Trump's hidden asset: rural -- but not poor -- voters
Americans who voted for Donald Trump are often framed as backing him chiefly because of their precarious economic status in an era of downward mobility. Yet new research from the Urban Institute reveals a more complex picture, finding that sizable pockets of support for the real estate mogul came from people who are better off.
In fact, the U.S. counties with the highest credit scores largely went for Trump rather than his Democratic rival, Hillary Clinton, the study found. Credit scores broadly reflect on an individual’s economic reality, such as the ability to pay bills on time and how easily one has access to credit.
Among the 55 counties with residents with the highest average credit scores -- at 720 or higher -- Trump won 51, while Clinton won just four, the centrist think-tank found. By contrast, Clinton won all 11 counties that had the lowest average credit scores, or those below 600, which is considered subprime.
Trump received a huge voter boost from rural U.S. voters, who data show were more likely to vote for the GOP candidate if they lived outside of a city. About 7 of 10 voters who live far from an metropolitan area and in a region with fewer than 2,500 people voted for Trump, National Public Radio found in an analysis of rural and urban voters. Rural Americans may have lower median annual income than city dwellers as a whole, but they also are more likely to enjoy the hallmarks of financial stability, such as homeownership and lower poverty rates.
“You don’t necessarily see the picture of struggle that you would have expected going into this,” said Urban Institute senior research associate Diana Elliott, who specializes in financial security and economic mobility. “Most of our counties that are doing quite well, with the top credit scores, are rural communities.”
That doesn’t mean that many Trump supporters aren’t under serious finanial duress, Elliott stressed. Instead, the data suggest that their current financial situation is more favorable than commonly thought.
Stark County, Ohio, which turned out for Trump on Nov. 8, is the type of Rust Belt region regarded as a crucial political battleground leading up to the election. Located at the heart of a swing state, Stark County includes Canton, the home of steel manufacturer TimkenSteel Corp. Voters there expressed support for Trump’s message of reviving manufacturing jobs and boosting th region’s economic growth.
Yet the population of Stark County -- which is mostly white and working class -- is “doing slightly better than the nation as a whole,” Elliott said. “They have a lower percentage of residents with subprime credit scores. The unemployment rate is on par with the national average.”
Curious about how Stark County residents have fared financially in recent years, Elliott looked at credit scores for 2012 to 2016, and found that their scores improved during Obama’s last term. “There aren’t objective measures that show they are struggling more in 2016 than in 2012.”
Credit scores tend to align with race, with white Americans more likely to have a higher credit score than black Americans. More financially secure voters tended to cast their ballots for Trump, which aligns with white voters, with Urban Institute concluding that “race was an important predictor in this election.”
Elliott’s findings are backed up by new Census research into rural America, which found that the economic life of rural citizens is generally more stable than those living in cities. Poverty and income inequality are both lower in rural regions than in metropolitan areas, for example.
That doesn’t mean that financial anxiety isn’t a real pressure felt by white, rural Americans, however. New research from Stanford University economist Raj Chetty and five colleagues found that young adults are less likely to learn more than their parents than in previous generations, reflecting a sharp decline in social mobility.
“Maybe for white families the future doesn’t look the way the past has,” Elliott said, adding “even if it’s not borne out in what actually happens.”
