As a rule, migration patterns are durable because people are risk averse. Most migrants follow the beaten path. You go where you know. Over a longer period of time, migration seems to be more dynamic. Pioneers find success in unexpected places. The legend builds. Word spreads. One place booms while another dies. Everyone who is anyone dreams of California. A generation later, the hot destination is Texas. What drives such shifts?
Within the United States, workers move to improve in an exceptional display of geographic mobility. I’ve associated major changes in these geographic mobility patterns with major economic change. Eras of agriculture, manufacturing, innovation or knowledge, and talent or legacy (my own terms) would each inform signature migrations. I was happy with this model, trying to improve it with new information and making predictions. Upon reading the Second Machine Age, I’ve scrapped the economic baseline of four eras in favor of two: the first machine age (manufacturing, or analog) and the second (digital). However, each machine age has two parts: diverging and converging. During the first part of the machine age, a few places prosper. During the second part, everyplace gets in on the act. Vancouver, British Columbia, trying to horn in on Silicon Valley’s act:
The digitization of the workplace, growth of Internet and mobile communications and e-commerce and the increasing ease of starting a tech company due to the abundance of low-cost cloud-based software have prompted many Vancouverites, along with entrepreneurs elsewhere, to start companies. A lack of good jobs since the recession is also a factor. The tech industry in B.C., driven by Vancouver’s startups, is generating about 250 new companies each year, and growing at an annual clip of over 6 per cent, according to the Vancouver Economic Commission.
“There’s almost a dividing line: Before the cloud, and after the cloud,” Mr. Holmes says. “We’re seeing an absolute decentralization of startups around the world.”
“Absolute decentralization” looks like economic convergence and the rise of new destinations for digital workers. The “dividing line” delineates between the divergence and convergence of the second machine age. Before the cloud, the techies migrated to a few hubs such as the Bay Area or Boston. Economist Enrico Moretti maps this migration in his book, the New Geography of Jobs. For a look at the dominant pattern of digital convergence, read “Demographic Changes In and Near U.S. Downtowns.” In or near the urban core for all U.S. cities, “residents … have become higher income, better educated, and more likely to be white, on average.” The diffusion of this trend has accelerated “after the cloud.”
When was this watershed of a world before the cloud and after the cloud? The year 2006 could be considered the birth year of Amazon Web Services. Perhaps a coincidence, the authors of the Second Machine Age also offer up 2006 as when the exponential growth of the digital economy reached the second half of the chessboard:
Ray Kurzweil, an inventor and entrepreneur, compared this process to what happens if you put a single grain of rice on the first square of a chessboard, put two grains on the next square, and keep doubling the amount with each square. By the time you get to the 64th square you have a pile of rice that’s bigger than Mt. Everest. And yet, if you look at just the first 32 squares, the amounts of rice are quite manageable, amounting to only a few truckloads by square 32. Our society is now starting to enter the second half of the chessboard. The scope of digital technologies is expanding because of the combinatorial nature of innovation. In a combinatorial economy, each idea, rather than using up the stock of ideas, creates building blocks for other ideas. And the new combinations of ideas can be even more valuable than the original ones.
The geography of the second half of the chessboard is one of convergence, economically and demographically. New combinations of ideas appear lower in the tech urban hierarchy. Following Boston comes Pittsburgh, with Cleveland lagging behind. The economies and demographics of Pittsburgh and Cleveland are converging with Boston’s. Amazon’s cloud services, among other things, help make this convergence possible. Companies can locate anywhere and access computational power when they want it without building their own data center. Similarly, untethered from the proximity to natural resources, manufacturing converged during the first machine age. The flow of the bulk of workers shifted from rural-to-urban to sprawl. Suburbanization was ubiquitous.
The decentralization of manufacturing had a profound effect on the labor market. The wealth spread and then diminished. As a percentage of the overall workforce, manufacturing (like agriculture before) is in precipitous decline. Without a divergent geographic advantage, companies couldn’t afford the wages and benefits. Same story for the digital economy:
The Bureau of Labor Statistics predicts that by 2022 some 1 million more Americans will enter the workforce as educators. Another 1.1 million newcomers will earn a living in sales. Such opportunities won’t be confined to remedial teaching or department store cashiers. Each wave of tech will create fresh demand for high-paid trainers, coaches, workshop leaders and salespeople. By contrast, software engineers’ ranks will grow by 279,500, or barely 3% of overall job growth. Narrowly defined tech jobs, by themselves, aren’t going to be the answer for long-term employment growth, says Michael Chui, a partner at McKinsey Global Institute.
Narrowly defined tech jobs are going the way of narrowly defined manufacturing jobs. Less people will be needed for ever greater production. Meanwhile, those in education and sales (see white-collar manufacturing employment) will be the agents of diffusing prosperity. In that regard, the next 40 years look great.
The main difference between the first and second machine age doesn’t look great. It looks dire. Even narrowly defined, much greater numbers of workers were needed for divergent manufacturing than for divergent digital. The wage premium in divergent geographies benefited a relative few (see growing inequality), at least directly, in the digital economy. Those who can’t transition into tech “white-collar” work will be left out of the economic boom.
Cleveland and Pittsburgh will need to do a better job of spreading the wealth than Boston did. That’s the challenge, avoiding the pitfalls that trapped many during the convergence of the first machine age. Welcome to the second half of the chessboard.
Jim Russell, a geographer studying the relationship between migration and economic development, writes regularly for Pacific Standard.
