How the economy looks depends on where you’re standing. Today some states and regions are booming while others are struggling. These local differences matter, not just for people who are looking to move to where the opportunities are, but also for policymakers trying to boost local economic opportunities — and that means the geography of economic anxiety matters for Hillary Clinton and Donald Trump, particularly in key battleground states.
How well a state is doing depends on what measure we look at. It turns out that the places with more economic pain today, as measured by the unemployment rate, are not the places where future job losses are most likely to be a drain. Among key election battlegrounds, high-unemployment states like Pennsylvania and Nevada have a lower share of jobs in shrinking occupations, whereas low-unemployment states like Iowa and Wisconsin have a higher share of jobs in shrinking occupations. In short: the places with more immediate economic pain are not the places at higher risk of longer-term economic drain.
Most of the at-risk occupations are service jobs
Where in the US is there the most economic pain? Unemployment in July (the latest available from the BLS) is highest in Alaska (6.7%) and Nevada (6.5%). Job growth from January 2009 to July 2016 was positive in all but two states: Wyoming and West Virginia (that’s seasonally adjusted nonfarm employment). But economic worries are about the future, and how big trends like globalization and automation will affect local economies. Jobs that get automated or competed away might never come back, and workers who once held those jobs might find their skills have become obsolete, even as technological innovation creates new occupations.
The jobs most at risk, according to the Bureau of Labor Statistics’ (BLS) latest occupational projections, are in production (that is, manufacturing) and farming, forestry, and fishing. But many service-sector occupations are also projected to shrink: the BLS predicts big drops in employment for bookkeepers and accountants, fast food cooks, and mail carriers, for example. In fact, because manufacturing and agricultural employment as a share of the overall job market have plummeted in past decades, most of the shrinking occupations are now service jobs: 57% of the jobs in shrinking occupations are in services, while just 33% are production and repair jobs and 9% are in farming, fishing, or hunting. Furthermore, occupations expected to shrink include some high-paying jobs like nuclear technicians, air traffic controllers, and, perhaps surprisingly, computer programmers (though other computer-related occupations, like software developers, database administrators, and network architects, are expected to grow; here’s more on jobs that offer lots of opportunity).
By matching BLS projections for each occupation with Census data on individuals’ occupations and location, we can see where the highest risk is of jobs disappearing. Nationally, 10.7% of adults are in shrinking occupations, but the risk varies across different places.
Metros and states of anxiety: where more jobs are in shrinking occupations
Let’s start with metropolitan areas, which are the best approximation of local labor markets: they’re defined by the government to reflect social and economic integration as evidenced by commuting patterns. Among the 51 metropolitan areas with at least one million people, the share of jobs in shrinking occupations ranges from 8.2% in metro Washington DC to 11.6% in Milwaukee. Those with the lowest shares of jobs in shrinking occupations include Las Vegas and New Orleans, which have relatively low average incomes and educational attainment levels — which is a reminder that shrinking occupations aren’t necessarily low-wage jobs.
Metros with the lowest share of at-risk jobs
|Rank||Metro||% of jobs in occupations projected to shrink|
|3||Las Vegas-Henderson-Paradise, NV||8.2%|
|4||New Orleans-Metairie, LA||8.7%|
|5||New York-Newark-Jersey City, NY-NJ-PA||8.8%|
Metros with the highest share of at-risk jobs
|Rank||Metro||% of jobs in occupations projected to shrink|
|1||Milwaukee-Waukesha-West Allis, WI||11.6%|
|2||Salt Lake City, UT||11.4%|
|3||Los Angeles-Long Beach-Anaheim, CA||11.3%|
|4||Louisville/Jefferson County, KY-IN||11.3%|
Metro areas don’t give us the full picture, though: much of US employment is outside these largest metropolitan regions; furthermore, large metros have urban, suburban, and sometimes even rural parts. Looking at the entire US, including the non-metropolitan portions, rural areas are at the highest risk from shrinking occupations:
Bigger cities, of course, have their own challenges, starting with more limited and more expensive housing than suburban and rural areas. In some cities with the most favorable occupational mixes, constrained housing supply holds back job growth. Still, rural areas face the strongest headwinds from shrinking occupations.
For most labor market analyses, it makes little sense to look at states: the job markets of, say, Manhattan and Rochester NY; Austin and Midland TX; or San Jose and Bakersfield CA are worlds apart. But for politics, especially in presidential election season, states matter. If the candidates want to understand where the anxious electoral votes are, at-risk occupations tell a very different story than current unemployment rates or recent job growth.
The states with the highest share of workers in shrinking occupations are South Dakota, North Dakota, Montana, Iowa, and Nebraska; yet in all five of those states unemployment is below the national average (as of July 2016), and the Dakotas and Nebraska have among the lowest unemployment nationally. Among all states and Washington DC, the correlation between the share of workers in shrinking occupations and the unemployment rate is -0.45 and statistically significant: that is, states that do better on one measure tend to do worse on the other. (There’s no correlation, positive or negative, between job growth since 2009 and share of workers in shrinking occupations.)
Among the eleven 2016 presidential election battleground states as identified by Politico, Pennsylvania and Nevada have the highest unemployment rate but modest shares of workers in shrinking occupations: their voters may be feeling less anxious about the economy than those high unemployment rates alone suggest. On the flip side, Iowa and Wisconsin have the highest share of workers in shrinking occupations, despite fairly low unemployment rates.
Comparing battleground states to those that are more clearly blue or red, the share of jobs in shrinking occupations again reveals a different, important angle than unemployment or recent job growth.
Blue states, on average, have higher unemployment than either red states or battleground states. But they are in the best shape in that fewer of their jobs are in shrinking occupations. Red states should worry most about disappearing jobs, even though their unemployment rate and recent job growth are in the middle of the pack.
|Unemployment rate, July 2016||Annualized job growth, January 2009-July 2016||% of jobs in shrinking occupations|
For places, as for demographic groups, economic anxiety is hard to measure. States with a higher share of jobs in shrinking occupations tend to have lower unemployment rates. Job seekers looking for opportunity — or presidential candidates looking to feel voters’ pain — need to dig deeper than unemployment rates and recent job growth and take shrinking occupations into account in order to understand where the future of work is cause for optimism or concern.
Data and Methodology
This analysis draws on two datasets: the Bureau of Labor Statistics’ (BLS) Occupational Employment Projections for 2014-2024 (published in December 2015), and the Census Bureau’s American Community Survey (ACS) Public Use Microdata Sample for 2012, 2013, and 2014. Occupation-level projections from BLS were matched with individuals’ occupations in the ACS. To create a consistent set of occupational categories, some occupations in the BLS projections were combined. ACS data were downloaded at IPUMS-USA, University of Minnesota, www.ipums.org.
The chart comparing urban, suburban, and rural areas is based on ACS Place of Work Public Use Microdata Areas (PUMAs), which are typically equivalent to counties in more urban areas or groups of counties in more rural areas. Place of Work PUMA’s were classified by tract-weighted household density into big, dense cities (weighted density of 2000+ households per square mile); big-city suburbs and lower-density cities (1000-2000); lower-density suburbs and smaller cities (500-1000); and small towns and rural areas (0-500). Approximately 30% of jobs are in big, dense cities; 30% in big-city suburbs and lower-density cities; 20% in lower-density suburbs and smaller cities; and 20% in small towns and rural areas.