Cluster Effects and the Changing Geography of Productivity

Exceptional productivity-driven returns to intellectual and human capital are geographically concentrated.

These results are characterized by investment in - and the open exchange of - people and ideas which, as the following article explains, results in significantly higher performance.

Smart companies recognize this competitive advantage and are acting on it - such as GE's move to Boston - take advantage of the benefits. JL

Bourree Lam reports in The Atlantic:

The largest U.S. cities tend to be the most productive areas, along with areas that specialize in oil, gas, and mining. The low end of the productivity spectrum consisted of smaller cities in the southern and southwestern U.S. Beyond those two, only small cities that had major research universities saw productivity growth of greater than 1%. It’s the ultimate example of cluster effects, and as such has astronomical productivity readings and very high density of critical high-R&D, STEM-intensive advanced industries.

From 2007 to 2016, productivity in the U.S. grew at a historically low rate of about 1 percent per year. In other recent periods, it’s been much higher: 2.6 percent from 2000 to 2007 and 2.2 percent in the 1990s. The divergence has left economists looking for answers about slumping productivity and how to fix it.
A host of reasons have been suggested for why productivity has been declining: slowing innovation, inefficiency in sectors that have become huge, the inability to adequately measure innovations on the internet, and a lack of spending and investment, to name a few. To get a better understanding of how productivity varies across the county, Joseph Parilla and Mark Muro, both fellows at the Metropolitan Policy Program at the Brookings Institution, looked into productivity growth at the local level and how geographical variations in productivity relate to the declining national figures.
It’s natural that productivity varies across regions. Across the U.S., there are varying resources, industries, workers, technologies, government policies, and incentives that play into how businesses and workers develops. But Muro and Parilla believe that productivity is often overlooked when studying local economies. That, they say, is a mistake, since productivity is key for long-term wage growth and improving living standards. The difficulty in studying localities and comparing them with the national picture is largely because of the lack of comparable data. At the Labor Department, productivity is measured by comparing labor input (hours worked) to a sector’s output (in dollars). At the regional scale, Parilla and Muro use metro-level output from Moody’s Analytics and employment data from the Bureau of Labor Statistics to estimate local productivity. In doing so, they observe massive variations across the U.S. economy, from an average of $299,000 per worker a year in Midland, Texas to $38,000 per worker in Jacksonville, North Carolina.

According to their research, the largest U.S. cities tend to be the most productive areas, along with areas in the energy belt that specialize in oil, gas, and mining. The low end of the productivity spectrum consisted of smaller cities in the southern and southwestern U.S. These findings aren’t that surprising given that cities and boom towns tend to be more productive.
San Jose, California ranked as the nation’s most productive metropolitan area, with labor productivity growth at 2.7 percent between 1978 and 2015. “San Jose is extraordinary because of the depth and high performance. It’s the ultimate example of cluster effects, and as such has astronomical productivity readings and very high density of critical high-R&D, STEM-intensive advanced industries. There, these most productive industries comprise more than 30 percent of all employment compared to an average of 9 percent in the largest 100 metros. So it’s an extreme point,” explained Muro.San Jose’s success is notable because its particular confluence of factors makes it one of the few success stories. During the period between 2004 and 2015, the researchers saw that even the most productive areas of the U.S. couldn’t escape the productivity slowdown, unless the area was the site of the energy or tech boom. Beyond those two sectors, only small cities that had major research universities saw productivity growth of greater than 1 percent a year.
These findings run contrary to the economic theory that regions will converge in productivity, which holds that low-productivity regions will catch up over time by importing the skills or technologies of higher-productivity regions. But that doesn’t seem to be occurring in the last decade, which is especially bad news for workers in the low-productivity regions, since higher productivity is associated with higher incomes, lower poverty rates, and higher living standards. “It is worrying that only small pockets of the country—tech hubs, energy boomtowns, or college towns—have registered productivity gains in the recent decade,” the authors say. And that’s precisely because not every place has these industries or resources that are providing the biggest boosts.
“There are tough realities here,” said Muro. “However, in the past, the country has changed the economic trajectory of places, whether through the distributed system of the land grant universities, or major investments in R&D (think Silicon Valley’s formation).”
As for what policy makers should do, Muro and Parilla suggest policies that help with the high cost of housing in these productive regions, to remove the barrier of entry for workers to move to these highly productive cities. But more important is boosting productivity in regions that have been suffering. How to do that, though, is a much more complex question.