Sunday, July 24th, 2011

New Data Shows Slowing Migration in America

The Internal Revenue Service just released its benchmark place to place migration data for 2009. This tracks moves from county to county and state to state for people who filed tax returns between calendar year 2008 and 2009. My initial look at the data confirms what other sources such that Current Population Survey have shown, namely that migration has slowed during the Great Recession. I’m going to cheat though and not actually show much of that despite my enticing title, and instead illustrate a few other points the come out from this data.

As I’ve said before, this data is a gold mine of information. Few people seem to use it though, probably because it is so cumbersome to work with for non-specialists. One of the biggest reasons I built my Telestrian system was to create a platform that would actually make this data usable for me. It is by far the best system I’ve ever seen for analyzing this data. And not only is it better, it’s cheaper. Just to get the IRS to ship you the full data set – in the form of over 3,000 Excel spreadsheet I might add – is $650 dollars, but you can get access to to it via Telestrian for only $49/year.

(If you are a researcher or other person who would be interested in getting a complete copy of the data in a file format that is ready to import into a database, email me. In addition to the base IRS files in a usable form, I’ve created a full matrix of in, out, gross, and net migration for people (exemptions), households (returns), income (AGI), household size (exemptions/return), and household income (AGI/return) for not just county-county and state-state, but also MSA-MSA and MSA-state for years 1996-2010. This is about 2 million rows per migration type, plus there are dozens of other summary statistics available from the files).

Megaregional Migration

With that out of the way, let’s take a look at some interesting things. I’d previously showed a chart of gross migration between Chicago and other major Midwest metros. Gross migration is one of the better measures of true human capital circulation between cities, and indicates which metros have the tightest talent linkages with Chicago. Here’s the update for 2000-2009 (note that year 2001 is people who moved between 2000-2001, so that’s why that’s the base year. This applies to all the charts and data).

You can see here the generally slowing migration I alluded to earlier in the 2009 data series though in some cases it’s still higher than the dot com recession earlier in the decade. The gap between St. Louis in Columbus is quite large as you can see. Clearly, certain nearby cities, as expected, have greater flows and thus are in a way better connected to Chicago.

You might be wondering what the net flows are. I’m glad you asked. Here’s the totals:

Unsurprisingly, struggling Detroit and Cleveland lead the list for inbound migrants. Looking at this chart, I also can’t help but wonder if the high net flows from Chicago to Indianapolis is what enables Indy to maintain a slight population growth lead over places like Columbus that are also rapidly growing in general.

Of course, people is one thing, but you might suggest that it is the high talent individuals that matter more for a city’s economic future. The IRS doesn’t measure that directly, but it does give data on income. You could potentially use this as a proxy. Here is a chart showing total income (AGI) flows:

Note that this data is in thousands, so in this case Detroit actually sent over the last decade households that earn $400 million per year. The total income lost over the decade actually is far higher, because as I note, that’s per year income, so we should really look at it on a total accumulated loss basis perhaps, but I didn’t calculate that for now.

That’s total dollars, but what about the income per person? We can’t quite get there, but we can look at the average per household (i.e., tax return). If we do that, here’s what we see:

Now there are some limits to this data. The annual values are arithmetic means. Probably median would be better, but that data is not available. Also, to save time I used a straight average of the annual values, when probably some type of weighted average would have been better. But as a quick look, this is fine. What it shows is that with the exception of Indianapolis, Chicago is losing higher income people to other cities. Again, I’d caution to do a more rigorous calc before reading too much into this.

The Indianapolis case is interesting. It is a high net importer, but is importing lower income households than it is exporting, which is contrary to the other cities. I took at look at the disaggregated inbound and outbound flows quickly, and it looks like the households going back and forth between Indy and Chicago are lower income than those of any other city. Plenty to explore here.

Again, you start looking at this and the possibilities for serious research are endless, but alas, we’ve only got time for a blog post.

What Type of City Are You?

Another interesting thing jumped out at me when looking at cities. It is the migration pattern differences between the large tier one cities and smaller regional cities. Let’s illustrate this by showing the top 10 sources of gross migration (circulation) for Chicago and Indianapolis. Here’s Chicago:

Row Metro 2001 2002 2003 2004 2005 2006 2007 2008 2009 Total
1 New York-Northern New Jersey-Long Island, NY-NJ-PA 8,819 8,603 8,409 8,260 9,117 9,478 8,991 9,572 9,685 80,934
2 Los Angeles-Long Beach-Santa Ana, CA 9,041 8,540 8,439 8,510 8,052 8,327 8,146 8,358 7,902 75,315
3 Phoenix-Mesa-Glendale, AZ 8,647 9,067 7,889 8,427 8,765 8,811 8,082 7,394 7,274 74,356
4 Rockford, IL 6,062 6,608 7,146 7,411 8,297 9,172 8,629 7,637 6,278 67,240
5 Milwaukee-Waukesha-West Allis, WI 7,001 6,586 5,955 5,901 6,241 6,634 6,528 6,562 6,180 57,588
6 Dallas-Fort Worth-Arlington, TX 6,929 5,750 5,283 5,272 5,616 6,159 6,163 6,206 5,955 53,333
7 Atlanta-Sandy Springs-Marietta, GA 5,931 6,101 5,237 5,309 5,574 5,665 5,781 5,697 5,050 50,345
8 Indianapolis-Carmel, IN 4,826 4,890 5,033 5,375 5,378 5,644 5,431 6,126 5,472 48,175
9 Detroit-Warren-Livonia, MI 5,840 5,006 4,643 4,572 4,880 5,880 5,393 6,357 5,219 47,790
10 Minneapolis-St. Paul-Bloomington, MN-WI 5,721 5,429 5,199 4,878 5,019 5,251 5,216 5,327 5,091 47,131

And here is Indianapolis:

Row Metro 2001 2002 2003 2004 2005 2006 2007 2008 2009 Total
1 Chicago-Joliet-Naperville, IL-IN-WI 4,826 4,890 5,033 5,375 5,378 5,644 5,431 6,126 5,472 48,175
2 Bloomington, IN 3,501 3,591 3,521 3,430 3,259 3,256 3,146 3,442 3,403 30,549
3 Anderson, IN 2,632 2,721 2,525 2,924 2,972 3,320 3,132 3,493 3,098 26,817
4 Columbus, IN 1,870 1,953 1,850 1,943 1,804 1,890 1,813 1,929 1,936 16,988
5 Lafayette, IN 1,692 1,720 1,789 1,755 1,699 1,902 1,908 1,884 1,931 16,280
6 Terre Haute, IN 1,791 1,620 1,807 1,606 1,871 1,611 1,546 1,756 1,694 15,302
7 Fort Wayne, IN 1,644 1,552 1,415 1,423 1,641 1,737 1,633 1,756 1,664 14,465
8 Muncie, IN 1,171 1,337 1,297 1,241 1,198 1,169 1,366 1,260 1,286 11,325
9 Kokomo, IN 1,202 1,239 1,115 1,311 1,192 1,232 1,159 1,319 1,249 11,018
10 Cincinnati-Middletown, OH-KY-IN 1,449 1,299 1,277 1,090 1,194 1,211 1,139 1,237 1,009 10,905

Interesting, isn’t it? While Chicago does exchange people with regional cities, it also has a lot of circulation with other national and tier one cities, including it’s top two of New York and LA. Indianapolis, by contrast, apart from its huge circulation with Chicago seems to primarily recirculate people within Indiana. Its human capital networks are much more parochial.

New York City

I thought I would also take a quick look at New York metro. Here’s a map of net migration from 2000-2009 using a five bucket sort with separate positive and negative gradients:

It looks like New York is drawing in from the Heartland while exporting everywhere else, though the magnitude of the imports is far less than the exports. This is not surprising given that New York is well known for very large net out migration. (This is not necessarily nearly as bad a thing as it is frequently made out to be, as I explained here).

I’ve also read a lot about income migration from New York, so thought I’d throw that up. Here are the top ten places New York imports income from. Again, this data is in thousands and the cavet that this is not a total accumulated gain/loss applies:

Row Metro 2001 2002 2003 2004 2005 2006 2007 2008 2009 Total
1 Detroit-Warren-Livonia, MI -2,029 10,717 -11,214 -56 3,511 25,394 27,123 37,996 28,009 119,451
2 Chicago-Joliet-Naperville, IL-IN-WI 40,657 20,866 39,038 7,010 16,827 14,725 -8,977 19,113 -35,796 113,463
3 Pittsburgh, PA 38,314 17,140 5,005 6,092 12,418 6,001 6,277 12,322 -3,932 99,637
4 St. Louis, MO-IL 14,706 4,064 18,140 5,696 5,728 -14,400 9,811 16,568 26,365 86,678
5 Cleveland-Elyria-Mentor, OH 13,479 -1,808 1,402 21,158 -436 5,588 -887 11,425 10,627 60,548
6 Cincinnati-Middletown, OH-KY-IN 9,574 10,010 3,634 2,071 913 3,970 8,901 -1,125 4,694 42,642
7 Ann Arbor, MI 7,171 -1,867 -1,721 -4,718 6,062 2,824 12,527 20,105 -1,356 39,027
8 Lexington-Fayette, KY 2,068 946 2,262 1,327 2,365 16,798 11,436 1,965 -734 38,433
9 Ithaca, NY 3,794 2,392 4,754 -131 6,723 2,500 4,919 10,689 2,403 38,043
10 Kansas City, MO-KS 32,966 -2,018 -6,633 -2,593 -2,244 -2,827 8,343 8,852 1,645 35,491

Here’s the bottom ten:

Row Metro 2001 2002 2003 2004 2005 2006 2007 2008 2009 Total
1 Miami-Fort Lauderdale-Pompano Beach, FL -489,537 -637,986 -488,454 -656,464 -921,299 -749,266 -656,371 -578,875 -319,368 -5,497,620
2 Bridgeport-Stamford-Norwalk, CT -219,685 -333,277 -346,915 -383,158 -454,150 -370,490 -245,764 -209,871 -275,242 -2,838,552
3 Poughkeepsie-Newburgh-Middletown, NY -226,590 -283,873 -292,037 -258,070 -293,994 -262,774 -226,163 -188,396 -121,935 -2,153,832
4 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD -175,575 -196,775 -223,303 -247,439 -282,018 -270,743 -104,943 -133,336 -188,973 -1,823,105
5 Allentown-Bethlehem-Easton, PA-NJ -117,869 -150,286 -184,930 -189,782 -225,925 -230,863 -212,165 -139,780 -86,940 -1,538,540
6 Tampa-St. Petersburg-Clearwater, FL -141,225 -150,747 -158,583 -172,940 -252,097 -244,928 -157,668 -139,623 -53,674 -1,471,485
7 Orlando-Kissimmee-Sanford, FL -84,237 -124,094 -131,037 -179,391 -234,732 -223,908 -171,544 -102,654 -48,316 -1,299,913
8 Atlanta-Sandy Springs-Marietta, GA -65,596 -86,237 -80,997 -118,411 -171,883 -221,298 -246,739 -165,034 -83,497 -1,239,692
9 Los Angeles-Long Beach-Santa Ana, CA -123,833 -153,255 -117,068 -149,971 -150,245 -123,540 -125,267 -131,519 -3,222 -1,077,920
10 Charlotte-Gastonia-Rock Hill, NC-SC -18,899 -44,940 -46,497 -83,099 -118,675 -126,562 -179,474 -146,129 -69,665 -833,940

Miami says thanks. No two ways about it, New York metro is exporting a lot of income. For those who are interested, you can download the full matrix of net AGI flows for New York.

Like I said, there’s some seriously interesting stuff in here, and I plan to keep digging into the new data for quite a while, so stay tuned. For more of what you can do with this, click here.

9 Comments
Topics: Demographic Analysis
Cities: Chicago, Indianapolis, New York

9 Responses to “New Data Shows Slowing Migration in America”

  1. John says:

    On the final NYC table, I think it’s interesting to see how much exportation is going to suburban/exurban areas in the region. Seems sprawl is alive and well.

  2. Alon Levy says:

    John: the two suburban MSAs near the top for New York – Poughkeepsie-Newburgh and Fairfield County – are very different. The former has high growth by Northeastern standards: Orange County, New York grew about 10% over the decade. I fully expected it to be where it is on the chart. The latter is a favored quarter suburb with low growth – 4% over the decade, less than the New York MSA – so its position on the chart would indicate that it’s still getting a lot of high-income New Yorkers. This surprises me – companies are moving headquarters back to the city citing easier access to professional employees.

  3. Wad says:

    John, sprawl is alive and well because New York has both wealth and high costs, and those tend to push economic activities outward. But, remember the sub- in suburb means subordinate or secondary.

    A suburb conditionally needs an urb.

  4. John Morris says:

    It should also be remembered that NYC up untill very recently had resisted rezoning to allow infill, residential and office development in large parts of the Brooklyn and Queens waterfronts (actually areas that comprise lrge chunks of the city)

    Some, like Jane Jacobs thought this was agood thing. Any way you look at it positive or negative-one can’t deny that it severely limited infill growth. One can’t call a massive amount of development illegal and then act surprised when it doesn’t happen. This had a big inluence on the overall regional supply and demand.

  5. Matthew Hall says:

    The choices that people have even ambitious people have are radically different than even 7 or 8 years ago. While the robust housing market made it much easier to leave there were many more places that were clearly worth the move, as well. Today that isn’t clearly true. Not only have Phoenix, California and Florida collapsed, but even places like charlotte, raleigh, and atlanta are much less appealing than they were. Austin, houston, denver and dallas do continue to do well and probably still are attrative enough to lure those looking for new opportunities, but even in these cities many more are not moving without having jobs in place before they do. Taking off and making a whole new life from scratch is just not the option it was. There are just far fewer places to go, aside from the challenges of housing, if you are unhappy with your local options.

    Of course, the internet means that physical location isn’t important in the same ways it was. It pushes some to concentrate in certain locations to leverage their knowledge and connections, but it also allows people to maintain professional relationships remotely in ways they couldn’t before. Maybe that explains the continued high occupancy rates at hotels in many cities. People who can go to conferences and presentations to meet people, but then sustain those relationships from a distance because it is not clear to them what the advantages are of living in a new city. Then again, I meet many in their 20s and early 30s who say they are committed to staying where they are for the rest of their lives. It’s a new kind of localism that used to seem naive to me, but maybe it is a good strategy for unpredictable times when individual business connections and loyalties may matter more than in the past. Will one strategy come to dominate or will both co-exist?

  6. George Mattei says:

    I don’t think it would be surprising that lower-income residents would be shuttling between Indianapolis and Columbus. My experiences in the two places I lived, New Haven CT and Columbus OH, tell me that’s pretty common amongst shorter distances. My experiences are jsut that-experiences, and I don’t have hard data to back them up, but this is my impression:

    New Haven, as well as Bridgeport, had an active pipeline with New York. Not only did higher income folks tend to move back and forth at time (or commute and live in both places), but many lower income folks would move out to New Haven, usually to live with relatives and escape some of New York’s rougher neighborhoods. Keep in mind this was the early 90’s when both cities were much rougher than they are today.

    Columbus has a pretty robust movement pattern between the metro and Appalachian Ohio and Kentucky. Cincinnati has an even stronger one, from what I hear from relatives there. Lower income folks routinely move back and forth. They usually have family in both places, and seem to be moving for economic reasons-getting jobs or moving in with relatives during hard times.

    I suspect Indianapolis has a similar relationship with Chicago-its close enough to have significant family ties, and folks move back and forth to take advantage of whatever oportunity arises. I’m somewhat surprised that Milwaukee does not have a similar relationship, since its even closer.

  7. George Mattei says:

    Sorry, I meant Indianapolis and Chicago in my previous post-first sentence.

  8. Chris Barnett says:

    For different reasons than George, I find the Indy-Chicago data unsurprising. It fits the life-arc narrative that Aaron has previously proposed:

    Young person from suburb, small city, or rural area of Indiana goes off to one of the state universities, then finds the main opportunity is in cities. Being Hoosier, such a person might typically choose to make Indy his/her first city living experience. (Migration data supports this thesis.)

    Some number of those folks go on to move-up jobs in Chicagoland. (Migration data supports this thesis, too.) In the case of young people who grew up in the Indy metro, they may look to Chicago for a first job out of school.

    Upon reaching the point of settling down/settling into family life, a subset of Hoosier transplants might look at the costs in Chicagoland…dollar costs of living, and social cost of living some distance from close family…and may choose to move back to Indiana.

    Because the cost of living is significantly lower in Indianapolis, the Hoosier may make the trade of some salary for a better set of living conditions. Note that Indianapolis (city) vs. Chicago (city) cost of living is about 25% lower. High-end suburbs (Naperville and Carmel) have a difference of 10-15%. (Quick and dirty results from http://www.bestplaces.net/col)

    So it’s possible for the $80-120,000 income family to give up $5-10,000 in salary and live better (or at least as well) in the Indy metro than in Chicagoland. This is one possible driver of the data Aaron reports.

    Without seeing the age/household income medians and family status, it’s tough to know if this conjecture is supported by the data.

  9. Chris Barnett says:

    George, Indianapolis was directly in the path of the great northward migration to Chicago that occurred in the industrial era. US421 and US52 cross in Indy and are roughly parallel routes from here to NW Indiana/Chicagoland. (Both routes come here generally from Southern Indiana, Southern Ohio, Kentucky, West Virginia, and the Piedmont region.)

    It is unsurprising that there would be more family connections south from Chicago than north; the southern migrants didn’t generally have a reason to continue north to Milwaukee.

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