The presidential election has raised an uncomfortable possibility for big American cities, most of them run by Democrats.
Voters in the largest urban counties moved more as a group toward Donald J. Trump since the 2020 election than the nation did as a whole, with eye-popping shifts in New York, Los Angeles, Miami and Boston.
That shift may reflect not just the sour national mood, Democratic strategists and commenters have warned, but a backlash to big cities themselves — their intractable housing costs, their homeless camps and migrant waves, their pandemic-era disruptions and long school closures. Perhaps a rising share of urban voters has rejected all that.
The theory proposes a kind of reverse-coattails effect: that local Democratic governance is dragging down the party nationally.
“It’s hard for Democrats to go out and make the case that we’re the party of good government, and Republicans are the party of chaos, when you have very visual examples of cities that look like they are ungovernable, or haven’t been governed well,” said Lis Smith, a Democratic strategist who has worked on presidential and mayoral campaigns.
A closer look at county-level results, however, offers little sign that urban woes were a primary driver of this rightward shift. Cities, rather, are the places where nationwide trends in this election stand out: Mr. Trump improved the most with nonwhite voters, and they live in big cities in big numbers. We can see that by revisiting the above chart.
If local urban dynamics were what influenced voters, independent of these demographics, we would expect voters in areas with more extreme conditions — faster rent hikes, more asylum seekers, longer school closures, growing homeless populations — to shift more toward Mr. Trump.
Our analysis found some local factors that did help fill in gaps race can’t explain, to a modest degree. But most measures of urban ills we examined simply didn’t do that.
A clear demographic pattern
If urban voters were rejecting liberal overreach or social disorder in their cities, we might expect that to show up as shifts toward Mr. Trump in Seattle, Minneapolis and Portland, Ore., three places with disruptive pandemic-era protests and progressive policy experiments.
But when we look at all 68 urban core counties — counties encompassing what we would think of as the “inner cities” of the nation’s largest metropolitan areas — the Minneapolis, Portland and Seattle areas notably didn’t shift much at all. They’re also among the least diverse:
Among these urban counties, how much they shifted toward Mr. Trump is correlated with how diverse their population is. At one end, Allegheny County, where Pittsburgh is, has the lowest nonwhite population share and made no shift at all. At the other, the Bronx and Miami have the highest nonwhite share and made large shifts toward Mr. Trump.
It’s possible that dissatisfaction with city conditions is part of what has pushed some Black, Asian and Hispanic voters away from Democrats, or to stay home on Election Day (a number of those voters who sat out this election may not have voted Democratic even if they had gone to the polls). But similar shifts happened outside of cities, especially in places with more Hispanic residents.
“That shifting was happening everywhere — so it’s happening in Lawrence, Mass., as much as it’s happening in the Rio Grande Valley, it’s happening in the Central Valley of California, it’s happening in Grand Rapids and Detroit,” said Carlos Odio, a co-founder of Equis Research, a Democratic-leaning group that focuses on Latino voters. “These places are so different that the only thing they have in common is that the kinds of people who are switching, they identify as Hispanic.”
He and other researchers and pollsters will now spend months trying to understand why ties have broadly loosened between Hispanic voters and the Democratic Party. But the answer is probably not a story that fits in New York but fails along the Rio Grande.
In cities where more granular precinct data is available, the same demographic pattern recurs at the neighborhood scale: Overall, Mr. Trump is most popular in precincts where white residents are the largest group by population, but he made the smallest gains in such places this year. The broadest gains he made were often in Hispanic neighborhoods, whether they’re predominantly Mexican, Puerto Rican or Dominican.
Among core urban counties, some voting differences clearly can’t be explained by basic diversity numbers. Why did Brooklyn, an East Coast liberal enclave, shift 11 points more than Washington, D.C., another East Coast liberal enclave with a similar share of nonwhite residents? Why did the Detroit area shift so much more than Milwaukee, when both are similarly diverse and subject to swing-state dynamics?
There are also nuances within racial and ethnic groups, white voters included. Detroit’s white population differs from Milwaukee’s — Wayne County, Mich., has one of the country’s largest communities of Arab Americans, who broke away from Democrats over the war in Gaza (census data currently counts people of Middle Eastern and North African descent as white). Washington’s white voters also differ from Brooklyn’s — the nation’s capital, which shifted less than one point toward Mr. Trump, has the lowest share of white working-class adults of all of these urban counties.
Other potential factors
There is no denying that over the past four years, many big cities have faced acute problems distinct from the surge in inflation that angered voters nationwide.
To test whether those ills were related to the rightward shifts, we compiled data on the local cost of living, growth in rents and home prices, new housing permits and homelessness. We looked at where migrants have settled, using court records from federal deportation cases. We considered long pandemic school closures. To identify where residents may have been disaffected enough to pack up and leave, we measured which urban counties had lost population share since 2019. We also considered the places hit hardest by Covid deaths.
Then we modeled whether these factors were able to predict how an urban county voted in the election.
Some data was incomplete, and many of these variables overlap, making it difficult to disentangle their effects statistically. When we sized them up individually, only some of these factors correlated with election results. After we controlled for race, those effects faded.
Three measures, looked at together, did help to fill in some of the differences between urban counties that remained after considering race: the share of white adults without a college degree, the local cost of living and migrant arrivals. But race still remained far and away the most important factor.
In an election year when voters were broadly upset about inflation, perhaps it mattered more in big cities, often already expensive places to live. But it doesn’t appear that voters shifted more in places where housing costs had risen the most. Big cities are also places where homelessness and high rents are longtime issues, said Stephen Eide, a senior fellow at the Manhattan Institute. That might make it less likely they can explain recent political changes.
Several of the counties that shifted significantly to the right also received among the most migrants since 2021, including Miami-Dade in Florida, much of New York City, and Essex and Union Counties in New Jersey. (This is also another difference between Brooklyn and Washington.)
Counties with long school closures did shift more toward Mr. Trump nationwide than counties where school returned to normal faster. But after accounting for race, the effect largely disappears. Because long closures happened broadly across big cities (often reflecting the concerns of nonwhite families), they also can’t explain the voting differences among urban counties. For example, highly diverse New York City, San Francisco, Baltimore, Atlanta and New Orleans had widely varying election shifts. But all of them had long school closures.
One other factor we didn’t measure is crime, given that crime data is particularly spotty and difficult to compare across places. In politics, perceptions of crime may also matter more than actual crime, and the two trends often point in different directions. So we don’t dismiss that crime fears may influence voters in a presidential election; we just can’t measure them.
Our overall analysis doesn’t mean that urban residents are unbothered by local problems. But that anger may not have much to do with choosing the country’s president.
If anything, said the Vanderbilt political scientist John Sides, U.S. politics have become increasingly nationalized — dominated by issues and dynamics at the national level. The theory of Democratic cities in disarray implies the opposite: that in big cities, a national election was actually localized.
Imagine a scenario, Mr. Sides suggested, where cities still experienced the same problems — subway crime in New York, a housing crisis in Los Angeles — but there had been no nationwide surge in inflation. Who wins that presidential race in a different national environment? Quite likely the Democrat, he said, and then perhaps people wouldn’t be having this same conversation.
Some urban voters did clearly express frustration with local conditions this year — in local elections. In San Francisco, they voted out a moderate Democratic mayor. In neighboring Alameda County, they recalled a progressive district attorney and the mayor of Oakland, who was also under investigation by the F.B.I. In Los Angeles, voters turned out another progressive prosecutor.
But none of those counties shifted further to the right than we might expect given their demographics.
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