🚨NEW from me and @TheEconomist's data team: Our interactive for the 2020 Democratic primary! We have a fancy polling average, candidate support by demographic group, data on who candidates' core voters are also considering and more. <THREAD> (No paywall!) projects.economist.com/democratic-pri…
1. Here is a collection of screenshots from the interactive. Allow me to tell you about some of the features, how they work, where we get our data and how we did our modeling. 1/13
2. The first element on the page presents our average of high-quality national polls of the Democratic primary. We include phone polls from firms that survey with live interviewers and online polls from firms that use well-documented, trusted methods (ie no IVR/Mturk combos).
3. We average the polls over time using a Bayesian implementation of a dynamic Dirichlet regression model. The model is specified to give more weight to higher quality pollsters, less weight to data collected in the past and incorporates pollster house effects.
4. The method used to calculate house effects is complicated, but know we let the model sort it out. Effects can change over time. (Something cool: the model also allows the average to learn about candidates' standings at the state level—but we're not releasing this just yet!)
5. Our 2020 site also features an array of interactive visualizations built on our weekly polling data from @YouGovUS. Breaking down support by demographic and political group is a major contribution of this project and something few other media outlets are providing.
6. We show a selection of demographics on the home page, but we make more detailed data available for each candidate on their own separate pages.
7. These stats are derived from the last month of data from YouGov. This gives us a large enough sample size to minimize sampling error while staying relevant, but also means the figures might differ from other analyses of YouGov's data. If you see small differences, fret not.
8. Though we focus quite a lot on first-choice vote intention, YouGov also provides some particularly insightful data in asking who voters are "considering" voting for. This may give us a reasonable upper bound on candidates' support in the polls.
9. One of the coolest parts of the project is this breakdown showing the share of each candidate's first-choice supporters who are considering other options. For example, Nearly 60% of Warren voters are also considering Harris, and 15% of Sanders voters consider Yang, too.
10. Because polls aren't all the information that may decide who is most likely to win the primary, and though prediction is not our ultimate goal with this project, we also show smoothed market betting odds.
11. The interactive updates at least daily, and sometimes more often when we have new polling, betting or YouGov data. We will be adding features (like state-levels polling) over time, so follow me for updates!
12. Worth giving a few hat tips. First up is @FiveThirtyEight for open-sourcing their collection of 2020 polling. @PoliSciJack also helped me implement a version of the that model we ended up using. Thanks to @PredictIt for archiving market data!
13/13. We hope you will find this as fun and insightful as we do! @martgnz and @futuraprime put their blood, sweat and tears into getting the website working and visualizations looking nice. It was a team effort.
If you have any feedback, we'd love to hear from you! Enjoy!
@martgnz@futuraprime Oh by the way, if you scroll over a candidate's face they will wiggle
Some early vote Qs: What % of 2020 early voters have voted so far in 2024? Does that differ by party? What about E-day voters?
Now that we have a substantial number of votes — above 10m in the swing states, or around 37% of likely voters in those states — we can start tracking:
This is the % of 2020 ABEV voters who have voted in 2024, as of yesterday
AZ 39% of Ds, 39% of Rs
GA 58%D 66%R
MI 43%D 45%R
NC 44%D 47%R
PA 40%D 35%R
WI 35%D 36%R
(No data in NV because our voter file vendor, L2, has been lagging there, and Clark County returns have been weird)
Other big caveat is that in MI, WI and GA, party registration is based on a model, so comes with a lot of potential measurement error. Partisan splits here may be less indicative of an advantage than in, say, AZ, NC or PA.
📊Today 538 is releasing an updated set of our popular pollster ratings for the 2024 general election! Our new interactive presents grades for 540 polling organizations based on their (1) empirical record of accuracy + (2) methodological transparency. 1/n abcnews.go.com/538/best-polls…
There’s tons to say but I’ll hit a few main points. First, a methodological note. For these new ratings, we updated the way 538 measures both *empirical accuracy* and *methodological transparency.* Let me touch on each. (Methodology here: ) abcnews.go.com/538/538s-polls…
(1) *Accuracy.* We now punish pollsters who show routine bias toward one party, regardless of whether they perform better in terms of absolute error. We find that bias predicts future error even if it’s helpful over a short time scale.
if you want to understand polling today, you have to consider *both* the results and the data-generating process behind them. this is not a controversial statement (or shouldn't be). factors like nonresponse and measurement error are very real concerns stat.columbia.edu/~gelman/resear…
given the research on all the various ways error/bias can enter the DGP, if your defense against "polls show disproportionate shifts among X group. meh" are "well X group voted this way 20 years ago," i am going to weight that pretty low vs concerns about non-sampling error
at the same time, if a critical mass of surveys is showing you something ,you should give it a chance to be true. interrogate the data and see if there's something there. i see tendencies both to over-interpret crosstabs and to throw all polls out when they misfire. both are bad
There is good stuff in this thread, and I’ve been making the first point too for some time. But remember a lot can change in a year, and some of the factors that look big now may not actually matter. Uncertainty is impossibly high this far out.
I took a look yesterday at how much Dem state-lvl POTUS margins tends to change from year to year. It’s about 7pp in our current high-polarization era. That’s a lot! With 2020 as our starting point simulating correlated changes across states, you get p(Biden >= 270) around 60%.
that is obviously not a good place to start if you are team Biden. But the range of outcomes is laughably large—a landslide for either party is more than plausible. So there is a pick your own adventure element to analyses like these: Dobbs, Jan 6 help Ds; Economy, Biden age hurt
Lots to share, but for now I'll just say FiveThirtyEight was one of the outlets that inspired me to be a data journalist. Nate Silver did great work & the team he led changed political journalism for the better. We will be iterating on that, but we start with a strong foundation.
2/3 ABC and I have been in talks for 6 months to ensure there will be as little disruption as possible in transitioning from the aggregation + forecasting models Silver is taking with him when his contract expires to our new in-house methods, developed w input across ABC & 538.
pretty bleak picture for the GOP 10-20 years from now, unless the party changes its policy endorsements and messaging to shrink the gap in Gen Z/Millennial voting behavior catalist.us/whathappened20…
yes, however, rolling back convenience voting reforms for students is not going to be an effective voter suppression strategy when the average Gen Z voter is out of school (my back-of-envelope math says this should happen around 2028)
bad tweet!
the point is that crossing your fingers and pretending that young people just get more right-leaning as they age is not an effective electoral strategy,
not that there is a 100% probability of democratic electoral success for the next 30 years