The past couple of decades have seen America sort itself into two distinct nations, as the more highly skilled and affluent have migrated to a relatively small number of cities and metro areas.
"The highly educated cluster around a few small nodes," writes David Brooks in The New York Times last week. "Decade after decade, smart and educated people flock away from Merced, Calif., Yuma, Ariz., Flint, Mich., and Vineland, N.J. In those places, less than 15 percent of the residents have college degrees. They flock to Washington, Boston, San Jose, Raleigh-Durham and San Francisco. In those places, nearly 50 percent of the residents have college degrees."
The Economist's Ryan Avent adds that "Cities that had relatively skilled populations in 1980 have become more skilled and more productive, and have generally featured fast-rising wages and housing costs. Places that were relatively less skilled, by contrast, have stayed that way and have mostly experienced a growing wage and productivity gap with the high flyers."
But a key question remains: Who benefits and who loses from this talent clustering process? Does it confer broad benefits in the form of higher wages and salaries to workers across the board or do the benefits accrue mainly to smaller group of knowledge, technology, and professional workers?
The University of California, Berkeley’s Enrico Moretti suggests a trickle-down effect, arguing that higher-skill regions benefit all workers by generating higher wages for all workers. Others contend that this new economic geography is at least partially to blame for rising economic inequality.
I've been examining the winners and losers from this talent clustering process in ongoing research with Charlotta Mellander and our Martin Prosperity Institute team. This research divides workers into three socio-economic classes — highly skilled knowledge, professional, and creative workers, and less skilled and lower paid blue-collar and service workers — and takes into the account the wages and housing costs borne by each.
Our main takeaway: On close inspection, talent clustering provides little in the way of trickle-down benefits. Its benefits flow disproportionately to more highly-skilled knowledge, professional and creative workers whose higher wages and salaries are more than sufficient to cover more expensive housing in these locations. While less-skilled service and blue-collar workers also earn more money in knowledge-based metros, those gains disappear once their higher housing costs are taken into account.
Our results are still preliminary, and it's worth remembering that correlation points to an association between two variables but does not identify what causes what. Still the broad story that emerges from our findings helps us better understand the true winners and losers from America's new economic geography.
At first blush, everyone seems to benefit from the clustering and sorting of talent. The wages of all types and classes of workers track the wages of the most skilled group, according to our analysis. The wages of both lower skilled service and blue-collar workers are significantly correlated with wages for knowledge, professional creative workers (with correlations of .80 for service wages and .62 for blue-collar wages).
Everyone also initially seems to benefit from talent clustering in larger metros as well. Bigger metros bring powerful clustering and agglomeration effects; they have faster metabolisms and greater rates of innovation. Improved productivity translates to higher wages across the board, as countless studies have shown. So it's not surprising that average wages closely track metro population, as the scatter-graph below shows. The correlation between average wages and metro population is considerable (.58), and it holds for all three class of workers: knowledge, professional and creative workers (.69), service workers (.46) and blue-collar workers (.28). Data for individual places is embedded in each chart.
But, housing costs are also higher in these larger, more skilled metros. Residents pay a significant premium for the increased productivity they offer, as well as for their amenities, everything from views and good weather and coastlines to restaurants and arts and cultural venues. Housing costs rise as good jobs and more highly skilled workers gravitate to these places, a process that is exacerbated by restrictive zoning regulations, as Avent argues in his book, The Gated City. The correlation between housing costs and knowledge, professional and creative wages is considerable (.80), as well as between housing costs and metro population (.53). The scatter-graph below shows the relationship between the latter.
Still, even when we look at the amount of wages left over after paying for housing (subtracting median housing costs from average salaries and wages), workers on average still seem to make out better from talent clustering. Workers in San Jose — home to Silicon Valley — do the best, with over $4,000 per month, or $48,556 per year, left over after paying for housing. Much the same is true in San Francisco where the average worker has $3,767 per month, or $45,200 per year, left over after housing, and Washington, D.C., where the amount left over is $3,609 per month, which works out to $43,308 a year.
But — and here is where the story gets way more interesting — this overall effect turns out to be an illusion. The "average" amount left over is higher simply because the most highly skilled and highly paid group does so well that it pulls up overall wages. The punch line changes dramatically once we consider the effects of higher housing costs on the three different classes of workers.
Highly skilled knowledge, professional, and creative workers continue to benefit. They have more than enough left over in the more expensive metros. The positive correlation between their wages left over and housing costs (.58) indicates this, and the line on the scatter-graph points upward.
But the opposite is true for the other two classes of workers. The correlations between left-over wages and housing costs are negative and significant for each of them (-.36 for service workers and -.20 for blue-collar workers), and the lines on the scatter-graphs slope down.
The trickle-down effect disappears once the higher housing costs borne by less skilled workers are taken into account. The benefits of highly skilled regions accrue mainly to knowledge, professional, and creative workers. While less-skilled blue-collar and service workers also earn more in these places, more expensive housing costs eat away those gains. There is a rising tide of sorts, but it only lifts about the most advantaged third of the workforce, leaving the other 66 percent much further behind.
The full effects of talent clustering are even more insidious. Avent points to research by Rebecca Diamond, a graduate student in economics at Harvard, which shows that this sorting process involves migrations away from as well as to knowledge-based metros. As she puts it, "[t]he combination of desirable wage and amenity growth for all workers causes large amounts of in-migration, as college workers are particularly attracted by desirable amenities, while low skill workers are particularly attracted by desirable wages." But this leads directly to higher housing costs, which according to Diamond "disproportionately discourage low skill workers from living in these high wage, high amenity cities." This creates an additional level of inequality — inequality of well-being — where more skilled workers not only take home more money, but benefit from better neighborhoods, superior amenities, and better schools. This well-being inequality, Diamond explains, is an additional 20 percent higher than can be explained by the simple wage gap between college and high school grads.
Inequality in America thus extends far beyond income to include the basic conditions that determine and reinforce avenues for upward mobility and future economic success in the long run. "This sorting is self-reinforcing," Brooks writes in the Times piece, "and it seems to grow more unforgiving every year."
It's not just a vicious cycle but an unsustainable one — economically, politically, and morally.