The Big Macro Force Thats Been Driving Stocks Higher For Years

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Hello and welcome to another episode of the Odd Lots podcast. I’m Joe Weisenthal. And I’m Tracy Alloway. So Tracy, one of the things that we’ve been talking about a fair amount everyone’s talking about it, I guess is how the biggest, most profitable companies in America, they’re still really big, they’re still really profitable, but they’ve switched from being throwing off tons of free cash flow to big investors spending a lot of money. Yeah, that’s right. So we’ve had years and years and years of big tech basically I guess generating infinite amounts of cash it feels like. And now they’re switching to actually spending some of that cash to build very expensive data centers and things like that. And you’re right, it is kind of a change for the market.

Yeah. Right? Like we haven’t seen that scale of investment for a very long time. Certainly not I don’t think in our lifetimes, have we? I don’t know. No, I it doesn’t feel like it. I mean you know, I guess maybe we’ll get into this in the conversation. You know, I think if you go back to like pre-GFC era when a lot of the really big companies in the index were like, you know, Exxon was the biggest company in the world for a long time. So they would have always been having to like spend because you can’t just sort of like passively collect oil etc. But it does seem generally true that the big theme both with financials and tech is this incredible ability to generate huge returns with fairly modest capital outlays whether we’re talking about equipment, plants, or even human labor. Well, the other big switch is just, you know, if you look at it just at the tech sector basically which has been, you know, the dominant force in our equity markets for a while now. But for much of the 2000s the investment was in sort of like intangible. Yeah. you know, SaaS type stuff. And now we’re switching to really like brick and mortar. They’re paying to build energy capacity and they’re paying for actual chips and actual buildings to house a bunch of air conditioners and servers and all of that. No, it’s it’s totally true. This is the big theme, right, is just this. So the question is like, okay, they’re still making a ton of money, they’re still very profitable. And maybe these investments will pay off in a massive way at some point down the future. But can investors expect the same level of returns that they’ve seen in the past if there’s this big switch in terms of strategic decision-making in terms of capital outlays and so forth, taking on debt? What does this mean for the markets? What does this mean for investors? And I don’t know the answer, but maybe our guest. Well, also, I mean you and I, I think for the past 20 years we have all gotten very used to everyone saying that the tech sector is overvalued, right? Like even as it throws off infinite amounts of cash, everyone is like, “Ah, so overvalued. The market’s at a top. The market’s at a top.” That has been the case for pretty much like my entire mature investing age lifetime. Right. And so you bring up a really another important dimension of this which is just that valuations by traditional metric I mean I remember, you know, early on what was it the Shiller the Shiller CAPE ratio and there’s like this has got to mean revert. It this is we’re at the 98th percentile of historical valuation and it keeps going up and so forth.

Mean reversion is always around the corner, Joe. It’s always coming mean reversion.

But no, this is another question. Why didn’t it mean revert, right? And why have just the multiples that we’ve seen on traditional price-to-earnings ratios, you look at them, they make you go crazy and they got to come down. Why haven’t they? Right.

That’s an also an interesting question that we need to get answers to even beyond the specific capital question.

Yeah, let’s do it. All right. Well, I’m very excited to say we do have the perfect guest today because we are speaking to someone who’s really done a lot of research on some of these exact questions including he published a paper co-authored a recent paper that really caught my eye back in January called a macroeconomic perspective on stock market valuation ratios. So it’s good that you brought up the earnings metrics. We’re going to be speaking with Jonathan Heathcote, one of the co-authors of this paper. He’s an economist at the Minneapolis Fed. We’re going to talk all about this. So Jonathan, thank you so much for coming on Odd Lots.

Thanks a lot for having me. Yeah, I should just say right at the start I should give a disclaimer. I’m an economist at the Federal Reserve Bank of Minneapolis and anything I say is going to be my views, not those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System.

Thank you for getting the disclaimer out of the way. We are very used to hearing that from Fed researchers and economists. So the title of the paper, I think Joe already said it, a macroeconomic perspective on stock market valuation ratios. Why did you decide to look at this particular topic at this particular moment in time, too?

Yeah, so I actually we started out before we worked on this, we were working on a paper on the US net foreign asset position and we noticed that you know, the value of US assets minus our liabilities, that had been declining really fast over the last 10 years. And historically people had mostly thought about that in terms of the US running big current account deficits, running up a bigger and bigger debt with the rest of the world. And we realized that the kind of international gross asset positions had gotten really big and a lot of the decline in the net foreign asset position was driven by the fact that foreigners had invested a lot in US equity markets and a lot of foreign direct investment into the US. And when the US markets were booming much more so than the rest of the world, that was driving up the value of these foreign investments in the US and that was driving down the US net foreign asset position. And so after that we kind of became more interested in trying to understand what’s driving valuations more generally. I mean our background’s not really we’re not really in finance, we’re sort of more macro economists, but we’ve been working on this for a few years now and that’s where this paper started.

This seems like a bit just from a sort of theoretical big picture perspective this link between sort of macroeconomics and stock markets. And it does feel like often these are worlds that talk past each other and the macro people aren’t talking about stock market valuations that much and stock market people they think they don’t even have to care about macroeconomics in many cases. But this strikes me as interesting. How like novel is this or talk to us about this attempt to bridge the gap between the two worlds here?

Yeah. I think there’s a lot of strong connections and we’re talking about the same things in a slightly different frame. So one thing macroeconomists have been talking about for a long time for example is the fact that it looks like labor share of output has been drifting down over time. So a larger share of the pie seems to be going to owners of firms and a smaller share as wages to workers. And obviously that ties directly into thinking about valuations. If the firms making bigger profits, that’s going to drive up valuation. So I think there’s a lot of connections. I think for a long time historically there was a sense that it was kind of really hard to understand valuations. They were driven by wild variations in risk premia that had not much to do with kind of standard slow-moving macro stuff. And so, you know, there were two separate camps, one studying the finance, one studying the macro and it was hard to connect them. But I think, you know, I think people are working on that and I think there’s a lot of connections.

Okay, well, let’s dive into the paper’s conclusion then because I think everyone when we talk about high valuations, the temptation is always to be like, “No, the people who are satisfied with these high valuations, like they’re the crazy ones, right? Like I’m the one that sees the truth.” But your paper actually sets out like a pretty reasonable explanation for why these high valuations have persisted and have not mean reverted as Joe mentioned. Talk to us about both I guess the labor component in your paper as well as the investment component.

Yeah, sure. So you know, I think Joe was mentioning a minute ago with the price-earnings ratio, that’s the sort of a classic valuation metric people have looked at for a long time. And the idea always was that, well, if prices get too far ahead of profits, then maybe that gap’s going to narrow again going forward. So either you’re going to have to have really fast growth in earnings or the prices are going to come down. So you’re going to get low returns. And people have looked at that ratio. Shiller has a like the famous version of it. And the problem is that it’s been drifting up and up the price-earnings ratio and it’s been kind of way above its historical average for a long time and that gap just seems to keep getting bigger. So we were we were kind of went back to that. We looked at it in macro data instead of financial data, but it looks much the same if you look at standard financial accounts. And we went back to 1952. Yeah, you see this big run up in the price-earnings ratio.

But you know, there are other metrics you can look at. Another thing you can look at is you can look at prices relative to free cash flow. And it’s sort of a similar ratio. It’s just that you’ve got free cash flow in the denominator. And the only difference between earnings and free cash flow is in measuring earnings you subtract a measure of depreciation. In measuring free cash flow instead of subtracting depreciation, you take out all capital expenditure. And then the nice thing about free cash flow is it’s sort of a measure of everything that’s left at the end of the day to be paid to the owners of the firm. So you take the sales of firms, you subtract the input costs, payments to labor, subtract their taxes, subtract their capital expenditure. Everything that’s left is money that the firm can pay out to its owners.

So if you look at that ratio, the value of all the firms in the US relative to the total cash flow they’re generating it bounces around a bunch over time. But it doesn’t have like a long-term drift. It’s not like it’s kind of systematically moving up over time. So if you look at that ratio, you’d say, “Ah, maybe the market’s not so overvalued today. Maybe prices are roughly where they you know, roughly within historical range compared to this ratio.”

This strikes me as very important and so we should just pause on this point or stick with this point for a second. So we’ve all seen the Shiller CAPE and various other versions. What you’re saying is if you just And I’ve always thought, just let’s just measure free cash flow. That’s all I care about if I’m an investor, just how much money comes back to me at the end of the day. But you’re saying that when you look at the entire market through this lens, it just does not have the same extreme drift outside of normal ranges that you see when you look at price-earnings ratios.

Yeah, that’s right. I mean, it bounces around over time, but if you look at where it was, say in 1980, so that was a low for stock values. If you look at it in 1980, and you look at it in the second quarter of 2022, that ratio of value to free cash flow is the same. And both cases are about the historical average. Now, if you look over the last 3 years, you know, that ratio has kept moving up. So now we are above the historical average, but we’re not wildly outside the range that it’s fluctuated in over the last 60-70 years.

And just going back to the labor and investment component, if we think about it very simplistically, I think you used the pie analogy earlier. Like if you think about that cash as a giant pie, less of it is going to labor, less of it has been going on investment, and more of it is being spent or returned to capital, i.e., the shareholders.

Yeah, that’s right. So, if you look at the price-earnings ratio, it’s not like earnings haven’t grown. They’ve grown pretty fast, and they’ve grown pretty fast because the share of the output that’s going to workers has been going down, and the share that’s going to owners of firms has been going up. So, earnings have grown, but cash flow has grown even faster, and cash flow has grown even faster because firms have been able to generate these extra earnings without doing a lot of extra investment. I think what investors care about at the end of the day, what they maybe ought to care about is, you know, how much income is actually they’re going to be receiving. And if firms are going to do a lot of investment to keep sustaining those earnings, that’s income that can’t go to the owners of the firm. But that investment seems to been relatively weak over time, and as a share of firm value has been declining. So, cash flow has grown fast.

Talk to us about this measure of labor share. Obviously, on an individual basis, for an individual company basis, you can just like, you know, find out how much is going to labor versus other things. At the aggregate level, which is where you’re working at the macro level, this line, and I’ve seen it for years, people talk about labor share, and it’s generally going down. How robust is that measure? How that single number, cuz it looks pretty bad for workers when you look at the long-term labor share trend. How like methodologically or sort of intellectually robust is this data?

Yeah, I think it’s something that macroeconomists have been looking at for a long time. I think it’s pretty robust. If you look at the corporate sector, you could just measure it in the national accounts. You can look at wages and salaries of employees, and you can compare that against the output of the corporate sector, and those wages and salaries have fallen by about eight percentage points since 1980, I think, from 1980 to 2022. So, that’s eight percentage points of GDP. That’s a big change. You know, if you look at the non-corporate sector, you’re looking at small businesses, that’s harder to measure because kind of hard to say for a small private business how much of their output is really payments to labor versus payments to capital, but for big corporations, it’s sort of straightforward. There is an extra wrinkle to that, which is that you know, some firms have been paying more. They’ve been compensating some of their workers with stock options and things like that. And so, that kind of complicates it a little bit because, you know, do you want to call that a payment to labor or do you want to call that part of income to capital? So, but putting that aside, I think there has been a big shift with less income going to labor, more income going either to capital or just as pure rents to the owners of firms.

Wait, now I’m really curious. In your own research, how did you classify stock-based compensation? Was that an increase in labor or was that an increase in to capital?

Yeah, we just follow the we just follow basically the national accounts. So, the Bureau of Economic Analysis and the flow of funds, they put together this data set called the Integrated Macroeconomic Accounts. And it’s really just a version of the standard national income and product accounts, and they classify labor income the standard way, which is wages and salaries. And I think they include in that standard national income measure, when stock options are exercised, that counts as part of wage income. But, you know, when they’re granted, that’s the you know, so there’s some details there, but you know, they’re supposed to be at least partially captured there in that wage income measure.

Okay, and on the investment side, what about intangibles? Cuz this is the thing that constantly comes up when we’re talking about both valuations and the broader macroeconomy. So much of what companies do nowadays, especially in big tech, has to do with intangibles. So, you know, ephemeral brand value and things like that, would that have been captured in that investment number?

Yeah, so they’ve changed a little bit over time the way they try and measure investment, and they’re trying to capture more of investment in intellectual property, investment in software, and stuff that wasn’t historically captured. There’s still a question about how well they’re capturing that, and how much of it is measured. But, in terms of measuring free cash flow, one reason we like the free cash flow measure is that in terms of the income that’s available to go to the owners of the firm, it doesn’t really matter whether that spending on intangibles if that could be counted as a purchase of an intermediate input, that subtracts from value added, or could be counted as a capital investment, then it’s going to subtract from investment. So, the free cash flow measure is going to be the same either way. So, I think that’s a nice thing about free cash flow. It is just a measure of the income that’s left over after the firm’s paid all its bills, and it doesn’t really matter whether you count those bills as an input cost or a capital expenditure.

So, when you embarked on this paper, how much was it motivated or driven by this current 2026, or probably 2025 when you started it, reality that there is a very big change in corporate behavior afoot. We don’t know how long it’s going to last, but this is the big story of arguably the last two to three years is how much these very profitable companies have seriously shifted into investment mode.

Yeah, I would say we weren’t that we were maybe a little behind on that. We worked on this for a while. So, I think you know, that’s not something that was particularly on our radar. We’ve kind of twigged onto that a little bit more recently. Now, it’s true that AI-centered investment by the big tech firms, that’s been booming. Other kinds of investment have been kind of weak. Residential investment, for example, has been weak. So, investment overall, yeah, it looks kind of relatively strong for the whole US economy, but it’s not, you know, outsized in aggregate.

So, yeah, I think it’s definitely a question. I think, as you said right at the start, this story that firms have been able to generate a bunch of earnings, some of these firms that have generated a bunch of earnings, especially in tech, they’ve done it without a lot of capital expenditure, and that’s meant that their cash flow has grown really strongly. And now they are starting to spend. So, it is a question going forward, is that spending going to pay off? So, at the moment, I guess there’s a bunch of companies whose cash flow temporarily is negative right now. Historically, maybe free cash flow. And so, that’s the question investors are thinking about.

How do you think about aggregates versus, I guess, sectors or, you know, a handful of big tech companies in this data? Because, again, you are looking at the aggregate numbers, like the macro variables, but if we think about the market right now and who’s actually spending money, it’s like a handful of tech firms, right?

Yeah, that’s right. We have been mostly looking at the aggregates. We’ve started looking a little bit at the firm level data in Chris and Compustat. And you know, what you see what we’ve seen so far looking at the firm level data is that, yeah, it’s a relatively small number of firms that account for most of the growth in value, most of the growth in the total stock market value, maybe say 50 firms. But those 50 firms are the same firms that have had the fastest growth in cash flow. So, cash flow and value have grown roughly in lockstep for, say, 50 of the biggest firms in the US. And so, these I mean, I guess a bunch of these are big tech firms, and it’s these big tech firms have been generating mountains of cash, and their high values, they’re not built on sand, they’re not built on an expectation that we’re going to make big future profits. The profits are there now. And I guess the question is, you know, are those profits going to persist going forward?

Let’s get back to the labor share component. I mean, one of the things that comes up is this question of like, is the booming stock market based on the perpetuation of inequality, right? To some extent, like this idea you know, back in the 2010s, everyone all these corporate leaders and people would go to Davos, and they’d say, “Oh, we really care about inequality, right?” You know, it sounds nice, etc. But also, everyone wants the stock market to go up. Seems if we tease this out a little bit, that there is some tension, right? Is there it seems like there’s some tension with if you actually had some sort of meaningful shift in terms of the ratio of profits that go from capital to labor, if part of the story in your line go up is the declining labor share, then it does seem like there’s pretty obviously some fundamental tension here.

Yeah, so I think that, you know, if the people who are owning the firms were the same people who are earning the wage income, then, you know, it would just be a reshuffling of income. You know, you’d be getting less income in one pocket, more income in your other pocket, and that would be kind of a wash for inequality, but I guess the concern is that the people who own a large part of the stock market are one group of people, and then the workers, you know, many workers don’t have a lot of that stock market wealth, and so they don’t benefit from these higher stock prices. So, that is a concern, and I guess it’s a concern going forward to people thinking about AI, how that’s going to change labor markets going forward, and how that’s going to change the pie, whether that’s going to reduce the share of the pie that’s going to workers still further, and increase still further the share that’s going to owners of firms.

Actually, this reminds me of a related question, but, you know, you’re at the Minneapolis Fed, and I assume when you publish a research paper like this, you want your bosses to look at it. I guess that’s Neil Kashkari right now. And you want there to be some sort of policy implication. What exactly should policy makers take away from something like this paper? Because, you know, at the Fed, I’m sure they care about wealth inequality, but they don’t have a wealth inequality mandate. They do have a financial stability mandate, so you know, you could even make the argument that they wouldn’t want to unsettle you know, current equity market valuations, which would argue potentially for not increasing labor share of that cash flow. But, anyway, when you publish a paper like this, what are policy makers supposed to take away, or what do you hope that they actually take away?

I think that at the Fed, we do follow equity markets, and we follow them because we sort of want to get a sense of those headwinds and tailwinds for the economy, and all else equal, if the stock market is stronger, that’s a little bit of a bigger tailwind, and higher stock prices, you’d expect a little bit more consumer spending, a little bit more business investment. So, the Fed, for sure, we’re kind of interested in understanding stock markets. I think, you know, forecasting stock prices is hard, and we’re not trading, and it’s hard to make money on that. But, yeah, for sure, we’re monitoring that. And in terms of financial stability, then yes, there’s a concern always like, you know, there’s always a risk that you worry one thing you worry about is, well, maybe what would happen. It’s always kind of a scenario in the background, what would happen if stock prices fell. Not that it’s in real time ever going to be easy to predict that, but just hypothetically, you know, you want to think through what might happen if stock prices fell substantially, and stock prices now are really high. So, you know, a 10% fall in prices when prices are really high is going to be a larger fall in household wealth than a 10% fall when prices are low. So, I think all else equal, you know, the fact that these valuations are so high, you know, makes you think a little bit more about those downside risks.

So, going back to the question of these cycles of capital expenditure, and you mentioned, you know, we’re in one now. We’ll see how long it lasts, and so forth. In your research, what other prior waves should we look at? You know, you mentioned the trend since 1980, but are there prior waves where you could see, okay, the stock market valuations on a free cash flow basis compressed, or stocks just fell, and there was some at the same time some sort of some massive decrease in free cash flow that we can point to that, okay, this helps explain a decline or a bear market or something like that.

Yeah, I think, you know, one thing that was interesting, I looked back, there was a paper it’s an old paper now, but I think it was published around 2000 by Hobijn and Jovanovic, and they were interested in why stock prices were really low around 1980. And their story was, well, in the late ’70s, early ’80s, people could see that there was an IT revolution coming, that the microchips were out there, they could anticipate they were going to be widely adopted, and this was going to be a big wave of investment, and it was going to create a bunch of new winners. Yeah, it was going to create a bunch of new winners and losers in the economy. And the idea of the paper was, well, you know, some of these old firms are going to get wiped out because they’re not going to be able to implement this new IT. They don’t have the technology, they don’t know how to do it. And there’s going to be some new firms that are going to come in, and they did come in. You know, the Intels and the Microsofts came in. But, at the time, you know, those were not mostly publicly traded companies, and nobody quite knew at the time, you know, which were going to be the winners, which were going to be the losers. But, they had a sense that this was going to be a radical transformation. So, that was the story for that paper, for why prices were low in the early 1980s. So, I thought that was kind of that feels a little bit like you know, it’s not exactly the same as AI, but it’s sort of like it was a big change, people could see it coming, but they just didn’t know at the time exactly how it was going to play out.

Yeah, definitely a historical echo there. Conversely to Joe’s question, I mean, a lot of the paper is explaining why if you look at valuations, they’re high, but, you know, macro sense, they might be quite rational. Were there any moments throughout history, I guess since I think you said 1952, was it, the beginning of your data? Were there any moments since 1952 where actually valuations did just look really irrational, and it was just, you know, investors getting ahead of themselves, and animal spirits going wild?

Yeah, well, I think, you know, a natural one for that would be the dot-com boom in 2000. That was a time when cash flow was weak, and yet valuations were sky-high. And, you know, with hindsight, investors did get ahead of themselves then, and took a hit. You know, some of those technologies they were excited about, they actually, you know, with 10 years later, they really did pay off, and the market bounced back higher than it had been, but you know, at the time, I think that was a little bit of irrational exuberance.

It does seem but, it’s hard to call it. Yeah. I mean, like I obviously I’m not going to put you on the spot, and say, all right, give us your stock market forecast for the next 5 years. We’re not we don’t want to do that, either. All that being said, it certainly seems like an implication of this research is that when you have a major switch that gets flipped from we were just producing mountains of cash, much of it returning to shareholders, a lot of it in the form of buybacks. When you have this switch that gets flipped, where it’s just tons of free cash flow, and suddenly, not only is that cash flow all being redeployed into investment, but furthermore, some of these companies are going into debt, so negative cash flow, perhaps. It seems like a safe implication for investors today is at least we should take this very seriously. That there is a flip that’s underway, and if one explanation for high stock market valuations is this free cash flow, we have to take pretty seriously the fact that for many of these big companies, it’s either gone to zero or flipped negative.

Yeah, so we looked at we only, you know, we looked at we were looking at quarterly data. This macro data is only quarterly, so we’re a little bit, you know, not totally up to date. The last quarter we had was the third quarter of 2025. If you look at the total corporate sector then, you know, cash flow is you don’t see a decline in cash flow up until that third quarter. So, maybe that’s changed the last once we get the next quarter or two of data, we’ll see something different, but you know, overall, I think in aggregate, the economy is still generating a bunch of free cash flow. So, it’s true that, you know, for some of these big tech firms at the top, those numbers might be different. I think, you know, the view the optimistic view is, well, this is 1 or 2 years of investment that’s going to generate a ton of free cash flow going forward, and I think historically, that’s why when you’re looking at individual companies, maybe it makes sense to look at prices compared to earnings instead of prices compared to cash flow, because this investment, if you have a period where you’re doing a ton of investment, you know, this cash flow measure looks weak for a quarter or two, and then it’s going to bounce back. And maybe earnings is a way to smooth through that, but you know, so for sure but, for sure though, the outlook going forward is going to depend on whether these investments pay off.

I think you can make a case that this AI is going to reduce labor share of income further. Right. You know, so that would be a plus for stock values. On the other hand, I think this idea that, you know, AI is kind of there for free, that you can just adopt it and get these bigger profits without any investments, I think that’s not going to be quite right. I think I mean, you see the big tech firms, they’re definitely doing plenty of capital expenditure. And I think even average firms that are just planning to adopt AI and increase productivity, it’s not like they can just tell their workers, you know, please try and use ChatGPT, and be a little bit more productive. They’re going to have to do big investments, too, to actually adopt.

So, I think I don’t have my own view. I wouldn’t want to make a forecast, but I think you can tell a glass half full, glass half empty story on that. One thing I feel confident, Tracy, is that, you know, investors go back and they say, well, look at all this free cash flow companies are generating, these valuation measures are totally robust. And then we get to 2025, and they say, well, look at these price to earnings ratios. Don’t ignore the free cash flow loss, and just switch back and PE ratio. I think it’ll be very comfortable for strategists to sort of pick that number. Whatever makes it look tolerable at that moment.

But, actually, Jonathan, so we really don’t want to put you on the spot and make you forecast the future. But, it does seem like the current moment in time, the AI boom could be a very natural, you know, real-life experiment for some of the factors you point out in your paper. So, on the one hand, you have a potential investment boom. On the other hand, as you just touched on, maybe firms, you know, save even more on labor costs. Can you just walk us through, like, broad brush strokes, a hypothetical scenario where companies spend a bunch on AI, and reduce their labor costs, what would that look like in your framework of thinking about valuations?

Yeah, so I think that what companies like would like is just, you know, sort of like a magic tree that just drops fruit and you just keep generating cash flow without doing any investment. And, you know, some of the big tech companies, they did important investments early on and maybe we didn’t measure those well at the time, but they’ve been just machines generating cash without a lot of capital expenditure. So, I think that is the optimistic view on asset valuations. And yeah, in terms of labor share, I think looking back at over time, it was more a story of people were thinking that it was going to be the technology was going to automate kind of low-skilled jobs and we were going to have robots building cars instead of workers. And that’s where the labor savings were going to come from. And now I think, you know, that’s flipped a little bit and now, you know, the high-skilled workers are starting to get a little bit nervous that maybe it’s going to be some of the knowledge workers that are going to get replaced. And it’s going to be the people doing kind of manual work who are going to be indispensable. But still the direction would be the same that you can just do the same amount of work and you can replace workers with either machines or with AI.

And in terms of I guess inequality, we were going back to that a second ago. I think that’s sort of an interesting thing to think about cuz it the old one seemed like, oh, this technology is bad for inequality because it’s competition for low-wage workers and it’s going to drive down wages of low-wage workers and that’s going to be a mechanism generating more inequality. Now, you know, you could tell an optimistic story on inequality. Well, now it’s kind of the high-wage workers whose jobs are at risk. And we’re going to need plenty of I like the old story. I like those guys are going to do, you know, those guys are going to the nurses and the construction workers are going to do fine and it’s going to be the knowledge workers who are going to take a hit. So, maybe that’s going to compress inequality a little bit, but yeah. I like the version of compressing inequality where people who got paid less would make more than the one where the knowledge workers. Yeah. It’s shrink there. It’s people being pulled up versus everyone being pulled down story.

I guess if we prioritize reducing inequality, we have to take it any way we can get it.

Jonathan, thank you so much for coming on Odd Lots. I think this is really important research and love to stay in touch particularly as you continue to follow on and do more tests of your theory. Thanks a lot for having me.

You know what, Tracy? I thought it was actually it made me take the research even more seriously when he said that they didn’t really stumble into this because it was timely in the news right now. Yeah. And so the fact that they’ve sort of arrived at this realization that a lot of this can be explained by free cash flows and investment at the exact moment when this is all happening. Like I said, would I ever want to forecast the stock market? Absolutely not. But I think investors have to take this pretty seriously as a potential turning point here. I agree. Also, I’m just I am very much in favor of keeping it simple when it comes to valuation and like free cash flow seems like it’s not necessarily forward-looking, but like it seems like a pretty decent thing to be looking at. And if you are just looking at cash flow, then the idea that suddenly a lot of that is going to be spent on a data center buildout or something like that, like that would seem to change the equation. But I think the complicating factor as we discussed is you also have this push factor on the labor side where, you know, again, if a bunch of the free cash flow is getting freed up because labor’s share is going down and suddenly you have AI coming in and companies are saving enormously on, you know, their headcounts or whatever, then that could maybe help keep valuations high, but, you know, it does seem like a good thing to be looking at. It’s interesting. I forget which conversation it was, one of our million AI-related conversations, but we were talking about like what are the AI winners going to be and they’re winners in the sense that they’ve massively become more productive. And maybe it’ll be European chemical companies or drug discovery companies, etc. and so forth who are not building models, but just strictly taking advantage of these potential productivity gains. And maybe if you look at the stock market this year, you could sort of tell that story in the specific sense that the US is underperforming. The US where all these models are built and they’re spending like crazy and the US markets have been sort of mediocre for a while and everywhere around the world is doing much better. Maybe we’re starting to see some of these distributional shifts underway just in terms of who reaps the reward from all this activity. I mean, I think it’s a really good thing to think about. I would also argue that there may be some other factors keeping the US equity risk premium fairly high at the moment. Definitely there are definitely other factors. All right, shall we leave it there?

Let’s leave it there. This has been another episode of the Odd Lots podcast. I’m Tracy Alloway. You can follow me at TracyAlloway. And I’m Joe Weisenthal. You can follow me at The Stalwart. Follow our guest, Jonathan Heathcote, at JohnHeathcote. Follow our producers, Carmen Rodriguez, at CarmenArman, Dashiel Bennett at DashBot, and Caleb Brooks at CalebBrooks. And for more Odd Lots content, go to bloomberg.com/oddlots for a daily newsletter and all of our episodes. And you can chat about all of these topics 24/7 in our Discord, discord.gg/oddlots. And if you enjoy Odd Lots, if you like it when we talk about macro variables and the stock valuation process, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad-free. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there. Thanks for listening.