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.
When people think of Rust Belt or other regions that are either shrinking or growing extremely slowly, what often comes to mind is the thought of rats fleeing a sinking ship. The concern over “brain drain” reinforces this exact type of narrative. And when you look at the net migration figures from the Census Bureau, it’s easy find the image confirmed. For example, here’s net domestic migration for Midwest metro areas from 2007 to 2008:
I’m sure that high out-migration was a big thing fueling the exodus to the suburbs, but are people really leaving the region? Are people really fleeing Detroit and Cleveland on a metro area basis?
Part of the challenge in answering this question is that the Census figures are net: in-migration minus out-migration. So you don’t know if the net figure is negative because lots of people left or because very few people came or both.
Fortunately, there is data out there that lets us disaggregate the number and look at in and out migration individually. It is the tax return data from the Internal Revenue Service. (This is actually one of the major sources the Census Bureau uses in estimating migration). Not many people really work with this data though because it is so painful. A friend who’s a well known demographer recently told me he “found it to be about the worst data I had ever seen, in terms of working with it.”
I believe I have cracked the code on this data, rendering it easily useful for real analysis by ordinary human beings for the first time. In addition to making the basic data easy to use, I also generated a ton of other data from it, including the MSA-MSA migration that I talked about in a previous post. I’m planning to launch a tool for this soon, so if you’re interested, you should definitely mail me so I can tell you when it’s ready.
In the meantime, I wanted to share some interesting things I’m finding in it, notably in the migration rates. I calculated these myself and the numbers are still experimental at this point, but I wanted to share some early results.
Looking at the most recent year for which data is available – 2008 (2009 data comes out in the spring) – here are the ten lowest metro areas for out-migration rate* between 2007 and 2008, along with the all metro are:
Not what you expected, is it? That’s right, Pittsburgh is dead last among all 366 US metro areas I’m tracking in terms of its out-migration rate. People aren’t leaving, just like they aren’t leaving a lot of other places famous for large absolute net domestic out-migration. Not even Cleveland (#13 from the bottom) or Detroit (#17). (In fairness, net migration did turn positive for Pittsburgh this year).
I’m still validating some of the numbers. Large metros seem to have lower rates than small metros, probably an artifact of many small metros being single county. But still, this was surprising even to me.
What’s really killing these places is that they have even lower in-migration. Here’s the bottom 10 MSAs in the US for in-migration rate.
Here’s all 12 of my Midwest MSAs on in-migration rate, as a percent of the US all metro average:
What I tend to see is the Rust Belt and other struggling regions have both very low in-migration and out-migration, and the net migration number is bad because in-migration is very low indeed.
I’m reminded of what Jim Russell once said about one city being a “cul-de-sac of globalization.” That seems to be the effect at work. These cities are not getting the human capital churn they need to build the talent networks necessary to connect them to the global economy. (Places like LA and Chicago are different in my view, since they are really two cities in one – a thriving global city core and a larger lumpen-city that more fits the Rust Belt model).
It made me wonder what the relationship really is between something like out-migration and population growth. Here’s a quick map of 2007-2008 population growth by county in Indiana, growing counties in blue, shrinking counties in red, color shading proportional to the percentage change.
Now here’s county out-migration rate from 2007 to 2008, grayscale, but again with intensity shading:
It’s a bit difficult to tell, but it does look like the belt of stagnant to declining population northeast and southwest Indiana roughly match the low out migration areas on that map.
I was curious so just before this post I dumped out-migration rate and percentage population change for all counties in the US and plotted them quickly:
Hmmm. This one I did in about two seconds right before this blog post when up, so while everything in here is caveat emptor right now, that one particularly so.
Anyhow, I think this analysis shows that we can’t fall into simplistic notions around people fleeing regions. It would appear that the opposite may in fact be true. People are stuck in them – either because they don’t want to leave or because they can’t. I’ve got to believe at some level that recovery means boosting the human capital circulation factor – in and out – significantly. I think these migration rates are a key indicator to watch in seeing if cities are turning the corner. I’ve got the data going back to 1996, and it looks to me like the rates are very stable over time for most of these places. That’s probably not a good sign.
* I calculate the migration rate as a rate per thousand people. The formula I used is (migrants) / ((non-migrants+out-migrants)/1000). If you have feedback on this methodology, I’d love to hear it.