One lesson of the U.S. presidential election is that we should forget about red and blue states, North and South, coastal coffeeshops and heartland diners. The geographic divide in American politics is closer to home. If you want to predict how someone will vote, ask, How near are your neighbors?
Residential density has long played a role in shaping American politics. In the recent election, 49 of the 50 highest density counties voted for Hillary Clinton, and 48 of the 50 lowest density counties chose Donald Trump (nearly the same split as for Barack Obama and Mitt Romney four years earlier). In “blue” California, the agricultural towns of the Central Valley swayed Republican, while in “red” Texas the big cities voted Democratic. Across the spectrum of purple hues, a high-resolution map of population density closely matches voting results.
There are reasons for this that go beyond identity politics. Urban density has social and economic advantages that make cities attractive to liberals and that also condition liberal values over time. Living among diverse neighbors can reduce fear and resentment, as everyday interactions break down stereotypes and misconceptions of ‘the other.’ (Which is not to ignore that cities have their own problems with racial and economic segregation.)
One recent study compared voters who switched from Obama to Trump with those who switched from Romney to Not-Trump. Controlling for “age, race, education, income, gender, party identification, concern about rising immigration, racial resentment, and worries about personal finances,” the authors found that a vote for Trump was correlated with fear of rising diversity. They concluded that the election was a “clash over the openness of society,” which may explain why cities produce liberal voters. Density politics is arguably at the core of racial acceptance. […]