Unexplained unemployment

I’m in a Labor Economics class this quarter, and the assignment/discussion portion of the class is centered around one question: Why is unemployment so high? The part of the answer that I’m most interested in right now is (unsurprisingly) the geographic portion. What explains the huge variation across counties that we see here? (Darker red is a higher unemployment rate).

A big part of it can be explained by the fact that different places have different mixes of industries: resource extraction is doing great right now, so places with a lot of resource extraction are also doing great. So, I accounted for (1) the share of employment in different industries, (2) the growth of different industries from 2001-2007–maybe places with a lot of growth in construction have suffered more than places with a lot of growth in health care, and (3) ratio of those with a college degree to the labor force as a whole.  Then, I taught myself a smidge of Python and made a new map, of which I am quite proud! Here, dark red is high positive “unexplained unemployment” while dark green is large negative “unexplained unemployment”. Dark green means that, after accounting for the local industry mix, that place has a lower unemployment rate than we would expect, while dark red means higher. Here she is: (Note: Alaska, Virginia, and part of northern Colorado are excluded for data reasons).

This map seems to tell a different story. Most of the south looks substantially better after accounting for industry mix, as does coastal California: Los Angeles, the nation’s largest county (and more populous than 42 states–and actually, it may have passed Michigan in the last six months), is doing pretty well, after accounting for its industrial patterns!

By the way, mining is the most reliably low-unemployment industry going. Manufacturing, local government, federal-civilian, federal-military, retail and forestry/fishing are the most reliably high-unemployment. Places that had a lot of growth in military, finance, and hospitality are also looking worse for it, while places with growth in manufacturing and retail did well–suggesting that some manufacturing jobs have been leaving their historical homes for places without much current manufacturing, and the places that the jobs moved to are doing just fine with it. Call it internal off-shoring?

There are some other interesting patterns. Look at the Nebraska-Kansas border for instance. In the first map, there doesn’t seem to be much difference, but in the second, Nebraska looks systematically better amongst border counties. The Louisiana-Texas border is similarly stark. It’s possible that state-level policies are helping Nebraska and Louisiana cope with the recession better. It then might be interesting to look at the county unemployment rates after accounting for state-wide conditions. That gives us this map:

The best way to read this map is probably to focus on one state at a time. For many states, there seems to be an urban/rural distinction: California, Maine, Massachusetts, New York, Ohio, Illinois, Washington, Oregon, Georgia, Tennessee, etc. But that’s only a tendency–Texas and New Mexico don’t seem to follow the pattern. Much of the Mexican border has low leftover unemployment–except for a few counties with deep red. There are also large swathes of inexplicably high unemployment left: along the lower Mississippi river, the Western Slope in Colorado, and parts of Alabama, Georgia, and South Carolina–not to mention the clear separation between Nevada counties.

There’s too much still going on for me to know just what to make of it. But I feel comfortable saying that there is a role for geography in understanding this–if there weren’t, the last map would have the colors scattered at random. But that doesn’t seem to be the case–or, I’m missing some other factors that will explain the rest of the geographic variation. Either way, I’m looking forward to doing more in this class.

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2 thoughts on “Unexplained unemployment

  1. “while places with growth in manufacturing and retail did well–suggesting that some manufacturing jobs have been leaving their historical homes for places without much current manufacturing, and the places that the jobs moved to are doing just fine with it. Call it internal off-shoring?” Jefferson Cowie tracks this phenomenon in his little book titled Capital Moves which tracks RCA moving from spot to spot until it did end up abroad in Mexico.

    But, after wrapping my head around this (some of the terminology was new to me), I’m wondering if some cultural explanations can explain some of the differences for places that should have higher unemployment. For example, I’m thinking maybe the Midwest areas that have lower unemployment are areas where folks have tighter knit communities. You’re not going to let Sally’s dad go unemployed for too long, so you get your buddy Phil to hire him for a while even though Phil can barely afford it.

  2. Yeah, there’s definitely something going on in the second map with regards to geography, and cultural something might be part of it. But why should that be more the case in Nebraska than in Kansas? And the western Louisiana/eastern Texas case–presumably those are places with similar cultural traits, but very different unemployment outcomes.

    One other thing that a lot of the darker green areas (in the second map) have in common is, at first glance, a lot of them avoided the housing boom–and may also have avoiding some of the corresponding pressures on local banks. I’d like to look into adding that in, actually–is there a relationship between bank lending in 2005 (say) or bank failure post-crash, and unemployment?

    Ooh data is easy for that. Kansas had 4x as many as Nebraska. 58 banks failed in Florida, while 5 failed in New York–two states with similar populations. Twice as many failed in Nevada as Utah, which also have similar populations. Obviously I’d have to do a bit more looking into that, but that seems like another one–along with possible cultural things–that might make an impact. Also on the culture front, it’s striking to me how terrible the south is doing in the first map, and how strong it looks in the second (after adjusting for industry mix). What at first looks like it might be a cultural thing basically disappears when you account for the kinds of sectors that the South focused on.

    This is not to deny that culture plays a role! But I think there are offsetting aspects, and I think it’s an incomplete story. You are right about Sally’s dad, but on the other hand, Javier out in LA has a lot of family nearby too, and they know a lot of people just by virtue of being in such a huge city–and someone knows someone with a job.

    Regardless though, interesting stuff! I’ll probably update this idea more as we go through the quarter. Also, thanks again for that RCA book rec, you’d mentioned it before and it sounded pretty interesting. Might be a while before I get to it, but I’d like to at some point.

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