Have We Been Partying Like It’s 1999?

This bubble may end with a tech-bro bailout

The political insanity of the past few days has been exhausting, and it is by no means over. But with the North American trade war temporarily (?) on hold, maybe I can take a day to write about a more comforting topic: financial insanity. But politics will make an appearance too.

One of the earliest columns I wrote for the New York Times was titled “The Ponzi Paradigm.” It mainly summarized Robert Shiller’s book “Irrational Exuberance,” which argued that bubbles, in which asset prices lose touch with reality, are common, and deeply rooted in human psychology. Shiller would, by the way, eventually receive a Nobel Prize for his work, sharing it with Eugene Fama, father of the “efficient markets hypothesis,” which says that asset prices are highly rational. Don’t believe people who tell you that Swedes lack a sense of humor.

Both Shiller and I were, of course, thinking about the huge runup in stock prices, especially tech stocks, during the late 1990s. And in retrospect both of us had amazing timing (which in my case was sheer luck.) My column was published on March 12, 2000, almost perfectly coinciding with the tech-heavy Nasdaq’s peak:

And it’s impossible not to wonder how much the current situation, with soaring valuations for a handful of technology stocks, resembles where we were 25 years ago, with the frenzy over AI now playing a role similar to that of the frenzy over the internet back then. I believe that there are strong similarities, but also some important and disturbing differences.

Let’s talk first about tech bubble 1.0 in the light of history.

At the time, people were extremely excited about the possibilities created by the internet and IT in general, and they weren’t wrong. Consider this Qwest ad in which a man checks into a depressing motel and is told that the in-room entertainment includes every movie and TV show ever made (the commercials were much better back then):

Well, we’re pretty much there. I have indeed gotten though lonely evenings in dreary rooms (do you think I only stay in 5-star hotels?) with the vast array of stuff to watch on various streaming services.

You can clearly see the tech surge in economic data, too. Economists try to measure technological progress by looking at “total factor productivity” — that part of economic growth that can’t be explained by the combined effects of growth in the labor force, increasing education levels, and growth in the capital stock. Here’s the rate of TFP growth over the previous 10 years, tracked over time:

Source: Bureau of Labor Statistics

After a generation of rapid productivity growth after World War II, progress slowed to a crawl for two decades. Then it surged again: the peak in 2005 means that there was rapid progress from roughly 1995 to 2005.

True, the surge didn’t last. Back in 2000 the economist Robert Gordon argued that the IT revolution was far less significant than what he called the Second Industrial Revolution of the late 19^th century, built around electricity, internal combustion engines, chemicals and — last but not least — indoor plumbing. (The great postwar boom was arguably about taking full advantage of this revolution.) So far the data have supported his skepticism.

Still, the tech surge was real, and brought real benefits to the economy, adding perhaps 10 percent to real GDP. What it didn’t do was justify the high valuations temporarily placed on tech stocks. Early entrants like Pets.com, whose famous sock-puppet appears at the top of this post, weren’t able to turn their hype into sustained profitability, even when the underlying concept made sense. (I order Jack’s cat food from Chewy.com.)

So why did tech stocks rise so high before crashing? Shiller argued that asset bubbles can act like natural Ponzi schemes: those who get in early make money, not from underlying asset returns, but from rising prices driven by later entrants; as people see the big payoffs others are receiving, they pile in too, driving the asset price even higher. Skeptics start to look foolish; eventually some of them join the party, driven by FOMO — fear of missing out.

And then you run out of greater fools, the music stops, and investors are left with a terrible hangover.

It’s impossible to read about the internet-based frenzy of the late 1990s without drawing parallels with the AI-based frenzy we’re experiencing now. In fact, even the numbers look similar. In 1999 the price-earnings ratio for the S&P 500 hit 33, which looked, and was, crazy. As I work on this post, the PE ratio is about 30.

Now, like the internet — but unlike crypto, which still seems to have no use cases beyond money-laundering — AI clearly has significant real-world applications. Even if you’re one of those who describes it as “souped-up autocorrect,” well, that could describe many white-collar jobs. Also, you could equally well describe heavy earth-moving machinery as a souped-up version of a guy with a shovel. So?

AI, then, is a serious technology that will add significantly to economic growth. Estimates, however, are all over the place, from a one-time bump of a point or two in GDP to a singularity in which computers become truly intelligent, surpassing humans (and then Skynet kills us all.)

As far as I can tell, it’s a reasonable guess that AI’s economic impact will look like that of the IT/internet boom of 1995-2005: a significant bump in productivity but not an enduring transformation of the growth rate. But that’s only a guess.

But what about stock prices? To the extent that stock values in the 1990s reflected more than a natural Ponzi scheme, they reflected the belief that some of the tech players would eventually establish themselves as highly profitable quasi-monopolies along the lines of Microsoft, which to this day holds an entrenched position based on network externalities: everyone uses their products because everyone else uses their products.

What’s different this time is that AI fever is concentrated on a handful of companies — the Magnificent 7 — most of which are already entrenched quasi-monopolies. I don’t know whether people realize how anomalous this is. Historically, major new technologies have tended to disrupt the existing market hierarchy; this time, investors are in effect expecting radical new technology to reinforce that hierarchy.

And I guess I don’t understand why anyone expects AI to make highly profitable quasi-monopolies even more profitable. How much bigger can the market for Office or Google search get? I understand that these companies feel the need to invest in AI for defensive purposes, to fend off potential competitors. But this need should if anything make them less rather than more profitable. This will be especially true if, as the shock over DeepSeek suggests, big, established companies are investing in expensive, bloated models rather than thinking carefully about what they actually need.

In any case, the concentrated nature of AI frenzy goes along with another big difference from the 1990s: political power. In the 1990s Silicon Valley types tended to consider government irrelevant to their libertarian techno-utopian dreams. These days Big Tech invests heavily in political influence, and the biggest players have either made their peace with or become active promoters of authoritarianism.

The share price of Tesla, in particular, appears to be “completely divorced from fundamentals,” and makes sense, if at all, only in terms of Elon Musk’s apparent role as co-president.

All of which suggests that while AI fever bears a lot of resemblance to the dotcom bubble, the end game may be quite different. Look at Donald Trump’s two big tech-related proposals — a strategic cryptocurrency reserve and a $500 billion AI infrastructure investment. From the point of view of the national interest, the first makes no sense at all; the second might conceivably have merit, but sits oddly with the Trump administration’s attempts to unravel all the Biden administration’s efforts on behalf of strategic technology, let alone green energy.

But suppose that we think of these proposals not in terms of the national interest, but in terms of who would get the money. Who holds a lot of cryptocurrency that the government would buy up? Which companies do you think would receive the lion’s share of subsidies for AI?

There are some clear similarities between the 90s tech bubble and recent AI fever. But this bubble may end, not with a pop, but with a giant tech-bro bailout.

MUSICAL CODA

Not the obvious Prince tune, but an unexpected cover.