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.
For the first time, economists have put a price tag on restrictive urban land use policies.
The dearth of affordable housing options in superstar cities like New York, San Francisco and San Jose (home of Silicon Valley) costs the U.S. economy about $1.6 trillion a year in lost wages and productivity, according to a new analysis from economists Chang-Tai Hsieh of the University of Chicago and Enrico Moretti of the University of California at Berkeley. The study, which journalists like The Economist’s Ryan Avent and Vox’s Tim Lee have written about, was made publicly available as a National Bureau of Economic Research working paper earlier this month.
While we know that cities and metro areas contribute massively to economic growth—the nation’s 380 plus metro areas generated $14.6 trillion in GDP in 2012, about 90 percent of the total—we know a great deal less about which factors limit the growth of cities and metros. Economists such as Edward Glaeser have raised important questions about how antiquated zoning, building codes and NIMBYism restrict development and therefore damage the economy, but until this study no one had developed defensible estimates of the costs of such constrained development on the U.S. economy broadly. The title of the study, “Why Cities Matter: Local Growth and Aggregate Growth,” reflects Hsieh and Moretti’s focus on ferreting out the contributions cities and metros do—or don’t—make to overall U.S. economic growth.
To get at this, Hsieh and Moretti develop a statistical model—a spatial equilibrium model to be more precise—of the contribution each U.S. city and metro make to national economic growth. Their model traces the economic contribution of 220 metros to overall U.S. economic growth over the more than five decade period spanning 1964 (the first year for which comprehensive data on wages for metros is available) to 2009, based on data from the U.S. Census Bureau’s County Business Patterns (CBP) and supplemented with data on the characteristics of workers (race, gender, age, union status and educational attainment) from the American Community Survey and the Current Population Survey. To look at the effects of housing on wages and productivity, the economists use data on housing supply developed by MIT economist Albert Saiz, and look specifically at the effects of policies that restrict the supply of housing via the Wharton Residential Land Use Regulatory Index.
Put more simply, the economists’ research examines the geographic allocation of workers across the United States, and tests the following proposition: What might happen if workers were free to move to the cities and metros with the most robust economies, where they could be most productive, thus fueling even greater productivity and growth for the U.S. economy as a whole? To get at this, Hsieh and Moretti develop a number of alternative scenarios based on the ability of workers to move to and settle in these highly productive metros. The exercise leads to several intriguing findings.
The Limits of Superstar Cities
First off, Hsieh and Moretti find that when they take wages into account, economic growth over the past half century was powered by a limited number of metro areas. Specifically, they find that roughly 75 percent of the nation’s economic growth between 1964 and 2009 came from a relatively small group of Southern metros and 19 other large metros. Even though superstar metros like New York, San Francisco, and San Jose created great wealth in sectors like finance and high-tech, nearly all of those gains were eaten up by the wages used to pay for higher housing costs. Greater New York, for example, was singlehandedly responsible for 12 percent of the nation’s aggregate output growth between 1964 and 2009, but when housing costs are taken into account, that figure falls to less than 5 percent growth. As the authors point out, “the main effect of the fast productivity growth in New York, San Francisco, and San Jose was an increase in local housing prices and local wages, not in employment.”
The crux of the economists’ analysis is their models, which create an “alternate universe” where workers can move freely to where they can contribute the most to the U.S. economy. They note the substantial wage differentials between the superstar cities of New York, San Francisco and San Jose and others over the past half-century. To correct for this, their models essentially reallocate workers in today’s economy according to the prevailing wage back in 1964. Based on this, they find that employment in New York would increase by nearly 800 percent, while it would grow by more than 500 percent in San Jose and San Francisco.
Overall, the economists calculate this would amount to an annual wage increase of $8,775 for the average worker. If the geographic dispersion of wages was the same in 2009 as it was in 1964, they estimate that America’s overall GDP in 2009 would have been 13.5 percent higher—a nearly $2 trillion economic gain.
The next step in their analysis considers why workers are not flowing to the most productive locations. Specifically, they look at whether the issue is that superstar cities like New York and San Francisco have become too crowded, noisy and unpleasant, or whether it’s policies like zoning and building codes, or NIMBYism, that restrict the supply of housing. Their next set of models relax housing and land use restrictions in these superstar cities to those of the median American metro. Now the economists find that U.S productivity increases by 9.7 percent, or roughly $1.4 trillion.
What Hsieh and Moretti have conducted here is a provocative thought experiment. To their credit, they take great pains to point out the caveats and limitations to their findings. There are many ways to frame these scenarios and slice and dice these numbers. That said, the economists’ estimates provide a stark reminder of the very real hit the U.S. economy takes every year because of its inefficient and suboptimal spatial structure. Instead of fueling productivity and growth, too much of America’s urban economic power is simply being wasted on higher housing bills.
Their analysis also reminds us of how spiky and uneven the knowledge economy is. This is a natural result of the clustering force—the basic motor of economic growth. Left to its own devices, without the impediments of higher housing costs and other factors, the U.S. economy would not only be more productive, but far, far more uneven and spikier than it currently is. While cities are certainly crucial to economic growth and while mayors can do a great deal, coping with this kind of inequality between and within places requires a concerted national urban policy.
Transit Is (Part of) the Answer
How to begin to fix the problem? Here the authors offer a welcome corrective to the naïve notion promoted by too many urban economists that simply loosening housing restrictions and overcoming urban NIMBYism will magically solve the problems of America’s superstar cities.
Moretti and Hseih rightly point out that a big part of the solution lies in transit. As I have long argued, transit is a key part of the great reset required for our current era of knowledge-based capitalism.
Transit can work on two levels. Within metros, it can more seamlessly connect suburban areas to the more clustered urban core, enabling workers to commute from greater distances while also spurring denser clustering and development along transit corridors. And it can help stretch labor and housing markets across metros, creating more economically functional mega-regions. As Moretti and Hsieh point out, high-speed rail would help connect “local labor markets characterized by high productivity and high nominal wages to local labor markets characterized by low nominal wages.” They specifically cite the example of California’s high-speed rail line, which could “connect low-wage cities in California’s Central Valley—Sacramento, Stockton, Modesto, Fresno—to high productivity jobs in the San Francisco Bay Area.“
“This could allow the labor supply to the San Francisco economy to increase overnight without changing San Francisco housing supply constraints,” they conclude. The economists point to the vast transit networks in London and Tokyo as a way to cope with the constraint of high housing prices. Even though wages in these two cities are high, the authors point out they would be even higher without such extensive transit. The U.K. and Japan are substantially richer as a result.
The transition from industrial capitalism to a placed-based knowledge economy will not just magically happen. Moretti and Hsieh’s study reminds us of the enormous costs of trying to run the powerful, highly clustered new economy on the platform of our outmoded suburban, industrial model. Unleashing the productive power of this new age requires a spatial fix based on transit-based infrastructure and a more flexible housing system. Without that, as Moretti and Hsieh so pointedly remind us, we will continue to squander this country’s productive potential, its economic performance and, critically, our overall well-being.