North Carolina’s Regions of Migration: Untangling the Migration Web

North Carolina’s Regions of Migration:

Commuter Trends in the Outer Banks

The first region I want to look at is the Northeastern Seashore. A popular tourist destination, scenic and historical region, and home to about 150,000 people, the Northeastern Seashore is primarily rural or small-town. It’s also mostly white, as the map below shows.

Darker blue indicates larger white share of the population.

From the Norfolk suburbs to the Albemarle Sound in the south, there’s a relatively large share of white population, while further west or in downtown Norfolk, African American populations predominate.

Darker green indicates higher income.

As the second map shows, average household incomes also vary by region, with these same majority-white areas also commanding higher average incomes. The outer banks themselves have the highest incomes of all.

Is tourism creating these high incomes? That might be possible, but it doesn’t seem extremely likely: beach tourism isn’t associated with tons of high-paying jobs, but tends instead of be low- and mid-wage and highly seasonal. So what is it?

It turns out that what we’re seeing is a story about commuters. Using County-to-County Worker Flow data from 2006–2010, I estimated how many residents of NC’s Northeastern Seashore travel across the border into the Norfolk-Suffolk-Hampton Roads-Newport News area for work.

From 2006–2010, about 11,000 Northeastern Seashore residents worked in Greater Norfolk. That comes to about 60% of all out-of-state commuters to the region, and 16% of all commuters generally. But perhaps most notably, these 11,000 commuters to Greater Norfolk amount to 17% of all workers residing in the Northeastern Seashore.

That’s a remarkably large amount, and testifies to why all of the counties I include in the Northeastern Seashore are included in the Virginia Beach-Norfolk Combined Statistical Area: for all that the Outer Banks may be a beautiful part of North Carolina’s cultural heritage, they’re inextricably tethered to Virginia’s economy (and especially the military-reliant economy of the Hampton Roads CSA). These economic ties create high migration volumes. It’s not clear precisely why these flows are negative, but certainly the urban connectedness and high commuter volume can explain most of the region’s extraordinarily high migration volume as local residents look for more convenient or attractive neighborhoods, schools, or communities.

North Carolina’s Regions of Migration:

Military Migration is Unbelievably Big

I’ve written many times about the role played by the military in driving migration flows. Military bases dominate the list of counties with the largest migration flows. While some researchers prefer to focus on “civilian migration,” I don’t find that restriction useful any more than I find IRS data restricted to tax-filers to be useful: military migrants (and their families) contribute to the local economy, participate in and impact local culture, experience dislocation from prior residence, etc. They are migrants and, as migrants, fall within my field of analysis. So in general, I don’t differentiate between civilian and military migrants. But for this case, I want to quantify the exact effect of military bases, so breaking out civilians can be useful.

North Carolina has some big military bases. Two in particular stand out: Fort Bragg near Fayetteville and Camp Lejeune near Jacksonville in the Southern Coasts. The Military Ocean Terminal at Sunny Point is also the largest such terminal on the eastern seaboard. So just how big a role do these bases have on migration in North Carolina?

The 2008–2012 ACS County-to-County data file breaks out migration by occupation and employment status, such that we can track military migration separate from civilians. These military migrants include soldiers, some base personnel who may not be strictly “military,” and many military families (though many other military families are not included in this measure).

About 8.5% of all migration into or out of North Carolina involves the military. That amounts to 28,000 in-migrants per year and 14,000 out-migrants. That’s really, really big.

When I look at military migrant in just Greater Fayetteville and the Southern Coasts, military migrants are 35% of all in-migrants, and 18% of all out-migrants. These two regions alone drew 26,000 military in-migrants, and lost 12,000 out-migrants.

Once we account for military migration, the volume of interstate migration in the Southern Coasts falls to 6.9%, and for Greater Fayetteville falls to 5.3%. The Research Triangle’s remains at 5.3%, though it does have a small amount of military migration. Correcting for military migration eliminates most of the gap between the Research Triangle and other regions in terms of gross migration flows, but still doesn’t make the Triangle’s migration record look exceptional.

When I assess net migration, the correction for military migration radically alters which regions we can call “migration winners.” Overall, Greater Fayetteville and the Southern Coasts have positive net migration: 0.3% and 0.9% respectively. Compared to the Research Triangle’s 0.6% rate, you can understand why I label the Triangle’s rate “just average.”

But once I subtract out all military migration flows, net migration in the Southern Coasts falls to -0.2%, and in Greater Fayetteville to -0.4%. Military migration is so large, and so lopsided, that it changes net-emigration regions into net-immigration regions. Areas that, on the economic and social fundamentals, can’t hang on to their resident populations are turned (as if by magic) into champions of migration.

North Carolina’s Regions of Migration:

Crowding Out and Mathematical Illusions

Many careful readers will note that I’ve played a kind of trick: I’ve taken observed flows, subtracted a subset, and appear to have declared that, without that subset, the residual would have been the whole migration flow. But that’s not strictly true.

If there were no military migration into these regions, it would probably be because there were no military bases. If there were no military bases, then that would have spillover effects on migration: military kids headed to college or distant work wouldn’t add to outflows, land used by the military could be put to some other use, civilian labor employed by the military might have some other use, local prices might fall further, whole towns might not even exist. The “static effect” of a military base on migration flows is extremely large, but the “dynamic effect” is much harder to estimate, and could be either larger or smaller, and could change migration flows in either direction.

Thus, I want to exercise caution in extrapolating from this kind of subdivision: “civilian migration” as I’ve calculated is not the same thing as “migration if there were no military bases.” If the military bases shut down tomorrow, the first effect would be massive out-migration by military personnel and civilians whose jobs depended on the base. In the long run, the effects are extremely challenging to estimate. As I launch into the next section discussing the role of education in North Carolina’s migration flows, it’s important to keep in mind that the “static” and the “dynamic” effects of a given variable may be radically different.

North Carolina’s Regions of Migration:

Life in the Brain Factory

As I’ve written several times before, education has a major impact on migration. Educated individuals generally migrate more than the less educated, and major transitions in an individual’s educational career can themselves induce migration (such as enrollment in a distant school). Likewise, education can create more wide-ranging social, academic, and economic networks, creating channels for return migration.

So we should expect that a region with a major educational hub, especially one with competitive graduate programs, should have some interesting migration flows when educational variables are introduced. When I analyzed Western Kentucky, I used freshman enrollment data to approximate the impact of educational institutions on migration. But such enrollments rely on some very specific data that isn’t always readily available, and don’t provide much insight on out-migration.

Luckily, the American Community Survey provides migration flows by education from 2007 to 2011. Isn’t it amazing how, for almost any question I ask, there’s usually an answer in the ACS?

As shown in the chart above, migration of degreed individuals is twice as large in the Research Triangle than in the rest of North Carolina. However, while volume is much higher, it turns out that the Research Triangle actually has net negative migration: it loses about 500 degreed individuals a year to other states, while the rest of North Carolina gains about 7,500. What’s going on here?

First of all, the Triangle also recruits in-state: so it has very high in-migration of degreed or degree-seeking individuals within the state. So its total net migration, rather than just interstate net migration, is more positive. But that adjustment doesn’t explain why interstate migration is so lopsided.

To explain the Research Triangle’s flows, we have to think of universities as brain factories. Their inputs are students and professors instead of metal, robots, and workers. Their outputs are graduates with presumably increased skill levels instead of just iPhones and cars for sale. Thus the flow of students and graduates to a university doesn’t look like the flow of workers for jobs: it looks like the flow of raw materials and finished goods in a manufacturing supply chain. There’s a perpetual negative migration rate because the region “manufactures” and then “exports” the educated migrants.

This is easy to see with a hypothetical. Imagine a bright young 18-year-old from Connecticut enrolls at UNC for her undergraduate degree. She is an in-migrant when she does not have a college degree. She graduates, then gets into Duke for her graduate work. After Duke, she gets a job in Colorado. She migrates away as a graduate-degree migrant. This migrant would show up in one year as a positive flow of undegreed-migrants, and 5–8 years later as a negative flow of a degreed migrant. This is not because the Research Triangle is repulsive to educated migrants, but because it is an education factory. The import of students yields revenues through tuition, and the export of student can yield additional revenues through alumni giving.

Thus, quite reasonably, the Research Triangle has low net migration among the educated, but a very high volume of educated migration. Degreed migrants make up 30% of the Research Triangle’s migration flows compared to just 15% for the rest of the state. So the rest of North Carolina imports brains, pays them, and those skilled workers then pay off the loans they took out to buy their skills. Ultimately, their incomes are transferred in large part back to the brain factory (though because we use loans to pay up front, and those loans are offered by the Federal government instead of the university itself, the university-factory receives its revenues in advance instead of contingent upon future payment).

North Carolina’s Regions of Migration:

Commuting and the Right Measure of Migration

It’s not always clear what the best way to measure migration actually is. There are enormous and decades-long debates in the migration/human mobility community about how we define migration, who “counts” as a migrant (or a refugee, or a displaced person, or as “mobility”). I’ve mentioned commuting many times in this post and in other posts. Now I want to use the lens of commuting to look at how different regions attract migrants who have different “geographical frameworks,” or different perceptions about how they will relate to basic questions like distance and travel.

As it turns out, when I compare Greater Charlotte and the Research Triangle, the Research Triangle has about double the commuting volume within the state. This is remarkable because both regions have similar populations around 2 million, both have similar employment bases around 900,000, and both have similar amounts of population in their neighboring counties. One major difference is that Charlotte directly borders South Carolina, and does receive many commuters from over the southern border. But if I included the over-the-border neighboring counties, I would need to include over-the-border core counties as well, and the effects roughly balance out.

Overall, the Research Triangle draws a much larger commuter population than Charlotte. This tells us something interesting about migration in the Research Triangle.

If Triangle workers are especially likely to commute from elsewhere, then migration caused by economic factors within the Research Triangle may occur outside of the region itself. People migrating for work in Durham may live outside the region at a higher rate than people migrating to Charlotte. This means that the “migration footprint” of the Research Triangle is likely somewhat larger than my direct measurements show.