Excellent notes -- But watch Indiana... A +20 points state for Trump in 2024, but notoriously ready to turn purple. Trump has screwed the soybean farmers, auto industry, and has really offended plain Hoosier folk with his self-love. In particular -- watch Governor Mike Braun -- a STAUNCH Trump supporter as senator and early-term governor -- but smart enough to know wind direction -- especially after Republicans in the state legislature overwhelming stiff-armed Trump on gerrymandering. Also note former Indiana governor Mitch Daniels, is finally, carefully, going public with is negative views of Trump. (He was privately negative on Trump in 2024.) Meanwhile, other previous GOP governor Mike Pence is actively stirring the negative-Trump pot. This all will make for an interesting stew by summer of 2026.
State by state is super helpful l, and I hope all of the campaign data nerds that need to see this are seeing it! Your work is so important. Thank you!!
The shift to focus on individual states rather than national polling is very helpful for working out election strategy at both the state and national level.
Your excellent explanation at the end of your modeling method is way beyond me, but I have one question: if you weight strata by their voting characteristics in the 2024 Presidential election, aren't you building in a pro-GOP (pro Trump actually) bias that will not be present in 2026 when he is not personally on the ballot (although arguably the mid-terms are heavily influenced by attitudes toward Trump himself)? Stated differently, if many GOP voters voted in 2024 because they wanted to support Trump, and simply clicked on GOP candidates on the ballot, won't there be a drop off in 2026 of such voters because their man is not on the ballot?
This is a great question. The simple answer is no, adjusting by past vote does not bias the model toward Republicans. This is because we are only holding their recollection of their past behavior constant with real-world results, and still allowing change in other variables. So if the people who said they voted for Trump in 2024 show higher disaffection rates in 2026/2028, that gets picked up by the model.
Put another way, imagine we have 4 groups of adults: (1) Adults who voted for Trump, (2) Adults who voted for Harris, (3) Adults who voted for someone else, and (4) Adults who did not vote in 2024, either because they were too young or they chose not to. These groups should be roughly stable over time, since turnout and Trump's vote share in 2024 do not change. But forcing the past vote buckets to match proportions in real results does not bias _current_ estimates, because those are allowed to change relative to past targets.
In other words, we aren't forcing the 2026 vote intention for every respondent to match their 2024 vote intention.
*I say "roughly" because actually the non-voter pool should increase slightly over time as 2024 voters age out of the electorate and younger people age in, increasing the non-voter %, but we can take care of that too.
Excellent notes -- But watch Indiana... A +20 points state for Trump in 2024, but notoriously ready to turn purple. Trump has screwed the soybean farmers, auto industry, and has really offended plain Hoosier folk with his self-love. In particular -- watch Governor Mike Braun -- a STAUNCH Trump supporter as senator and early-term governor -- but smart enough to know wind direction -- especially after Republicans in the state legislature overwhelming stiff-armed Trump on gerrymandering. Also note former Indiana governor Mitch Daniels, is finally, carefully, going public with is negative views of Trump. (He was privately negative on Trump in 2024.) Meanwhile, other previous GOP governor Mike Pence is actively stirring the negative-Trump pot. This all will make for an interesting stew by summer of 2026.
It's fascinating to see the difference between western rural North Carolina and eastern rural Tennessee
State by state is super helpful l, and I hope all of the campaign data nerds that need to see this are seeing it! Your work is so important. Thank you!!
The shift to focus on individual states rather than national polling is very helpful for working out election strategy at both the state and national level.
Your excellent explanation at the end of your modeling method is way beyond me, but I have one question: if you weight strata by their voting characteristics in the 2024 Presidential election, aren't you building in a pro-GOP (pro Trump actually) bias that will not be present in 2026 when he is not personally on the ballot (although arguably the mid-terms are heavily influenced by attitudes toward Trump himself)? Stated differently, if many GOP voters voted in 2024 because they wanted to support Trump, and simply clicked on GOP candidates on the ballot, won't there be a drop off in 2026 of such voters because their man is not on the ballot?
Hi there Rees,
This is a great question. The simple answer is no, adjusting by past vote does not bias the model toward Republicans. This is because we are only holding their recollection of their past behavior constant with real-world results, and still allowing change in other variables. So if the people who said they voted for Trump in 2024 show higher disaffection rates in 2026/2028, that gets picked up by the model.
Put another way, imagine we have 4 groups of adults: (1) Adults who voted for Trump, (2) Adults who voted for Harris, (3) Adults who voted for someone else, and (4) Adults who did not vote in 2024, either because they were too young or they chose not to. These groups should be roughly stable over time, since turnout and Trump's vote share in 2024 do not change. But forcing the past vote buckets to match proportions in real results does not bias _current_ estimates, because those are allowed to change relative to past targets.
In other words, we aren't forcing the 2026 vote intention for every respondent to match their 2024 vote intention.
*I say "roughly" because actually the non-voter pool should increase slightly over time as 2024 voters age out of the electorate and younger people age in, increasing the non-voter %, but we can take care of that too.