects of Trump’s erratic tariff policy, which has had a depressing effect on employment — not so much the tariffs themselves as the uncertainty. It’s very hard for businesses to make plans, very risky for them to sink money into new ventures when they have no idea what the tariff regime will be a few months down the road. But that uncertainty probably did a one-time hit to employment which is mostly probably behind us because yeah we have crazy erratic trade policy, but that’s now just a piece of the landscape which affects the level of employment, maybe, but not the rate of growth. The second thing is AI. So we have this enormous boom in spending on data centers, a large surge in investment, big rise in stock prices because of hopes about what AI might return. There are not that many people who benefit from high stock prices, but these are people with a lot of money and a lot of spending power. And if they go out and spend more, that boosts the economy. So that’s a sort of force that operates in opposition to the effects of the tariffs. And possibly the AI-driven spending is coming on now while the tariff effect is sort of closing out. About oil: For what it’s worth, prediction markets are by and large evil things, but they do give you a quick way of summarizing conventional wisdom. And just about a week ago, Kalshi said that the probability that the Strait of Hormuz would be open by August 1st was 60%. It’s now 26%. So people have justifiably gotten very skeptical of White House pronouncements that this is just about over. They should have been more skeptical before. But anyway, it just does not look like it’s going to open. And there’s a still huge remaining uncertainty about what does this imply? Through all of this there’s been a dichotomy between people in financial markets — including people in the futures market for oil who are presumably more professional, less vibes driven than a lot of investors — and what people who actually study the physical market for oil have to say. And right now futures prices are way up from where they were before the war, but they’re still under $100. Yet the oil industry people are basically hair on fire, saying, we’ve been meeting the loss of supply from the closure of the strait by drawing down inventories and the inventories are very close to critical critically low levels — there’s a certain amount you need to just sort of function — and there were a lot of warnings that really bad things would happen if the strait wasn’t reopened by June 1st. Well guess what here we are, it’s June 6th, D-Day, and the strait is not open. So is there a really severe oil crunch just a few weeks down the pike, or is it kind of manageable? So are we going to be hovering around current oil prices? I still find the physical oil argument quite persuasive, but I do wonder, again, it’s not like there are a lot of meme stock investors speculating in oil futures. That’s not a market that you would expect to be highly emotional. We know that there are insider traders who seem to know what Donald Trump is going to do a few minutes before he does it, who are in the market, but they’re probably not enough to be seriously, on a sustained basis, distorting the price. So I don’t know what’s happening on the oil scene except that it is a source of worry. Other objective economic facts: that jobs report also showed wage growth slowing, which it has been doing for a while, at the same time as inflation has been accelerating. Inflation was first pushed up by the tariffs, and now has been pushed up further by oil prices and prices of other goods, fertilizer, helium, that were transiting the Strait of Hormuz. That hit to prices is not all the way through the system. There’s a lot of effects, particularly from diesel prices and also fertilizer, that will show up over time in higher prices of goods that involve using these hydrocarbon-based resources to operate. So inflation is likely to stay elevated for a while. With wage growth slowing down, we are almost surely looking at least another couple of months of falling real wages, which is not a good thing. I’m a little skeptical of all the K-shaped economy stories — up at the top and down at the bottom. A lot of that is sort of going beyond what the data really say. But it is definitely true that people who earn their income are being hit by inflation and not being compensated with higher wages, while people who own lots of stocks have been doing much, much better. So that’s a real bifurcation. Of course, people who own lots of stocks are not feeling as good as they did a week ago. We’ve had a significant fall in the stock market and then a real tumble yesterday, more than 4% on the NASDAQ, somewhat less on the other indices, but still significant decline in stocks. The President of the United States went on a rage tweeting or whatever rage truth socialing spree sand said good jobs report should send stocks should go up not down. He somehow or other managed to find ways to contrast himself with Biden and make a lot of accusations against industry people who under-forecast this jobs number as suffering from Trump derangement syndrome. Actually, a quick point there about conspiracy theorizing. I know people who have to do these NFP, non-farm payroll projections, and they are, whatever their personal views, their job depends on being as correct as possible in the forecast. Every month, they’re evaluated. They have a story. They have a number. Their prediction will be wrong. But there’s always a question, were you better or worse than other forecasters? They do not have any space to indulge their political views. They will get it wrong. This happens all the time. The economy is a complicated thing. And even with the best will in the world even with the best information in the world, you are going to get it wrong. The idea that there’s a special negativity of economic forecasters towards Trump is ridiculous if you were awake during the last five years. Many of us still remember when Bloomberg put the odds of recession, this was in 2022, put the odds of recession over the next year at 100%. There was no recession. I don’t think I ever suggested that the professional forecasting of the economy was politicized. And I don’t think it was politicized either for or against Biden, and it isn’t politicized for or against Trump. There was a fundamental misconception, I think, behind those recession forecasts. But that is not a case of politicization. Anyway, there’s certainly no call for Trump to see himself as a victim. So what is happening? Trump professed to be baffled that a good jobs number should make stocks go down. But of course, it’s actually quite straightforward. What’s happening here is that with the combination of elevated inflation, now largely driven by the effects of Iran, and a job market that is holding up — that is not, in fact, falling off a cliff, if anything, appears to be accelerating — there is no case for cutting interest rates. A few months ago it seemed plausible that there would be some reduction in interest rates, that the Fed would have a rate cut or two this year. Now the chance of a rate cut, according to the market implied probability uh is around one percent. So there’s essentially no chance that rates will be cut and last I saw the market implied probability that rates will actually be increased is about 70 percent. Not big rate hikes but the Fed is probably going to find itself wanting to lean against potential inflation, against the possibility that inflation might get entrenched in the economy which is always their great concern. That’s not going to lead to drastic action but by any historical criteria there are is no case for cutting rates and there’s starting to be a reasonable case for increasing rates. Lots of stuff can happen but probably not soon so your expectation about what’s going to happen to the fed funds rate which is a very short term rate, actually literally overnight, has risen substantially that in turn leads to higher rates on longer term stuff which is what matters for economic activity. And that rise in interest rates hurts stocks. There’s always a couple of different ways to say this, but should you put your money in stocks or in bonds, well, if interest rates are higher, people are less inclined to put in stocks or what is really an equivalent thing, since the price of a stock depends upon expectations of profits in the future, if interest rates are higher those future profits are discounted more which means that the price of stocks should fall. And consistent with that story, the biggest falls in yesterday’s action were in stocks whose value depends much more on profits, hoped for profits sometime well into the future. So the NASDAQ fell 4%. The S&P, which is kind of a mixture of growth stocks and stocks that are driven more by current earnings fell less than that. The Dow, which is even more established companies who already have their profit flows fell less. So this was very clearly interest rates are going to go up because the economy is holding up while inflation is a little worrying and the Fed is not going to cut rates and may well raise rates so of course stocks are down. Nothing odd about that, nothing perverse. All that we learn is that the President of the United States doesn’t understand any of this and he just thinks that he should get interest rate cuts as a gold star for his incredible efforts. The interesting plot here is what does this do to Kevin Warsh, the new chairman of the Fed? Warsh was installed by Trump as somebody who Trump believes will do his will, that he will cut interest rates because Trump says we should cut interest rates and that he will find ways to justify it. And Warsh has been gesturing in that direction, calling upon the Fed to use different measures of inflation that look more benign than the standard measures. That’s an interesting debate, but it’s just so obviously motivated reasoning. It clearly says pick the inflation measures that show the lowest inflation so that we can make a better case for interest rate cuts, which is what Donald Trump wants. It’s clear that this is not a serious intellectual argument. But I think he has basically no chance of getting those rate cuts. Again, the Fed is not a dictatorship, it’s not even like a corporation where the CEO gets to make big decisions on his own. The Fed’s interest rate policy is set by a committee — the federal open market committee — which is a mixture of long-serving members of the federal reserve board and presidents of regional feds. Basically it’s not answerable to Donald trump it’s answerable in the long run to elected politicians, but that’s quite a long-run thing. And outside of Trump’s creatures, there is zero support for interest rate cuts on the Fed board now, as there should be none. The logic of an economy where employment still seems to be plugging along and inflation is high is not one in which there’s any rational argument for cutting interest rates. So what does Warsh do? Does he act like a professional central banker, in which case he will incur enormous rage from the White House, or does he advocate for stuff that he knows, he’s not stupid, and that everybody else, that all of his colleagues know is really, really bad policy, and then just keep losing votes at the FOMC, thereby becoming the least respected, least influential Fed chairman in history. and I don’t know which way that goes but pass the popcorn. I hope that I’ve been clear in the past in warning people against expecting instant gratification in people who are opposed to Trump in expecting instant gratification I’ve been I’ve made that mistake myself as well but if you want the fact that Trump is doing terrible things, which he is, to cause a severe recession now or a month from now or six months from now, well, unfortunately economics is not a morality play. The wages of bad behavior take much much longer and are much more diffuse. There’s all kinds of things happening out there so the idea that you could expect catastrophe just because you have catastrophically bad leadership is true in warfare as we’re seeing in Iran, it’s true maybe at the level of corporate competition. But something like the US economy is a lot less sensitive especially in the short run to the quality of leadership at the top of the United States because the US government influences the economy but doesn’t run it so this is not going to be the kind of spectacular flame out that many people would like for political reasons to see. So on we go. For what it’s worth, I don’t see anything that’s happening now that will turn around the public’s extremely negative view of the economy. Most people don’t care what the job number is, as they shouldn’t. It’s not something that affects their lives directly. The perceived state of things is that although we don’t have high unemployment, jobs are hard to find and prices are rising and they’re rising faster than wages. That’s not an ideological point, that’s just a fact. So people are going to stay negative and I guess have some sense that we have crazy erratic leadership. And loud proclamations that this is the hottest economy ever and it’s great and it’s wonderful are almost truly counterproductive politically. This is a time when Trump could really take some lessons from Bill Clinton and say that he feels our pain, which would be a lie. He doesn’t, but he can’t even pretend that he does. And so this is going to continue to be a very negative economic situation. The one thing that I think Trump thought he had was the stock market, which is again not that relevant to many people but statistically appears to have some impact on consumer sentiment so naturally he’s enraged that stocks went down after yesterday’s pretty good jobs report. So I do think that we’re looking at a situation where it’s hard to explain why people are quite as negative on the economy as they are, except that it they have a kind of cumulative feeling that the system is rigged and that the people in charge are not on their side, which at this point is very much true. So this is very unlikely to turn around, certainly very unlikely since everything is political, very unlikely to turn around before the midterm elections. I think that was a happy note. Anyway, take care and I’ll be back to my regular format of interviews and everything else in a few days. Bye. Get full access to Paul Krugman at paulkrugman.substack.com/subscribe [https://paulkrugman.substack.com/subscribe?utm_medium=podcast&utm_campaign=CTA_4]