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How The Economist’s presidential forecast works
The ins and outs of how we forecast the election
Developed with the assistance of a team of political scientists led by Andrew Gelman of Columbia University, our model calculates Joe Bidenâs and Donald Trumpâs probabilities of winning each individual state and the election overall. It uses a statistical technique called Markov Chain Monte Carlo (MCMC), which explores thousands of different values for each parameter in our model, and evaluates both how well they explain the patterns in the data and how plausible they are given the expectations from our prior. As the election draws near, there are fewer days left for this random drift to accumulate, reducing both the range of uncertainty surrounding the current polling average and the influence of the prior on the final forecast.
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