Two hundred twenty nine. That was the number of private companies valued at a billion dollars or more—so-called “unicorns”—worldwide in January 2016, according to a report released by VentureBeat. The Wall Street Journal offered a more conservative estimate, but even there the overall trend was clear. In just two years, the number of unicorns worldwide had more than tripled, from 45 to 149.
To prophets of doom and gloom, there was only one explanation for the unicorn explosion: Silicon Valley was in a bubble, and it was about to burst. In April, Benchmark’s Bill Gurley published a blog post claiming the unicorn financing market had become “dangerous … for all involved.” In May, the Wall Street Journal’s Christopher Mims suggested the end might have already begun. In June, San Francisco announced it was working on an “economic resiliency plan” to help the city survive the inevitable downturn. The whole tech world held its breath.
And nothing happened. Sure, there were down rounds. Some old unicorns, like content company Mode Media, shut down entirely. The unicorn explosion slowed its pace, with only a few new companies earning that status. But it’s now 2017, and we’ve seen nothing like the collapse in startup valuations and consequent economic catastrophe that everyone’s been predicting.
Here’s the thing: The collapse isn’t going to happen this year, either. Or next year. Or the next, or the next, or the next. That’s because, despite sky-high startup valuations, we actually aren’t in a bubble. Most of those valuations reflect actual value creation — a level of which we haven’t seen since the second Industrial Revolution. And as innovation accelerates, they’re only going to get bigger.
To see why, we’ll need to take a trip into the economic past.
Information technology as a “general purpose technology”: the third industrial revolution
At the tail end of the 20th century, there was much puzzlement in economics circles over why the information technology (IT) revolution wasn’t doing much to accelerate productivity growth. In 1987, labor economist Robert Solow quipped that “you can see the computer age everywhere except in the productivity statistics.” The so-called “Solow paradox” was not what it seemed, however. Looking back to the first and second industrial revolutions, economic historians like Stanford’s Paul David were able to show that a slowdown in productivity growth after a major technological innovation was not a paradox but a sure sign that a revolution was occurring.
Technological innovations that trigger changes on the scale of the first or second industrial revolutions are known in economic parlance as general purpose technologies (GPTs). General purpose technologies (GPTs) are special because via a single breakthrough they open the door to potential innovations across many, if not all, sectors of the economy. Steam was a GPT in the first industrial revolution and electricity was one in the second. And, as historians like David have argued, IT is the GPT in a third industrial revolution that is still occurring.
The U.S. saw a slowdown in productivity growth occurred between 1890 and 1913, when electricity was just being introduced. This may have been due to the slow pace of factory electrification, as David has argued, or some other cause. But the end result is clear: After taking more than 20 years to reach full penetration, electrification suddenly set off an enormous acceleration of productivity growth for the next 15. If that acceleration hadn’t been cut short by the Great Depression, who knows how long it could have gone on.
Evidence shows a similar pattern with the adoption of IT. Writing in 2005, Jovanovic and Rousseau dated the period of IT adoption as beginning in 1971, when Intel invented the microprocessor that would become the core of the first PCs. Almost immediately, productivity growth slowed as offices began taking baby steps into the PC revolution, only picking…