Richard Florida is a co-founder and editor at large of CityLab and a senior editor at The Atlantic. He is a university professor in the University of Toronto’s School of Cities and Rotman School of Management, and a distinguished fellow at New York University’s Schack Institute of Real Estate and visiting fellow at Florida International University.
Before 1980, places in America with lower average incomes grew faster than their richer counterparts, so that incomes converged. Today, that’s no longer the case.
One of the biggest takeaways from the election of Donald Trump was what it revealed about the polarization of America by class and geography. Knowledge workers and manufacturing workers occupy not just different classes, but different spaces and worlds.
The growing divide between the higher-skilled, higher-income, more educated workers who occupy Blue America and the lower-skilled, lower-income, less educated workers of Red America is something economists increasingly refer to as the Great Divergence.
The Great Divergence has happened in just the past few decades. For much of the 20th century, we saw the opposite pattern: The incomes of workers actually converged, both across skill groups and across regions of the country. You can think of this as a rising-tide-lifts-all-boats kind of economy.
But that once-stable pattern has fallen by the wayside. High-paying blue-collar jobs have faded, and the labor market has bifurcated into high-paid knowledge workers and low-paid service workers. Geographic clustering amplified this as knowledge workers packed themselves into a select group of large cities and and tech hubs. America and Americans have split apart by class and geography.
Two recent studies take a closer look at the factors that are driving the Great Divergence.
How states have drifted apart
The first, by economists Peter Ganong and Daniel Shoag, examines the Great Divergence across states. For the century that ran from 1880 to 1980, incomes across states converged at a rate of 1.8 percent per year. Over this period, population growth and income growth went hand in hand.
But that convergence slowed to less than half its historical pace between 1990 and 2010. At the same time, population growth and income became untethered from one another, as the charts below show. The x-axes show the starting income per capita—the baseline average that wages started at in a state. The y-axes represent the annual income growth rate, or how much wages increased over time.
The steep line in the chart on the left shows how incomes converged across states from 1940 to 1960. The less a state earned initially, the faster it would grow.
But the flat line in the chart to the right shows how this income convergence broke down after 1990 and turned to divergence. No longer did growth correlate with lower wages to encourage economic growth.
The Great Divergence is further magnified by the huge variation in housing costs between states—something I pointed out back in 2014. While higher-skilled knowledge workers make enough to cover these costs, lower-skilled service workers have seen huge shares of their income eaten up by housing. Ganong and Shoag’s study illustrates this by contrasting the wages of lawyers and janitors in different parts of the country.
In New York, housing eats up 21 percent of lawyers’ income, but 52 percent of janitors’ income. After housing costs are taken into account, janitors end up earning less in New York than in the Deep South. Skilled workers have more than enough left over after paying for housing, but unskilled workers see their wages whittled away by the housing costs of expensive cities.
The result is a sorting process by which knowledge workers concentrate in large, dense, more innovative and productive locations, while service workers are shunted off to other parts of the country with lower housing costs.
This sorting process is exacerbated by land-use restrictions, which constrain the amount of housing that can be built in large, dense, productive places. These restrictions not only make housing more expensive in these areas, they price out less skilled groups and contribute to the Great Divergence.
The Great Divergence of cities
The second study to look at is a working paper by Elisa Giannone at the University of Chicago, which tackles the Great Divergence between cities or metro areas. Her research focuses on the intersection of what economists call skill-biased technical change and tightly clustered agglomerations of business and talent in contributing to the Great Divergence between cities.
The charts of metro wages below, from Giannone’s study, mirror those of state incomes by Ganong and Shoag above.
On the chart to the left, the line sloping downward sharply indicates the convergence of wages across metros from 1940 to 1980. During this period, wage growth in poorer metros outpaced wages in richer ones by about 1.4 percent per year. The nearly flat line in the chart to the right highlights the more recent divergence of wages between 1980 and 2010. Note the positioning of Boston, San Francisco, and New York in the upper-right-hand corner of the chart for the most recent period. Look at how far their wages diverged from other metros, including Los Angeles and Chicago.
This trend has been almost entirely driven by the gains of high-skilled knowledge workers as the next set of charts, below, testify. The red line represents workers who did not complete college, while the blue line is workers with a college degree or more.
As the chart on the left shows, from 1940 to 1980, the wages of both types of workers converged across metros. But as can be seen in the chart on the right, between 1980 and 2010, these two lines diverged.
The wages of lower-skilled workers continued to converge, but the wages of higher skilled workers diverged radically. Again, look at how far New York, San Francisco, and Boston sit above the line, showing the substantial divergence of high-skill wages in those metros. The Great Divergence thus reflects the clustering of highly-skilled, highly-educated knowledge workers in these metros.
America’s division into blue and red states and cities is not just a result of political preferences and ideology, but of the sorting of its people into distinct into separate classes and locations.