What Happened to Migration in 2014?
American Community Survey Edition
Last July, I covered the Current Population Survey statistics on migration in 2014. The CPS is the first look we get at migration in the previous year. It has its perks, but also has some shortcomings. Luckily, there are other sources, most notably the American Community Survey (ACS)and the IRS’ Statistics of Income. New IRS data will be released on September 30, so I’ll cover that source later. But the 2014 ACS data was released today.
In 2014, gross migration remains about the same as it was in 2013. However, several sub-groups did see changes. The education gap in migration rates between the most and the least educated widened to the highest level since the ACS began tracking, mostly as those without high-school degrees migrated less. Retirees and near-retirees migrated somewhat more. Migration rates for Hispanics remained at historic lows, while rates for multiracial individuals remained far above most other groups. Middle-class migration rates continued to show some signs of recovery from the recession-year declines.
Migration in 2014
Comparing the Sources
The red and orange lines reflect ACS migration rates. For 2014, same-state intercounty migration rose. This may reflect a return to long-standing suburbanization trends. Suburbanization slowed down a bit during the recession, but it seems to be making a real comeback. But my headline number, interstate migration, is flat for the third year in a row. Now admittedly, better flat than down, but as yet there’s no clear sign from the ACS that migration is recovering. (Ignore the IRS spike for now, I’ll cover that later this month when we get another year of data).
ACS Interstate migration has been flat for 3 years.
As usual, ACS estimates a much higher migration rate than CPS. That’s par for the course, and the gap is about the same it has been for several years. Notably, CPS, while offering a lower figure, shows the same essentially flat trend for the last 3 years. This new migration rate could potentially be a “new normal” for the nation. We’ll see.
Migration in 2014
Migration By Age is Stable
The ACS confirms the trend we see in CPS and IRS data in terms of migration rates by age. Notably, migration rates by age have barely budged since 2006. That’s odd. When overall trends change but subcomponents don’t, it suggests the overall trend may be merely due to a composition effect.
Declining migration may just reflect an aging population.
If people are getting older, they move less. Even if a given age group has the same rate as in the past, if low-rate groups are a bigger share of the population, we would move less. However, that aging population would still imply diminished dynamism in the labor market and a more rigid economic order. Whether falling migration is due to aging or something else, it’s still not a positive indicator.
Migration in 2014
Widening Education Gap
The chart above shows the gross interstate migration rate by educational attainment for those over 25 from 2005 to 2014. From 2005 to 2010, most groups basically moved together, and declined. But after 2010, there’s a divergence as more highly educated groups experience rising migration, while the less educated become less mobile.
The rising education gap in migration is cause for concern.
Migration is a major pathway out of poverty, especially for children in low-income families. I’ve demonstrated the pro-mobility mathematics of migration before, so I won’t run the numbers again here. But if we see fewer less-educated individuals migrating, then more of those peoples’ kids are likely to be stuck in areas of concentrated poverty. While this chart doesn’t strictly show income but rather shows education, education is a key predictor of income, and parental education is also a strong predictor of children’s future incomes. Mobility is rising for the skilled and the educated, even as the unskilled and uneducated are increasingly stuck where they are.
Migration in 2014
Changing National Makeup May Change Migration
The above chart shows gross migration rates by race or ethnic background. There are a few trends really worth noting. First, while migration rates were formerly higher for blacks than whites, they are now lower. And even as white and Asian migration rates have shown some recovery, black migration rates have been stagnant. This follows with the education gap I pointed out earlier.
Hispanic and multiracial migrants show two different futures.
But there may be a more interesting story here. There are at least two groups that are consistent outliers in terms of migration rate that we also know are going to be a growing share of the U.S.’ population in the future: Hispanics and multiracial individuals. Hispanics have persistently lower rates of migration, multiracial individuals have persistently higher. The gap between these two groups has widened over the last several years.
As the U.S. becomes more Hispanic, it is possible that the lower propensity to migrate among Hispanics will change, and they’ll “assimilate” to American migration likelihoods. Maybe. But it’s also possible that existing migration patterns will remain about what they’ve been for a decade now, and a rising Hispanic share of the population will lead to a lower national interstate migration rate. Not because any given group of people are moving less, but because the composition of the nation has changed.
On the other hand, other fast-growing groups in the U.S., like multiracial individuals and Asians, have persistently higher migration rates than the largest current groups (whites and blacks). As multiracial and Asian individuals make up a larger share of the population, migration rates can be expected to rise. So in terms of forecasting the future of domestic migration, a key question is the ratio of Asian to Hispanic immigrants and emigrants, as well as natural fertility differences in both groups, and also the rate at which Americans of different races get married and have kids. This is yet another example of how international and domestic migration are linked together in little-studied ways.
Migration in 2014
“Gainer” and “Loser” States
The above maps show net migration rates by state in 2013 and 2014, and the year-over-year change. The trends in 2014 are pretty similar to in 2013 in most cases, however, there are some changes.
But I want to distinguish between large changes and significant changes. Alaska, Delaware, DC, Wyoming, and Idaho all had fairly large changes. But they weren’t all significant. The ACS provides not just estimates, but margins of error. I estimated the margins of error for 2013 and 2014, and then identified states where the 2014 net migration rate estimate was outside the 2013 margin of error.
Seven states had significant changes in net migration rates.
Arkansas, New Mexico, and Louisiana all saw significant improvements: Arkansas from -0.22% to 0.33%, Louisiana from -0.17% to 0.26%, and New Mexico from -0.91% to -0.06%. Some states like Alaska or the District of Columbia had larger changes, but those changes had wide error bands due to small populations or small aggregate flows.
Meanwhile, Illinois’ net migration rate fell from -0.64% to -0.89%, Missouri’s from 0.36% to -0.2%, New York’s from -0.67% to -0.85%, and Virginia’s from 0.37% to -0.39%.
I have not explored what exactly happened to drive these changes (for Virginia, for example, I suspect DC and Maryland held onto more metro-area migrants than in the past). But many states didn’t change. Net migration isn’t perfectly stable, but we don’t tend to see huge regional swings on a regular basis. A few states experience significant year-over-year changes each year.
Overall, migration in 2014 remained fairly similar. The gross migration rate was essentially unchanged, even as several groups saw changed rates. Several concerning gaps, such as the education and racial migration gaps, continued to widen. On the other hand, other gaps, like the income-gap for migration, appeared to narrow. It isn’t immediately clear what’s driving all of these trends. However, as the ACS is around longer, it is becoming more and more useful as a tool to analyze change over time.
Migration in 2014
More Charts! More Graphs! No Explanations!
See my last post, on migration by state of birth.
Start my series on migration from the beginning.
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I’m a graduate of the George Washington University’s Elliott School with an MA in International Trade and Investment Policy, and an economist at USDA’s Foreign Agricultural Service. I like to learn about migration, the cotton industry, airplanes, trade policy, space, Africa, and faith.
My posts are not endorsed by and do not in any way represent the opinions of the United States government or any branch, department, agency, or division of it. My writing represents exclusively my own opinions. I did not receive any financial support or remuneration from any party for this research. More’s the pity.
