| data | ||
| go.mod | ||
| main.go | ||
| makefile | ||
| README.md | ||
Nuño's deads imple election simulator
First round: just consider the base rates.
- Get past electoral college results since 2000
- Get number of electors for each state with the new census
- Combine the two to get an initial base rates analysis
This initial approach gives a 25% to republicans winning in the 2024 election. Why is this? Well, consider the number of electoral college votes:
| Year | Republican electoral college votes |
|---|---|
| 2000 | 271 |
| 2004 | 286 |
| 2008 | 173 |
| 2012 | 206 |
| 2016 | 304 |
| 2020 | 232 |
| Year | Democrat electoral college votes |
|---|---|
| 2000 | 266 |
| 2004 | 251 |
| 2008 | 365 |
| 2012 | 332 |
| 2016 | 227 |
| 2020 | 232 |
When Democrats won with Obama, they won by a lot, whereas when Republicans won with Bush and Trump, they won by a smaller amount. Or, in other words, this initial approach doesn't take into account that states are correlated.
Remedy: consider the conditional probabilities? But how? Or, relax assumptions using Laplace's law?
- Consider conditional probabilities
- See how other models account for the correlation
- Add uncertainty using Laplace's law of succession?
- Maybe only do this for contested states? Alabama is not going to turn Democratic?
Second round: just consider polls
- Download and format
- Read
- Add date of poll
- Consider what the standards error should be
- Consider how to aggregate polls?
- One extreme: Just look at the most recent one
- Another extreme: Aggregate very naïvely, add up all samples together?
- Aggregate polls?
- Exclude polls older than one month?
- Exclude partisan polls
- ...