[raw shortcodes=1]
Stories about young people these days often focus on the apartment-renting, third-wave coffee-drinking, bike-to-working urban millennial.
Just read the headlines: “30 photos show the extreme lengths millenials will go to to live in cities instead of suburbs”; “Millennials are Spending More on Coffee than on Saving for Retirement”; “Millennials choosing buses and bikes over Buicks.”
But are millennials really so different from their parents? Their grandparents?
“Young adults have been going to the cities since the ’50s in droves,” said Richelle Winkler, associate professor of sociology and demography at Michigan Technological University. As they grow up, pair up, get married and have kids, they tend to move away to the suburbs — or farther away.
It happened in the ’50s and ’60s, when members of the Silent Generation were young. It happened in the ’70s into the ’80s, with the Baby Boomers, and it happened with Gen-X in the late ’80s and ’90s.
Moving to the city
After graduating from college at the University of North Dakota in the late ’90s, twentysomethings Amy Baldwin and her husband — boyfriend, at the time — moved about 320 miles southeast to St. Paul, where she started graduate school at Hamline University and he got a job working at the University of Minnesota Medical Center.
The pair illustrate a common trend: Between 2000 and 2010, Hennepin and Ramsey counties saw a net gain of about 55,000 young people, ages 20-29, according to data from the University of Wisconsin’s Applied Population Laboratory, which compiles statistics on migration by age group for counties throughout the U.S.
As Winkler, who worked on the Population Lab adata noted, this has been happening among this age group since at least the 1950s, as young people left rural areas and small towns or away from where they went to college for opportunity in bigger cities.
If there is an exception, she said, it’s the ’70s, when a back-to-the-land movement paired with growth in manufacturing jobs in non-urban areas led larger number of young people to move to rural areas, prompting a sort of rural renaissance.
Millennials, Winkler said, may be moving to cities in larger numbers than their parents in the first place, but history indicates that just as young people move to cities in large numbers, they also tend to move away as they get older.
Moving to the suburbs
Baldwin loved St. Paul — its walkability, the amenities. But by the mid-2000s, she and her now about-to-be husband were looking to buy a home — something affordable that could accommodate the family they were planning to eventually have.
“During the housing bubble — the mid-2000s — for what we could buy in St. Paul, which we loved, there was just nothing, it felt like at the time,” she said.
Baldwin’s job moved out to the western suburbs, and so, around age 30, did the couple. They moved to Maple Grove, where they lived for about seven years, making them illustrative of another trend: as people get to about 30, around the time many start having kids, there’s movement out of urban areas. Minneapolis and St. Paul are no exception.
“A lot of that is suburbanization, once they have kids, leaving the county where the inner-city is located, maybe they’re still in the metro area but they’re moving to Anoka County or something like that,” Winkler said.
(Since the data from the University of Wisconsin is county-level, Baldwin’s move to Maple Grove in Hennepin County from St. Paul in Ramsey County wouldn’t appear as an urban-to-suburban move in the numbers.)
These trends are easy to see in a chart. Hennepin and Ramsey counties gain net population in the 15 -to-24 age range — precisely when the suburban metro counties, Anoka, Carver, Dakota, Scott and Washington, lose net population.
Once people start approaching 30, though, that trend reverses, with the suburbs gaining net population while the urban counties lose it.
Similarly, while Hennepin and Ramsey counties lose net population in the under-14 age set, suburban metro counties see gains in this group, as children move out to the ‘burbs with their parents.
But the suburbs aren’t the only part of the state gaining population among the 30-something set.
After their first child was born, Baldwin and her husband started thinking maybe Maple Grove wasn’t where they’d like their kids to grow up. Having grown up themselves in rural areas, they liked the idea of living in a smaller community.
“Is this the quality of life, the pace of life we really wanted?” she remembered asking herself, mindful that once the kids hit school age it would be more difficult to move.
They made a list of communities they might be interested in. When she landed a job in community and economic development in Fergus Falls, they decided to make the move. He works remotely for a software company in the Twin Cities. This makes them illustrative of another trend: net population gain among 30-somethings for some Minnesota counties outside the metro area.
Fergus Falls is the county seat of Otter Tail County. The county has net population loss in the 15 to 24 and 25 to 29 age groups, but starts to see modest net gains in migrants over 30 (it also saw net gains over the decade in children under age 14).
Winkler and her colleagues classify Otter Tail county and many of its lake country neighbors as a retirement county. With natural amenities, like lakes, it loses emerging and young adults. It gains young families, yes, but its biggest net gains are actually among those around retirement age, when many seek a different lifestyle or move to their lake homes permanently.
But the degree to which non-metro counties are able to attract migrants of different ages varies considerably.
Delaying Milestones
It’s not really age, per se, that drives a lot of these migration patterns. It’s the arc people’s lives follow, which, of course, is related to age. Young adults move to where there’s opportunity. People with kids move toward more space and good schools. Retirees move to downsize, or to be closer to health care and their kids.
The Wisconsin dataset doesn’t include data recent enough to say conclusively what millennials, as a generation, will do. But Winkler speculated that if millennials are to be any different, it’s likely to be because they’re delaying milestones like marriage and home buying and childbirth — and therefore delaying migration patterns.
State Demographer Susan Brower says Minnesota data seem to show millennials following well-worn life patterns — just at slower rates.
“When I’ve looked this over, comparing millennials to Baby Boomers, they’re still making the transition to homeownership, it’s just at a slower rate,” she said. They also fit into long-term trends toward delaying marriage and having kids later, she said.
Explore the data
The data on net migration by age group for all 87 of Minnesota’s counties are in the table below. You can click on the column headers to re-sort the table or use the search box to look for a specific county.
Additionally, to help visualize some of the migration patterns that hold true across counties, you can select a classification from the drop-down menu. The classifications, which are from the Applied Population Laboratory, are:
- Destination: Destination counties, which tend to be close to metro areas, rich in natural amenities, or both, experience less loss of young adults than other types of counties.
- Group quarters: Counties with institutional facilities like prisons and military facilities.
- Retirement: Counties that see net loss of emerging and young adults, but are destinations for young families and retirees.
- Rural exodus: Counties losing young people and not attracting enough family-age people and retirees to replace them.
- University influence: Counties with university presences, which bring influxes of population in the 15–24 age range, followed by net losses as students graduate.
- Youth migration: Like rural exodus, these counties experience net losses of emerging and young adults, but show more ability to attract family and retirement-age people.
- Metros: Counties whose migration patterns are influenced by the presenece of an urban area.
MP.highcharts.makeChart(‘.chart-hennmigration’, $.extend(true, {}, MP.highcharts.columnOptions,{
legend: { enabled: true },
xAxis: {
categories: [‘0-14′, ’15-24′, ’25-29′, ’30-54′, ’55-74′, ’75+’],
title: { text: ‘Age’, enabled: true }
},
yAxis: {
min: -50,
title: { text: ‘Net migrants per 100 residents’},
plotLines: [
{
value: 0,
color: ‘#ABABAB’,
width: 1,
}
]
},
tooltip: {
formatter: function(){
var sign = “”;
if (this.y > 0) {sign = “+”};
return ‘ ‘ + this.series.name + ‘
‘ + sign + MP.formatters.number(this.y,1) + ‘ net migrants per 100
residents in the ‘ + this.x + ‘ age group’;
}
},
series: [
{
name: ‘1950s’,
data: [-.05, 31.2, 36.2, -0.6, -2.4, -2]
},
{
name: ‘1960s’,
data: [-4.4, 12.1, 28.9, -3.6, -6.4, 0.7]
},
{
name: ‘1970s’,
data: [-13.2, -3.1, 14, -13.3, -12.7, -0.5]
},
{
name: ‘1980s’,
data: [-0.9, 10.9, 32.5, -2.7, -8.4, 1.2]
},
{
name: ‘1990s’,
data: [-4.9, 16.3, 58.4, -6.1, -13.5, 1.5]
},
{
name: ‘2000s’,
data: [-7.6, 3.9, 42.9, -8.5, -11.9, -2.7]
},
]
}));
MP.highcharts.makeChart(‘.chart-ramseymigration’, $.extend(true, {}, MP.highcharts.columnOptions,{
legend: { enabled: true },
xAxis: {
categories: [‘0-14′, ’15-24′, ’25-29′, ’30-54′, ’55-74′, ’75+’],
title: { text: ‘Age’, enabled: true }
},
yAxis: {
min: -50,
title: { text: ‘Net migrants per 100 residents’},
plotLines: [
{
value: 0,
color: ‘#ABABAB’,
width: 1,
}
]
},
tooltip: {
formatter: function(){
var sign = “”;
if (this.y > 0) {sign = “+”};
return ‘ ‘ + this.series.name + ‘
‘ + sign + MP.formatters.number(this.y,1) + ‘ net migrants per 100
residents in the ‘ + this.x + ‘ age group’;
}
},
series: [
{
name: ‘1950s’,
data: [-3.7, 15.2, 14, -4.8, -4, -1.9]
},
{
name: ‘1960s’,
data: [-6.7, 6.3, 17, -4.4, -3.5, 3.1]
},
{
name: ‘1970s’,
data: [-16.5, -1.7, 2.9, -17.2, -10.6, -0.7]
},
{
name: ‘1980s’,
data: [-5.2, 11.1, 13.2, -8.7, -7.3, 0.6]
},
{
name: ‘1990s’,
data: [-6.1, 20.4, 29.3, -11.4, -11.4, -2.3]
},
{
name: ‘2000s’,
data: [-10.1, 10.5, 15, -15.5, -9.5, -3.1]
},
]
}));
MP.highcharts.makeChart(‘.chart-metromigration’, $.extend(true, {}, MP.highcharts.columnOptions,{
legend: { enabled: true },
xAxis: {
categories: [‘0-14′, ’15-24′, ’25-29′, ’30-54′, ’55-74′, ’75+’],
title: { text: ‘Age’, enabled: true }
},
yAxis: {
min: -80,
title: { text: ‘Net migrants per 100 residents’},
plotLines: [
{
value: 0,
color: ‘#ABABAB’,
width: 1,
}
]
},
tooltip: {
formatter: function(){
var sign = “”;
if (this.y > 0) {sign = “+”};
return ‘ ‘ + this.series.name + ‘
‘ + sign + MP.formatters.number(this.y,1) + ‘ net migrants per 100
residents in the ‘ + this.x + ‘ age group’;
}
},
series: [
{
name: ‘Non-urban metro counties’,
data: [71.3, -76, 64.5, 106.3, 5.1, 141.7]
},
{
name: ‘Hennepin’,
data: [-7.6, 3.9, 42.9, -8.5, -11.9, -2.7]
},
{
name: ‘Ramsey’,
data: [-10.1, 10.5, 15, -15.5, -9.5, -3.1]
} ]
}));
var migrationData = [[“Aitkin”, “Retirement”, 11.1, -26.3, -34.5, 22.9, 36.5, -18.6], [“Anoka”, “Twin Cities metro”, 6.6, -15.1, 1.1, 7.5, -4.6, 3.5], [“Becker”, “Retirement”, 11.3, -23.4, -23.3, 17.6, 14.1, 3], [“Beltrami”, “University influence”, -1.6, 29, -19.6, -4.1, 12.7, 16.5], [“Benton”, “St. Cloud metro”, -3.8, 8.8, 25.3, -4.6, 4.5, 72.4], [“Big Stone”, “Rural exodus”, 9, -39.3, -41.5, 6.1, 5.2, 4.3], [“Blue Earth”, “University influence”, 0.3, 153.8, -13.6, -21.9, 3.7, 15.8], [“Brown”, “Youth migration”, 6.1, -13.2, -37.3, -4.5, 0.3, 15.5], [“Carlton”, “Duluth metro”, 17.8, -10.6, -10.4, 19.7, 7.2, 11.4], [“Carver”, “Twin Cities metro”, 23.7, -17.5, 4, 31.8, 2.3, 26.8], [“Cass”, “Retirement”, 5.1, -27.6, -31.2, 22.3, 22.2, -23.1], [“Chippewa”, “Rural exodus”, 6.3, -24.1, -25.4, 0.8, -2.8, 0.2], [“Chisago”, “Twin Cities metro”, 14.8, -10.1, 4.1, 37.8, 22.5, 47.8], [“Clay”, “Fargo metro”, 13, 70.2, -22.8, -3.7, 0.8, 0], [“Clearwater”, “Retirement”, 8.3, -22.7, -35.5, 12.4, 9.6, -1.2], [“Cook”, “Youth migration”, 2.2, -25.8, -16.1, 13.8, 7.8, -13.5], [“Cottonwood”, “Rural exodus”, 9.6, -25.7, -35.4, 7.1, 1.7, -2.9], [“Crow Wing”, “Destination”, 11, -8.3, -10.4, 17.4, 22, -4.5], [“Dakota”, “Twin Cities metro”, 6.1, -17.8, 12.1, 6.5, -4.7, 22.1], [“Dodge”, “Rochester metro”, 17.4, -21, -17.7, 16.5, 0.8, -0.2], [“Douglas”, “Youth migration”, 13.1, -4.1, -19.3, 11.2, 15.8, 7.7], [“Faribault”, “Rural exodus”, 5.1, -29.4, -45.9, 3.5, -0.1, -9.8], [“Fillmore”, “Rural exodus”, 7.4, -30.1, -29.1, 6.7, 3.1, 3.9], [“Freeborn”, “Youth migration”, -0.6, -21.7, -26.2, 0.8, -0.1, 1.1], [“Goodhue”, “Retirement”, 9.4, -21.8, -24.6, 9.8, 3.8, 20.4], [“Grant”, “Retirement”, 8.6, -32.7, -26.5, 9.7, 12.1, -5.2], [“Hennepin”, “Twin Cities metro”, -7.6, 3.9, 42.9, -8.5, -11.9, -2.7], [“Houston”, “LaCrosse metro”, 8.3, -32.7, -30.9, 3.5, -0.1, 1], [“Hubbard”, “Retirement”, 17.4, -22, -25.8, 25.3, 24.2, -13.7], [“Isanti”, “Twin Cities metro”, 19.4, -9.5, -3.6, 23.9, 6.7, 31], [“Itasca”, “Retirement”, 13.4, -19.7, -36.3, 12.6, 10.1, -1], [“Jackson”, “Rural exodus”, 15.7, -29.3, -38.1, -0.4, -5.9, -14.5], [“Kanabec”, “Retirement”, 15.4, -23.7, -25.2, 16.7, 15.3, -9.3], [“Kandiyohi”, “Youth migration”, 0.3, -6.3, -25.6, -0.3, 1.6, 3.4], [“Kittson”, “Rural exodus”, 4.3, -44.4, -44.9, -1.3, 0.9, 4.3], [“Koochiching”, “Rural exodus”, 7.1, -27.4, -38.7, 3, 2.1, -8.3], [“Lac qui Parle”, “Rural exodus”, 12.6, -42, -48.5, 7.4, 2.6, -1], [“Lake”, “Retirement”, 4.5, -23.9, -25.6, 9.3, 8.4, 3.8], [“Lake of the Woods”, “Rural exodus”, 13.4, -45.7, -45.4, 5, -0.4, -18.3], [“Le Sueur”, “Rural exodus”, 18.3, -24.4, -14.4, 17.3, 3.1, -11.3], [“Lincoln”, “Rural exodus”, 3.9, -36, -34.7, 2.2, 4.6, 10.7], [“Lyon”, “University influence”, 2.3, 21.8, -17.7, -10.9, -5.5, 1], [“McLeod”, “Youth migration”, 3, -22.3, -11.1, 4.5, 1.8, 6.2], [“Mahnomen”, “Retirement”, 9.7, -26.3, -27.5, 14.4, 6.1, -23.3], [“Marshall”, “Rural exodus”, 11.1, -34, -35.3, 4.4, -6.3, -21.8], [“Martin”, “Rural exodus”, 8.6, -27.6, -32.1, 4.2, 0.3, 2.8], [“Meeker”, “Retirement”, 10.7, -25.6, -28.6, 9.8, 4.7, -1.9], [“Mille Lacs”, “Destination”, 14.2, -7.9, -11.3, 26.2, 15.6, 13], [“Morrison”, “Retirement”, 4.8, -22.2, -23.9, 10.9, 7.8, -0.8], [“Mower”, “Youth migration”, 2.9, -11.3, -15.2, 3.5, -3, -7.7], [“Murray”, “Rural exodus”, 14.9, -33.8, -39.3, 7.2, 3.7, -6], [“Nicollet”, “University influence”, 7, 48.6, -24.7, -7.3, -0.5, 7.2], [“Nobles”, “Youth migration”, -2.9, -5.4, -8.3, 1.1, -4.5, -15.1], [“Norman”, “Youth migration”, 8.3, -37.7, -39.2, 3.8, -1.3, 8.5], [“Olmsted”, “Rochester metro”, 2.5, -9.7, 33.2, 8.2, 1.4, 13.1], [“Otter Tail”, “Retirement”, 10.1, -26, -34.2, 9.7, 12.4, -0.5], [“Pennington”, “Youth migration”, 7.2, -1.6, -23.7, 2.8, -2.9, 8.8], [“Pine”, “Group Quarters”, 16, -16.1, -5.5, 22.1, 16.8, -13.5], [“Pipestone”, “Rural exodus”, 7.3, -25.5, -31.3, 6.2, -0.2, 6.6], [“Polk”, “Grand Forks metro”, 7.2, -0.4, -32.6, 2.6, 1.3, 7.1], [“Pope”, “Retirement”, 12.4, -32.8, -29.4, 11.2, 13.6, -4], [“Ramsey”, “Twin Cities metro”, -10.1, 10.5, 15, -15.5, -9.5, -3.1], [“Red Lake”, “Rural exodus”, 14.8, -36.2, -31.3, 8.8, 1.3, -32.9], [“Redwood”, “Rural exodus”, 9.7, -28.5, -34.8, 1.9, 0.8, 3.1], [“Renville”, “Rural exodus”, -3, -34.6, -34.5, 2.2, 0.6, -2.3], [“Rice”, “University influence”, 12.1, 47.1, -32.2, 0.1, 4.1, 12.9], [“Rock”, “Rural exodus”, 9.4, -29.8, -33.3, 9.5, 3.2, 14.7], [“Roseau”, “Rural exodus”, 2.3, -36.8, -37.7, 1.1, -2, 0.3], [“St. Louis”, “Duluth metro”, 3.2, 26.4, -24, -4.5, -0.5, -2.4], [“Scott”, “Twin Cities metro”, 16.8, -9.4, 44.3, 41.6, 13.9, 52.9], [“Sherburne”, “Twin Cities metro”, 21.1, 3.9, 19.5, 29.9, 12.8, 66.9], [“Sibley”, “Rural exodus”, 9.7, -32.1, -27, 5.7, -0.5, -10.4], [“Stearns”, “St. Cloud metro”, 7.2, 53.3, -18.2, -8.1, 5.5, 0.5], [“Steele”, “Youth migration”, 5.8, -20.3, -10.2, 7.4, 2, 11.8], [“Stevens”, “University influence”, 7.2, 89.5, -56, -25, -3.9, -7.2], [“Swift”, “Rural exodus”, -5.1, -27.8, -35.9, -24.8, -9.3, -7.9], [“Todd”, “Retirement”, 13.7, -20.6, -39.3, 9.5, 8.4, -17.2], [“Traverse”, “Rural exodus”, 3.8, -40.1, -47.9, 0.5, 3.6, -9.3], [“Wabasha”, “Rochester metro”, 6.8, -30.2, -31.8, 7.7, 3.6, -5.7], [“Wadena”, “Retirement”, 2.2, -21, -31.1, 6.3, 12.5, 24.8], [“Waseca”, “Group Quarters”, 1.9, -25.2, -7.6, -4.4, -4.4, 6.3], [“Washington”, “Twin Cities metro”, 18.1, -16.2, 3, 18.9, -1.8, 36.4], [“Watonwan”, “Rural exodus”, -3, -25.9, -32.3, -0.4, -1.4, -3.8], [“Wilkin”, “Rural exodus”, 6.7, -35.1, -40.1, -1.9, -2.9, 22], [“Winona”, “University influence”, -0.2, 99.7, -41.2, -21.5, -0.4, -1.2], [“Wright”, “Twin Cities metro”, 20, -11.9, 19.4, 40.3, 13, 29], [“Yellow Medicine”, “Rural exodus”, 7, -23.6, -32.7, 3.7, -1.3, -12.1]]
var tableColumns = $.extend(true, {}, { 0: { sTitle: ‘County’ }, 1: { visible: false }, 2: { sTitle: ‘Age 0-14’, bSearchable: false, sClass: ‘numeral’, mRender: function(data, type, full) { return MP.formatters.number(parseFloat(data),1); } }, 3: { sTitle: ‘Age 15-24’, bSearchable: false, sClass: ‘numeral’, mRender: function(data, type, full) { return MP.formatters.number(parseFloat(data),1); } }, 4: { sTitle: ‘Age 25-29’, bSearchable: false, sClass: ‘numeral’, mRender: function(data, type, full) { return MP.formatters.number(parseFloat(data),1); } }, 5: { sTitle: ‘Age 30–54’, bSearchable: false, sClass: ‘numeral’, mRender: function(data, type, full) { return MP.formatters.number(parseFloat(data),1); } }, 6: { sTitle: ‘Age 55-74’, bSearchable: false, sClass: ‘numeral’, mRender: function(data, type, full) { return MP.formatters.number(parseFloat(data),1); } }, 7: { sTitle: ‘Age 75+’, bSearchable: false, sClass: ‘numeral’, mRender: function(data, type, full) { return MP.formatters.number(parseFloat(data),1); } }
});
var options = $.extend(true, {}, { aaData: migrationData, aoColumns: _.values(tableColumns), columnDefs: [ { targets: [2,3,4,5,6,7], createdCell: function (td, cellData, rowData, row, col) { if ( cellData
Housing stock
It’s also about what housing is available. Where I live in minneapolis, there used to be a lot of empty nesters & few young families. Now the proportions have changed, young families have moved in as a bunch of homes that hadn’t changed hands in decades came on the market. I’d expect to see that ripple outward; which seems to be happening in Richfield & East Bloomington.
Urban Housing
The problem I have with articles like this is it talks about the suburban move as a inevitability and a prerequisite for families and good schools. Most people I know want urban housing but it’s too expensive due to housing regulations. It’s shouldn’t be a surprise that people move out of urban areas when enact laws that inflate housing prices.
Burying the lede
The best section in this article was the penultimate one, which explained the whole situation.
Yes, it’s true, millennials are still moving to the suburbs in middle age like their parents. But they are making that move *later* and that makes a huge difference.
For example, if we assume for the sake of simplicity that the 320 million people in America are evenly distributed between the ages of 0-80, then there are 4 million people of every age. If millennials all stayed in urban neighborhoods for just two years longer than their parents, that would represent a growth of our cities by 8 million people; a huge shift.
There is plenty of evidence that younger people are living in cities at higher rates than people in the cohorts older than them (http://cityobservatory.org/are-the-young-leaving-cities/). The shift in location preferences is real, even if young people still broadly and belatedly follow the same patterns.
Yes, but its not evenly distributed
Wouldn’t the trend reverse as the following demographic generations, with their smaller numbers (the real world situation), take their place? Is it worth the logistical effort to realign planning goals for those 2 years? Its the same thought I have as I see the explosion of senior housing, built for aging boomers, that will be empty in 10 years.
Perhaps, but…
… the evidence, as far as we can see, is that younger ages still prefer urban living more than earlier cohorts did at their age. That goes for younger millennials vs older millennials, and whatever else the post 2000 generation is called.
It’s impossible to know for sure if there will be some kind of backlash against urban living at some point in time, but so far, the trend of greater urban preference seems to be continuing. Additionally, a lot of the trends that are credited with driving suburbanization (segregation, crime, expanding road infrastructure, cheap credit for homebuilding) have either slowed or reversed.
Trending
As the piece suggests similarly to those generations before them. Everyone likes to think they’re something new under the sun its true, but in my admittedly anectdotal experience as a nearing 40 year old parent of two youngsters, I can say that city living was great when you have time and opportunity to enjoy it. My circle pushed children to our 30’s and we all professed our well intentioned desires to raise our kids amidst the bustle and excitement of our urban homes. 10 years later, I haven’t a single aquaintence, much less close friend, that hasn’t moved to the suburbs. Maybe millenials and their followers will be the sea change we thought we were, but somehow, I doubt it.