You can’t trust exit polls on demographics crosstabs. From Matt Yglesias on Slow Boring:
Over and above the challenge inherent in any statistical sampling exercise, the basic problem exit pollsters have is that they have no way of knowing what the electorate they are trying to sample actually looks like, but they do know who won the election. They end up weighting their sample to match the election results, which is good because otherwise you’d have polling error about the topline outcome, which would look absurd. But this weighting process can introduce major errors in the crosstabs.
For example, the 2020 exit poll sample seems to have included too many college- educated white people. That was a Biden-leaning demographic group, so in a conventional poll, it would have simply exaggerated Biden’s share of the total vote. But the exit poll knows the “right answer” for Biden’s aggregate vote share, so to compensate for overcounting white college graduates in the electorate, it has to understate Biden’s level of support within this group. That is then further offset by overstating Biden’s level of support within all other groups. So we got a lot of hot takes in the immediate aftermath of the election about Biden’s underperformance with white college graduates, which was fake, while people missed real trends, like Trump doing better with non-white voters.
To get the kind of data that people want exit polls to deliver, you actually need to wait quite a bit for more information to become available from the Census and the voter files about who actually voted. Eventually, Catalist produced its “What Happened in 2020” document, and Pew published its “Behind Biden’s 2020 Victory” report. But those take months to assemble, and unfortunately, conventional wisdom can congeal in the interim.
You can’t trust exit polls on demographics crosstabs. From Matt Yglesias on Slow Boring:
I misspoke. I was using the actual results from Dearborn, and not exit polls. Note how differently they voted from Wayne County as a whole!