How’s the Economy Where You Live? 3 Interactive Maps Show State-by-State Comparisons

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David Jarman
Is your area booming or busting, or just chugging along?

The economy might be leaving a lot of people dissatisfied, but at least we’re living in a golden age of interactive maps about how the economy sucks. Three different maps released in the last few weeks approach the question from three different angles: wage stagnation, when wages peaked, and men who aren’t currently part of the labor force.

How's the Economy Where You Live 3 Interactive Maps Show State-by-State Comparisons

The Wall Street Journal’s map addresses the question of wage stagnation (click through to see the interactive version of the map), looking county-by-county at whether inflation-adjusted wages are better than they were a decade ago, or not. Dark-colored counties have seen wages increase, while light-colored counties have gone backward. Nearly one-third of all counties, which hold 46 percent of the nation’s population, have seen a decline in median income in the period from 2004 to 2013, when adjusting for inflation. There isn’t a clear red/blue split between the counties that did or didn’t decline, though; 280 of about 700 counties that voted for Barack Obama in 2012 saw declines (about 40 percent), while 800 of 2,400 counties that voted for Mitt Romney saw declines (about 33 percent).

As the WSJ points out, the biggest wage increases came in states most associated with the energy sector: not just new sites of fracking like North Dakota and Wyoming, but also old-school oil patches like Texas and Louisiana. The states with the declines seem, in particular, to be manufacturing-centered (not just traditional smokestack-industry states like Michigan and Ohio, but also the Carolinas). States with either direct (California, Florida) or indirect (Oregon, via the timber industry’s collapse following the collapse in housing construction) housing bubble problems during the 2000s also show up.

Click to enlarge.

Another map comes from the Washington Post, as part of an introduction to a multi-part series about the problems facing the middle class. It’s an interesting chronological map (click through for the interactive version), filtering out the counties according to in which decade inflation-adjusted incomes peaked. Here, the light-colored counties are the ones doing well (with incomes currently peaking), while the dark-colored counties are doing the worst (having peaked furthest in the past). Rust Belt (especially upstate New York) incomes tended to peak in the ’60s, Appalachian incomes peaked in the ’70s, and most places’ incomes peaked in the prosperous ’90s.

This is vaguely reminiscent of an interactive map I created earlier this year, mapping when counties’ populations peaked, but the new map shows something very different: the mostly empty counties across the Great Plains that peaked, population-wise, in the 1920s and 1930s are the ones where incomes are peaking right now. That’s partly thanks to the energy sector, especially fracking, but also because of agriculture, which can be profitable but thanks to automation doesn’t require any near as large a work force as it used to.

Click to enlarge.

The final map is from a New York Times multi-article look at, specifically, men in the work force. It’s a map of the percentage of men of prime working age (25-54) who aren’t working (click through for the interactive version), drilling all the way down to the census tract level. Dark-colored counties have the highest rate of men not working, while light-colored counties have the highest rate of men in the labor force. The lowest rates are in both prosperous urban cores and suburbs in major metropolitan areas, and also in those Great Plains rural counties mentioned above.

The highest rates tend to be in high-poverty areas like the Appalachians, reservations, and the Black Belt, and also some agricultural areas with seasonal work forces. While some urban cores have high levels of worker participation, certain others don’t (try zooming in on Detroit, for instance). There are also high rates in pockets around major universities; this exposes a weakness of this kind of analysis … late-twentysomethings pursuing graduate degrees get lumped in with disabled and long-term unemployed persons. A separate chart helps distinguish these categories, but only at a national level; A recent Pew study also found a similar breakdown of what men who aren’t working do (with “ill or disabled” a plurality, and “unable to find work” not a much bigger segment than stay-at-home dads or full-time students).

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