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Reading this interview with GSG’s Nick Gourevitch, a Harris pollster, I was reminded that we pollsters are the ultimate bubble-piercers. Regardless of party, we see the same data, hear the same things in focus groups, and operate from the same reality. Really nothing to disagree with here:
“I generally think reasons number one, two and three are the economy and inflation. If you look at the 15 percent middle of the electorate, the swing voters, they said inflation was their top issue. They gave President Biden 73 percent disapprove on the economy. And they retrospectively approved of Trump’s performance on the economy, even if they held mixed opinions of him personally.”
“Harris did better in the battleground states, where turnout was higher. So one interesting thing will be just to understand the degree to which that gap was due to turnout in non-contested states. I do not believe that will be the whole story, but it will probably be part of the story. The other part is vote switching. A lot of those states [have substantial numbers of] voters of color. Those are states also with high cost of living. I think that sort of cocktail was problematic in those places.”
South Carolina, a non-battleground, saw a bigger racial realignment— especially in Charleston and Upstate.
Meanwhile, Georgia saw the biggest swings in the Black Belt, based on micro-communities I had previously defined in my brief on the state.
Last week’s panel with the Niskanen Center and The Liberal Patriot is up as a podcast.
The salience of this connection is demonstrated by post-election data from the Blueprint strategy group. The third most potent reason—after too much inflation and too much illegal immigration—for voters to choose Trump over Harris in a pairwise comparison test was “Kamala Harris is focused more on cultural issues like transgender issues rather than helping the middle class”. And among swing voters, this concern about focus was the most powerful reason.
And look at what swing voters who chose Trump thought were extremely or very accurate criticisms of the Democratic Party:
This was a bad election for the Crosstab Truthers, who called into question every result showing Trump doing better with Black voters or Harris doing fine with seniors. At least some version of both of these things came to pass, as David Shor demonstrates with seniors.
Despite high levels of political homophily in the labor market, these results point to the limited role for the workplace in shaping partisanship in the short run – especially in changing the minds of those who already know where they stand. By contrast, selection is strong: even those who haven’t yet registered as a Republican move to Republican-leaning firms, and vice versa for Democrats. This leads us to study the effect of workers’ politics on their job choices.
Finally, we interpret the estimates using the canonical Rosen (1986) model of job amenities and compensating differentials. In the model, the difference in Democrats’ and Republicans’ preferences for ideological amenities leads them to sort into different workplaces, but heterogeneity in their preferences for these amenities limits the segregation that they can create. For example, even if some Democrats value these amenities highly, the ones who care more about their salary than their ideological compatibility with their employer will take jobs where they encounter Republicans at work, and overall segregation will be low. Thus, the extent to which this channel can drive segregation depends on the full distribution of worker preferences, not just the average.
No newsletter next week due to the holiday and trying to slow down things down at least some from the post-election whirlwind. Happy Thanksgiving!
Thanks for the Chinoy paper! Quick scan finds some interesting tidbits (like Costco employees being very slightly redder than Walmart employees out of the author's sample set; not what I would have guessed).
Thanks for the Chinoy paper! Quick scan finds some interesting tidbits (like Costco employees being very slightly redder than Walmart employees out of the author's sample set; not what I would have guessed).