The strong national economic recovery in recent years hides big differences across local labor markets. Today unemployment ranges from less than three percent in some states to more than six percent in others. Many downtowns have seen a revival, luring both educated young adults and some corporate headquarters back to city centers. The gap between rich and poor metros is growing, affecting our politics: The 2016 presidential election was more geographically polarized than previous elections, and the vote in small-town and rural areas and economically struggling regions swung strongly toward President Trump.
As these gaps in local economic performance grow and become more urgent, we’re watching whether these trends are continuing or changing. Yesterday the Bureau of Labor Statistics’ (BLS) Quarterly Census of Employment and Wages (QCEW) — which provides the most current and complete look at jobs at the county level — published data for the third quarter of 2016. We classified counties by their metropolitan size and whether they are urban or suburban; metropolitan areas are made up of one or more counties (see note). Here are the highlights of the data release.
The Suburbs Lead in Job Growth, While Rural Areas Slipped
Job growth from the third quarter of 2015 to the third quarter of 2016 was fastest in the lower-density suburbs of large metropolitan areas, with populations over one million. In those counties, employment grew 2.2%, slightly ahead of growth in higher-density suburban counties (2.1%) and in urban counties (2.0%) of large metros. Despite the publicized moves of some jobs to downtowns, job growth is slightly faster in the more suburban portions of large metros. Similarly, population is now growing faster in suburban than urban areas, consistent with the long-term trend.
Large metros — both their urban and suburban portions — account for almost 60% of U.S. jobs. In the rest of America, where the other 40% work, job growth lags. Employment increased 1.6% in mid-size metros and just 0.9% in small metros, while falling ever so slightly (by 0.02%) in non-metropolitan, largely rural areas.
Wages Grew By Almost 7% in Urban Counties
Wage growth, however, was strongest in the urban counties of large metros, where aggregate wages grew by 6.9%. (Both employment growth and wage growth per worker contribute to aggregate wage growth.) Unlike employment, aggregate wages are rising faster in urban counties than in suburban counties of large metros — consistent with the movement of some headquarters with well-paid executives to downtowns. Wage growth, like job growth, lags in midsize and smaller metros, with non-metropolitan areas even further behind.
This most recent year of data reveals a bounceback for large metros generally and their urban counties in particular. From 2000 to 2007, as the housing bubble formed and peaked, job growth in non-metropolitan areas exceeded that in large-metro urban counties. Then, from 2007 to 2015, during the bust and recovery, these urban counties bucked the national trend and saw faster job growth than in the bubble, though still behind suburban counties. Now, urban counties have nearly caught up on job growth and lead on wage growth.
What’s Behind the Differences?
What’s driving job growth in large metros and, especially, wage growth in the urban parts of large metros? Higher-wage jobs might be following educated, young workers, who are increasingly living in dense, urban neighborhoods as other demographic groups move to the suburbs. Broader economic shifts also favor big cities: The occupations projected to grow tend to be more urban, while shrinking sectors like manufacturing and farming tend to be located outside large metros. Although one headwind for job growth in many large cities is that housing is limited and expensive, on balance economic growth is increasingly tilting toward large metros.
Yet even among large metros, there are big differences in economic growth. Job growth between the third quarters of 2015 and 2016 was fastest in the Deltona-Daytona Beach-Ormond Beach, FL, metro area. Four of the six large metros with the fastest job growth were in Florida; the rest of the top ten were in the Mountain states and elsewhere in the South.
Wage growth was also fastest in the South and West, but one difference is that three California metros — San Francisco – Oakland, San Jose, and Riverside – San Bernardino — were among those with the biggest wage gains but not the largest job gains. In the Bay Area in particular, a shortage of housing holds back job growth while firms continue to pay more to hire those who can afford to live there.
The large metros that buck the trend are those dependent on the energy industry. Houston, New Orleans, Tulsa, and Oklahoma City were among the large metros with job losses and sluggish wage growth. On both measures, they fared even worse than non-metropolitan America did.
All data in this post are from the Bureau of Labor Statistics’ (BLS) Quarterly Census of Employment and Wages (QCEW). Wages typically include bonuses, options, and other forms of compensation. All wage data were converted to constant 2016 dollars using the CPI-U for August of each year.
Metropolitan areas are defined as of 2013 and classified by their 2010 Census population into large (1,000,000+), mid-size (250,000-999,999), small (<250,000), and non-metropolitan. Metropolitan areas are defined by the Office of Management and Budget and consist of one or more counties. Counties of large metropolitan areas are classified based on tract-weighted density of households per square mile, as of the 2010 Census, into urban (2000+); higher-density suburban (1000-2000); and lower-density suburban (<1000). Tract-weighted density equals the average density of the Census tracts in a county, weighted by tract households; compared with a standard density measure, it is less skewed by large areas of uninhabited land. Tract-weighted household density of 2000 is close to the level that survey respondents consider urban, as explained in this post.
The metro rankings at the end of the post included the 104 metropolitan areas with at least 500,000 people.