the Kauffman Foundation’s hometown, Kansas City. The area showing the biggest decrease was (perhaps surprisingly) Silicon Valley. But in absolute terms, Kansas City still has few tech startups compared to Silicon Valley, and the two cities are unlikely to trade places on the economic stage anytime soon.
Comparing places like Kansas City, Corvallis, OR, or Ames, IA, to San Jose “is kind of like apples and oranges,” Stangler says.
The other subtlety obscured by the startup density rankings is what Stangler calls “path dependence.” Put plainly, historical accidents count for a lot, and it’s hard to build something from nothing.
The seemingly permanent boomtown that is Silicon Valley, for example, was actually more than a century in the making, and might never have coalesced where it did if not for three unrelated facts: 1) Railroad magnate and politician Leland Stanford owned a country estate in Santa Clara County. It became the setting for Stanford University, which was transformed during and after World War II into one of the world’s most effective engines for university-industry collaboration. 2) In 1931, the U.S. Navy decided to build a major airfield adjacent to Mountain View and Sunnyvale, providing a nucleation point for dozens of aerospace and defense companies. 3) William Shockley, who co-invented the transistor at Bell Labs in New Jersey, decided to open Shockley Semiconductor Laboratory in Mountain View so that he could live closer to his aging mother in Palo Alto. Shockley’s firm was the progenitor of Fairchild Semiconductor, which in turn gave birth to Intel and most of the other companies that put the silicon in Silicon Valley.
Any region hoping to build an analogous high-tech ecosystem faces a chicken-and-egg problem, as Xconomy documented recently in an in-depth series on the startup scene in Santa Cruz, CA. In short: you can’t build fast-growing companies without a local talent pool, and it’s hard to attract talent without an existing base of high-tech employers.
“Most entrepreneurs, especially in the tech sector, have left an existing high-tech job,” Stangler says. “None of these places woke up and said ‘We suddenly have a technology sector.’ There was always some sort of internal dynamic they were able to capitalize on.”
Corvallis, for example, had Nike down the road in Beaverton, OR, and was a short drive from outposts of Intel and Hewlett-Packard. Boise, ID, had Micron. Santa Cruz had Borland Software.
When Stangler plumbed Hathaway’s data for common characteristics that might explain how regions achieve high startup densities, he didn’t come up with much. Some startup-rich areas have diverse and highly educated populations; others don’t. Some regions boast a lot of socioeconomic mobility; others don’t. Some are home to top research universities or federal facilities like national laboratories or military bases; others aren’t.
The only common thread seems to be what Stangler calls “entrepreneurial genealogy”—a tradition of established companies that train future entrepreneurs and spawn spinoffs.
But he also suspects that policy quirks play a role: Does the local university have a well-oiled technology transfer office? Do local laws allow large companies to enforce non-compete agreements, which are often used to deter former employees from starting companies in related sectors?
“There are so many things that are invisible but important,” Stangler says. “It’s like the ‘dark matter’ of the regional economy.”
