Update: The self-service tool that has easy query access to the IRS migration data, including at the metropolitan area level, is available at www.telestrian.com. You can also read the launch announcement with more info on this tool and what it can do for you.
It’s almost become a truism that human capital is of paramount importance in the modern economy. It’s also becoming evident that networks play an increasingly powerful role as a determinant of urban success. It doesn’t seem like such a leap of logic to hypothesize that a city’s human capital network might be the most important one it has. So you would think cities would consider it mandatory to have a good understanding of their human capital flows. Without that, you are flying blind.
Alas, few cities seem to have even the most rudimentary ideas about this. Why is that? For one thing, it’s not easy to determine. The Census Bureau publishes net migration figures, but that doesn’t tell you anything about where people are coming from or going to, or anything about them. The Internal Revenue Service publishes very useful information on place to place migration, including data about income flows. You’ve probably see this before, such as via the Forbes map that made a splash a few months back.
Unfortunately, the Forbes analysis and most others like it are basically useless. It’s excellent eye candy, but it has key limitations. For one thing, the Forbes map only looks at one year. More importantly, the IRS reports this data in terms of county to county flows, but this isn’t really what we want. What we really would like to understand is metro to metro flows and such. But the data is so painful to work with that you rarely see this done.
However, I cracked the code on this problem. I hope to put out a self-service tool that will revolutionize analysis of this data. If you are interesting in being notified when I launch it, or if you are interested in commissioning custom analysis in the meantime, please shoot me an email.
In the meantime, I will be sharing some interesting findings that I’m already generating with this, though I’ve only scratched the surface myself.
Human Capital Circulation and Gross Migration
Migration numbers are typically reported in terms of net migration: where you are gaining people from and where are you losing them to. That’s important analysis to be sure, but is only one piece of the puzzle. For example, net values don’t tell you the absolute magnitude of the flows between cities. With City A you could have an inflow of 10 and an outflow of 5 for a net inflow of 5 people, while with City B you have an inflow of 10,003 and an outflow of 10,000 for a net inflow of 3. The net number alone obscures important information.
I think you need to look not just at net flow, but also the individual inflows and outflows. And also at something that, with a hat tip to an old University of Louisville study, I call gross migration. That is, the inflow plus the outflow. This I believe is the best measure of human capital circulation between cities and the relative strength of their human capital network relationship.
Let’s illustrate with some quick data from Pittsburgh. Here’s a graph of the top ten net inflow sources for the Pittsburgh MSA. The data is for release dates 2000-2008, which measures people who moved between 1999 and 2008:
|7||Buffalo-Niagara Falls, NY||181|
Here’s the same data, though this time showing the top ten net outflow cities:
|2||Tampa-St. Petersburg-Clearwater, FL||-3,161|
|3||Charlotte-Gastonia-Rock Hill, NC-SC||-3,132|
|5||Atlanta-Sandy Springs-Marietta, GA||-2,262|
|10||Miami-Fort Lauderdale-Pompano Beach, FL||-1,531|
Looking at this, what you see is a city that takes in people from regional metros and exports them largely to the Sun Belt. It’s the story you would expect of a Rust Belt regional center. But look at the 2000-2008 gross migration and we see another part of the narrative:
|3||New York-Northern New Jersey-Long Island, NY-NJ-PA||18,419|
|7||Miami-Fort Lauderdale-Pompano Beach, FL||9,181|
|8||Tampa-St. Petersburg-Clearwater, FL||8,761|
Now that’s interesting, isn’t it? Note the very large circulation numbers with New York, Youngstown and Cleveland that were completely missing from the net view. What we see from this view is a strong alignment with major East Coast metros as well as a secondary flow through the emerging Tech Belt between Cleveland and Pittsburgh.
I hope this gives you a flavor for the reason you should look at numbers other than just net.
Midwest Megaregional Migration
I ran the numbers for gross migration between the twelve large greater Midwest metros I tend to focus on here, and it’s fascinating stuff. Since Chicago is the capital of the region, I’ll share today migration between Chicago and these others cities. Here is a graph of total gross migration for the 200-2008 period. It’s MSA-MSA data – I just shortened the names for space reasons:
Milwaukee is number one, as you might expect. I find it interesting that there is such a gap between the top five and the rest. At one level it is not surprising, as migration follows a sort of gravity model pattern related to size and distance. These cities are either closer and/or bigger. On the other hand, Cleveland isn’t that much smaller or further away than, say, St. Louis. All of the Ohio cities are comparatively low. Indeed, Ohio is only the ninth highest state for migration with Chicago overall.
From this you could probably trace the outline of Chicago’s real sphere of influence from a human capital network perspective. Those top five cities clearly have a tighter relationship with Chicago than the rest. Pittsburgh and Louisville unsurprisingly bring up the rear. They are dubious as Midwest cities to begin with, and this just helps illustrate why.
Incidentally, the low standing of Pittsburgh on Chicago’s migration list, combined with its own East Coast orientation shows perfectly why Penn State has no business being in the Big Ten (IMHO). Also, while there might be a megaregion called Chi-Pitts, it’s not clear to me if Pittsburgh is really in it. Perhaps the are actually a couple of regions in the area from a human capital perspective, one centered on Chicago and another from the remains of the old metals region. This is an area for further research.
By the way, here’s the year by year on the gross migration data:
Migration has held fairly steady, with a sort of mid-decade dip. The exception is Indianapolis, which has been on a fairly steady upward streak. Here’s the detail on Chicago-Indy:
I’d also note that Indy’s ranking is, based on my gut feel, higher than it probably should be, and particularly on a run-rate basis. It’s more or less equal to Detroit and Minneapolis-St. Paul, both much larger cities, and a bit ahead of St. Louis, which is about a million people larger. All of those cities are further away, but it’s interesting nevertheless. And there appears to be a deepening of the human capital relationship. Possibly Indy simply missed the early decade spike some places had and that skews the chart, but it’s certainly something worth noting.
If you are interested in seeing the raw Chicago data, you can download it here in Excel format.
In case you’re wondering, I can make eye candy too. Here’s a bonus map of net migration for Cook County, showing all the counties with which it had measured migration from 2000 to 2008. Net inflows are in blue and net outflows are in red – and no, there isn’t a political message intended! While this doesn’t indicate magnitude, it does in a sense reinforce the migration geography I noted above.