Odd Lots

The Big Macro Force That's Been Driving Stocks Higher for Years

36 min
Apr 11, 20268 days ago
Listen to Episode
Summary

Hosts Joe Weisenthal and Tracy Allaway discuss why stock market valuations remain elevated despite traditional metrics suggesting overvaluation, featuring economist Jonathan Heathcote from the Minneapolis Federal Reserve who presents research showing that free cash flow—rather than price-to-earnings ratios—better explains current valuations. The conversation explores how declining labor share, reduced capital investment, and the shift toward AI-driven spending may reshape future market dynamics.

Insights
  • Free cash flow metrics show stock valuations are within historical ranges, contradicting the narrative of extreme overvaluation suggested by price-to-earnings ratios
  • The decline in labor share of corporate output (down 8% since 1980) has been a primary driver of earnings growth and elevated valuations, benefiting capital owners over workers
  • Major tech firms are transitioning from cash-generation machines to heavy capital spenders on AI infrastructure, which could fundamentally alter the free cash flow picture that has justified current valuations
  • Historical precedent (1980s IT revolution) shows that periods of anticipated transformative technology can justify lower valuations due to uncertainty about winners and losers
  • AI adoption may further compress labor share, but could also create investment requirements across the economy that reduce free cash flow available to shareholders
Trends
Shift from intangible asset investment (SaaS) to physical capital expenditure (data centers, chips, infrastructure) in big techDeclining labor share of income as a structural feature of modern capitalism, accelerating wealth concentrationAI-driven productivity gains creating bifurcated labor market risks—knowledge workers now facing automation threats previously associated with manual laborPotential geographic divergence in AI benefits, with non-US companies adopting AI without building infrastructure gaining relative advantageMacro-finance convergence: macroeconomists increasingly studying equity valuations as traditional finance models prove insufficientCorporate debt accumulation among mega-cap tech firms to fund AI infrastructure, changing risk profile of equity investmentsPotential mean reversion in valuations if free cash flow growth decelerates due to sustained high capital expenditureInequality dynamics shifting as knowledge worker wages face pressure from AI, potentially compressing wage gaps
Companies
Microsoft
Referenced as a major tech winner from the 1980s IT revolution that benefited from early adoption
Intel
Referenced as a major tech winner from the 1980s IT revolution that benefited from early adoption
Exxon
Mentioned as example of pre-GFC era largest company requiring continuous capital expenditure
People
Jonathan Heathcote
Co-author of paper on macroeconomic perspective of stock market valuations; primary guest discussing free cash flow m...
Joe Weisenthal
Co-host of Odd Lots podcast conducting interview on stock valuations and macroeconomic drivers
Tracy Allaway
Co-host of Odd Lots podcast discussing valuation metrics and labor share implications
Neil Kashkari
Referenced as Jonathan Heathcote's supervisor at the Minneapolis Fed
Shiller
Referenced for Shiller CAPE ratio, a traditional valuation metric discussed in the episode
Hobain and Jovanovic
Authors of paper explaining low stock prices in 1980 due to anticipated IT revolution uncertainty
Quotes
"If you look at that ratio, the value of all the firms in the U.S. 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."
Jonathan Heathcote~18:00
"Earnings have grown, but cash flows have grown even faster and cash flows have grown even faster because firms have been able to generate these extra earnings without doing a lot of extra investment."
Jonathan Heathcote~25:00
"The profits are there now. And I guess the question is, you know, are those profits going to persist going forward?"
Jonathan Heathcote~48:00
"I think when you see the big tech firms, that's 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 chat GPT and be a little bit more productive."
Jonathan Heathcote~65:00
Full Transcript
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That's Bloomberg This Weekend. Saturdays and Sundays starting at 7 a.m. Eastern. Make us part of your weekend routine on Bloomberg Television, radio and wherever you get your podcasts. Bloomberg Audio Studios. Podcasts Radio News. Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal. And I'm Tracy Allaway. 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 and 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, 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, 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 long term. So they would have always been having to like spend because you can't just sort of like passively collect oil, et cetera. 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, 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 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, oh, 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 measure. I mean, I remember, you know, early on, what was the Shiller, the Shiller-cape ratio, and there's like, this has got a mean revert. And 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 in eventually. 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? 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, or co-authored a recent paper that really caught my eye back in January called a macroeconomic perspective on stock market valuation ratios. So good data. 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 OddLots. Thanks a lot for having me. Yeah, I should just say right at the start, I'm, 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 at 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 actually, we started out before we worked on this, we were working on a paper on the US net foreign asset position, and we'd 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 is not really, we're not really in finance, we're sort of more macroeconomists, but we've been working on this for a few years now, and that's where this paper started. This seems like 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 or output is being 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 firm's making bigger profits, that's going to drive up valuations. 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 premium that had not much to do with kind of standard slow moving macro stuff. And so there were two separate camps, one studying the finance, one studying the macro, and it was hard to connect them. But 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 been 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, the price earnings ratio, that's 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 little returns. And people have looked at that ratio, Sheila has 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 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. And 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 this sort of a measure of everything that's left at the end of the data 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 U.S. 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, maybe the market's not so overvalued today. Maybe prices are 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 Shuler K, but 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 turning 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 is about the historical average. Now, if you look over the last three years, that ratio has kept moving up. So now we are above the historical average, but we're not wildly outside the range that is fluctuated in over the last 67 years. I'm Francine Lacqua, an award-winning journalist, and I've got a new podcast, Leaders with Francine Lacqua from Bloomberg Podcasts. I've interviewed everyone from heads of state to fashion icons about the news of the moment. But I've always been curious, who are these people as leaders? I don't think there's one right way to be a leader. Make decisions. A poor decision is always better than no decision. Listen to new episodes every other Monday. Follow Leaders with Francine Lacqua wherever you get your podcasts. 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 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 work has been going down and the share that's going to owners of firms has been going up. So earnings have grown, but cash flows have grown even faster and cash flows have 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 may be ought to care about is 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 have been relatively weak over time. And as a share of firm value has been declining, so cash flows 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 that for years, people talk about labor share and it's generally going down, how robust is that measure? How that single number, because 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 a macro economist have been looking at for a long time. I think it's pretty robust. If you look at the corporate sector, you 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 8% since 1980, I think, from 1980 to 2022. So that's 8% 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, you know, one 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, you want to call that a payment to labor or you want to call that part of income to capital. So, but putting that aside, I think it is there is 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 Microeconomic 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, there's supposed to be at least partially captured there in that wage income measure. Okay. And on the investment side, what about intangibles? Because this is the thing that constantly comes up when we're talking about both valuations and the broader macroeconomy, like so much of what companies do nowadays, especially in big tech, has to do with intangibles. So, you know, if 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 international property and 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, 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 capital expenditure. So I think that's one advantage of looking at this free cash flow measure. So when you embarked on this paper, how much was it in the, when you're thinking, you talked about the intellectual origins of it with your prior research, but how much was it motivated or driven by this current 2026 or probably 2025 when you started at 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 kind of twigged on to that a little bit more recently. Now, it's true that that investment on 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 the 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, you know, is it going to pay off? So at the moment, I guess, yeah, I guess there's a bunch of companies whose cash flow temporarily is negative right now. Historic people make big free cash flow. And so that's the question investors are thinking about. This is Tom Keen inviting you to join us for the Bloomberg Surveillance Podcast. It's about making you smarter every business day. I'm Paul Sweeney. We bring you complete coverage of the US market open. We cover stocks, bonds, commodities, even crypto, all the information you need to excel. And I'm Alexis Christophress. Bloomberg Surveillance also brings you the analysis behind the headlines. We do that through conversations with the smartest names in economics, finance, investment, and international relations. We do all this live each and every weekday, then bring you the best analysis in our daily podcast. Search for Bloomberg Surveillance on Apple, Spotify, YouTube, or anywhere else you listen. On the East Coast, listen at lunch. And on the West Coast, listen as soon as you wake up. That's the Bloomberg Surveillance Podcast with Tom Keen, Paul Sweeney, and me, Alexis Christophress. Subscribe today wherever you get your podcasts. Bloomberg Surveillance, essential listening each and every business day. 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 at firm level data and Chris from 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 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, 50 of the biggest firms in the US. And so these, I mean, I guess a bunch of these are big tech firms. And these big tech firms have been generating mountains of cash and the 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 and all these corporate leaders and people would go to Davos and they 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 that 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 farms were the same people who are owning the wage income, then, you know, it would just be a reshuffling of income. 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, you know, 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 farms. Actually, this reminds me 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 policymakers 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 the, 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 policymakers 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 the 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 can 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 the decline or bear market or something like that. Yeah, I think, you know, one thing that was interesting, I look back, there was a paper, it's an old paper now, but I think it's published around 2000 by Hobain 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 are 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's 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're not, 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, the Intel's and the Microsoft's came in. But at the time, those were not mostly publicly traded companies, and nobody quite knew at the time 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 their 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 papers explaining why if you look at valuations, they're high, but in a macro sense, they, you know, 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, the dotcom boom in 2000. That, that was a time when cash flow was weak and your 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 a rational exuberance. It does seem, but it's hard to call it. Yeah. I mean, like, I obviously I'm not going to like put you on the spot and say, all right, give us your stock market forecast for the next five 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're 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 flip 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 flows, 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 or 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 one or two years of investment, there'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, it's 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 when you see the big tech firms, that's 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 chat GPT 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 Glass half full Glass have empty story on that. One thing I feel confident, Tracy, is that, you know, investors go back and 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. They don't ignore the free cash flow loss and just switch back and the ratio. It'll be very comfortable for strategists to sort of everyone. Cherry picks. Yeah, whatever makes it look tolerable at that moment. But actually, Jonathan, so I, 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 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 skill 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 school 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 with either machines or with AI. And in terms of, I guess, inequality, we're going back to that a second ago, I think, I think that's sort of an interesting thing to think about because 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 or 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 a high wage workers whose jobs are at risk. And we're going to need plenty of, I like the old story. Those guys are going to do, you know, those guys are going to the nurses and 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 shrink there. It's people being pulled up versus everyone being pulled down story. I guess, I guess, if we prioritize reducing inequality, we have to take it anyway, we can get it. Jonathan, thank you so much for coming on OddLots. 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 they were, because it was timely in the news right now. 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 like one like 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 free cash flow seems like it's not necessarily forward looking, but 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 build out 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 again, if a bunch of the free cash flow is getting freed up because labor share is going down and suddenly you have AI coming in and companies are saving enormously on their headcounts or whatever, then that could maybe help keep valuations high. But 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're talking about what are the AI winners going to be and their winners in the sense that they've massively become more productive. Maybe it'll be European chemical companies or drug discovery companies, et cetera, 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 we build all these models are built in the US and they're spending like crazy and 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 these sort of like some of these distributional shifts under way, 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... There are many other factors. There are other factors. The US equity risk premium fairly high at the moment. There are definitely the other factors. All right, shall we leave it there? Let's leave it there. This has been another episode of the OddLots podcast. I'm Tracy Allaway. You can follow me at Tracy Allaway. And I'm Joe Weisenthal. You can follow me at the Stoll Wirt. Follow our guest, Jonathan Heathcote, at John Heathcote. Follow our producers, Carmen Rodriguez, at Carmen Arman. 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