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.
Mapping inequality across U.S. metros.
Inequality is shaping up to be one of the biggest issues in the 2012 presidential election. The Occupy movement may have waned since last fall, but its focus on the privileges of the top one percent has yet to go away.
Most economists argue that rising inequality is driven by broader structural changes in the economy. Globalization has shifted manufacturing jobs to lower wage countries like China; new technologies and increases in productivity have eliminated millions of the low-skill but high-paying jobs that were left.
As the middle class has disappeared, the job market has literally cleaved in two. On one side are high-paying, professional, knowledge, and creative jobs that require considerable education and skill. But the number of lower-wage jobs in fields like personal care, retail sales, and food service is expanding even faster. This process, one of "skill-biased technical change," according to MIT economist David Autor, has shaped the huge rise in wage inequality, which in turn underpins a broader set of social, cultural, geographic, income, and other inequalities.
Most studies of inequality have focused exclusively on its manifestations on a national or international scale, but there is much to be learned by examining local patterns. With the help of my Martin Prosperity Institute colleagues Kevin Stolarick, Charlotta Mellander, and Zara Matheson, I began by simply mapping two different measures of inequality – wage inequality and income inequality – across America’s 350 metro areas.
(Click on the map for a larger image)
The above map charts the geography of wage inequality. It’s based on a measure of wage inequality developed by Stolarick that compares the wages of those in lower skill service and manufacturing employment to those higher skill knowledge, professional, and creative jobs across U.S. metros. (For my technically-inclined readers, the measure is based on the Theil Index).
The variation in wage inequality is considerable, ranging from a high of .50 in Huntsville, Alabama and .48 in San Jose (Silicon Valley), to a low of .22 in Hanford-Corcoran, California and Elkhart-Goshen, Indiana.
The list of the most unequal metros on this score reads like a who’s who of major knowledge economy centers. Huntsville (a center for semiconductor and high-tech industry) and Silicon Valley come in first and second place. College Station-Bryan, Texas is third, Boulder, Colorado, named by Business Week as the number one place for new start-ups, is fourth, Durham, North Carolina, in the famed Research Triangle is fifth, and high-tech Austin, Texas is ninth. New York (11th), Los Angeles (12th), Washington, D.C. (16th), and San Francisco (18th) all number among the top twenty metros with the most unequal wages.
Even though the wage gap is greater in more highly-skilled, knowledge-based metros, those at the bottom of the wage scale also do better in them. A metro’s average wage is closely linked to its average wage for creative class workers. The correlation between the two is a whopping .94, an almost perfect relationship. The wages of lower-skilled service and blue-collar workers are also higher in creative class metros, with correlations of better than .6 and .8., respectively.
(Click on the map for a larger image)
The second map (above) charts inequality across American metros using the standard measure of income inequality based on the Gini coefficient (the figures come from the U.S. Census Bureau’s 2010 American Community Survey). While wage inequality considers the differences between salaries only, this measure of income inequality compares all income, including rents, royalties, and dividends.
What’s striking is how different the two maps are. Bridgeport-Stamford, Connecticut, has the highest level of overall income inequality in the nation (no surprise to anyone who has made the short drive from leafy Westport to gritty, downtown Bridgeport). Greater New York is seventh, and Miami ninth. But those three are the only metros with more than one million people to make the list. The majority of unequal metros are much smaller, like Naples, Gainesville, and Vero Beach, Florida, and College Station, Texas.
College Station and Gainesville are far from the only college towns represented – Athens, Georgia, Morgantown, West Virginia, Lawrence, Kansas. Corvallis, Oregon; Auburn, Alabama; and Ithaca, New York, score relatively high, along with some industrial metros like Brownsville, Texas.
High-tech, knowledge-based metros are conspicuously absent from this list.
The graph (above) compares metros on the two measures of inequality, wage and income inequality. It arrays into four basic quadrants. Metros in the upper right-hand corner – Bridgeport, New York, Gainesville, College Station, and Boulder face the double whammy of high income and high wage inequality. Metros in the lower right – including notable high-tech clusters like San Jose (Silicon Valley), Austin, and Huntsville, Alabama – have relatively high levels of wage inequality alongside lower levels of income inequality.
Metros in the upper left – for example, Tuscaloosa, Alabama, and Miami – have high income inequality alongside relatively low levels of wage inequality. Lastly, metros in the lower left – for example, Sheboygan, Wisconsin, and Ogden and St. George, Utah, – have relatively low levels of both wage and income inequality.
There's only a modest association between these two measures of inequality, according to our statistical analysis. In fact, wage inequality accounts for just 15 percent of the variation in income equality across metros.
What accounts for the rest? Why are these two kinds of inequality so different? What are the key factors that underpin income inequality in America? I'll dig into these issues in my next post.