Children who grow up in rural counties are more likely to be married by their mid- to late 20s than those who are reared in the middle of our largest cities.
In general, the longer a child spends growing up in a rural community, the more likely he or she is to be married at age 26. Poor children who grow up in nine out of ten rural counties will marry at rates above the national average at age 26.
Meanwhile, children from poor families marry at rates above the national average in only 10 of the 57 densely populated counties at the center of metropolitan areas of more than a million people.
These findings come from a massive study of income tax records by Stanford University economist Raj Chetty and Harvard University economist Nathaniel Hendren. The two led an army of statisticians that has sought to isolate how growing up in each American county affects poor children.
Earlier this month, the Daily Yonder reported on Chetty’s and Hendren’s study of income. The two economists found that poor children growing up in rural communities are more likely to earn above the national average income at age 26 than poor children growing up in densely populated counties in cities of a million or more.
Chetty and Hendren identified “neighborhood effects” that raised income for children growing up in poor families — attributes of a community that help raise the future income of the people who grow up there. Places that were less segregated, had more “social capital” (more churches, civic organizations, lower crime rates, higher voting percentages) and better schools produced children who earned more by their mid- to late 20s.
Those same neighborhood effects appear to be at work when it comes to marriage.
(We are reporting the results for children who grow up in families in the bottom quartile in income. The marriage rates for children who come from rich families follow the same pattern. Also, Chetty and Hendred said the results are unchanged if marriage rates were checked at age 30 instead of 26.)
Chetty’s and Hendren’s study uncovers a cultural, economic and, in the end, political divide in this country. The communities that are good for children in terms of income aren’t the places receptive to the new economy. The counties that promote marriage aren’t the places gaining people or jobs. The areas good for poor children are often the communities that are losing population, employment and income.
And the places best for poor children and for marriage are considerably more Republican than the Democratic centers of job creation and innovation.
The map on this page shows the stark urban-suburban-rural divide in marriage rates. Orange counties are urban; each year spent in these counties diminishes the chances children growing up in poor families will be married at 26. Blue counties are urban areas where poor children grow up to marry at rates above the national average. (Note how orange, central city counties are often surrounded by blue, suburban counties.)
Red counties are rural areas where children growing up decrease their chances of being married at rates above the national average at 26. Each year spent growing up in a green rural county increases the chances that children will marry by the time they are 26.
Gray counties had too few examples for researchers to reach any conclusion.
Chetty and Hendren have done a lot of work trying to isolate the community factors that diminish the chances that a young person will earn income above the national average at the time he or she is 26 — such as high levels of income inequality and racial segregation; low levels of social capital; and poor schooling. They have done less work on the neighborhood effects that encourage marriage.
In an email, Hendren wrote that his early analysis found that places with more two-parent families and a higher rate of church-going could be found in those counties that had children who were more likely to marry at age 26. (And remember, the results are the same for children raised in well-to-do families.)
The more rural the county, the more likely it is that it will have community effects that lead poor children raised there to marry by the time they are 26:
The political divide is more pronounced when it comes to marriage. Clinton won the counties with neighborhood effects that result in lower than average marriage rates, 59% to 36%. Trump won the half of the country living in communities where children from poor families are more likely to marry by 56% to 37%.
Chetty and Hendren hope their research will spur “place-focused approaches to improving economic opportunity.” Poor families could benefit their children with a “move to opportunity,” relocating to communities with beneficial neighborhood effects. And governments and nonprofits could make investments in communities that would enhance those neighborhood effects that have been shown to be so beneficial, such as reducing segregation and increasing social capital.
Writers such as author and CNN commentator J.D. Vance, author of Hillbilly Elegy, look at rural areas and see dysfunction and decline. Citing Chetty, Vance wrote that in Appalachia “poor kids really struggled.”
What Chetty and Hendren find, however, is that much of rural America isn’t a source of individual pathology but a place where we can all witness the beneficial impacts of community.
Appalachia may be largely poor, as Vance writes, but three quarters of the rural counties in the mountains of Kentucky and West Virginia have communities that help children in poor families earn and marry at rates above the national average as young adults — well above the cities that have booming economies.
Most of these people who grow up in rural communities move to cities to earn their incomes. The jobs simply aren’t there in many rural areas.
But Chetty and Hendren find a “generic pattern” in their data: “(U)rban areas tend to exhibit lower levels of intergenerational mobility than rural areas on average.” Kids growing up poor in rural areas are more likely to climb the income ladder than kids growing up in cities — not despite their rural communities, but those places were their homes.
Click on individual counties to see data. Or view the map via Google Maps.