markjrieke / 2024-potus

repo for constructing a 2024 presidential election forecast
MIT License
45 stars 6 forks source link

2024 Presidential Forecast

This repository contains the code for running a dynamic and hierarchical Bayesian model that forecasts election outcomes in states, the nation, and the electoral college. The model is written in Stan and the supporting pipeline is written in R.

The model improves upon the Economist’s 2020 model (which, in turn, improved upon Pierre Kemp’s implementation of Drew Linzer’s model) by estimating the parameters used to generate state covariance matrices, rather than being passed the matrices as data. I intend to write a formal explanation of the model, likely after the election has concluded. In the interim, you can view a brief overview of the model definition in the README in the stan/ folder.

A more general overview of the model methodology can be found here, and the full output can be explored here.

Version history

2.11

2024-10-10

2.10

2024-09-28

2.9

2024-09-27

2.8

2024-09-26

2.7

2024-09-25

2.6

2024-09-18

2.5

2024-09-12

2.4

2024-09-03

2.3

2024-08-19

2.2

2024-08-12

2.1

2024-08-11

2.0

2024-08-03

Harris Model

Other Fixes

1.2

2024-07-16

1.1

2024-07-14

1.0

2024-07-04

Other forecasts