Right now, our model thinks Joe Biden is very likely to beat Donald Trump in the electoral college.

Our model is updated every day and combines state and national polls with economic indicators to predict a range of outcomes.

Our model works by simulating 20,000 paths for the election, each time varying candidates’ vote shares to account for polling error, changes in turnout or the political environment and the effects of campaigning. Our model combines the national prediction with polls and political-economic factors at the state level. We take into account that states that are similar are likely to move with each other; if Donald Trump wins Minnesota, he will probably win Wisconsin too.

We use two metrics to measure states’ importance. One is the “tipping-point probability”: the chance that a state will cast the decisive 270th electoral vote for the victor. The other is the chance that any single voter in a state will cast the decisive ballot that wins the tipping-point state for the next president. The model first averages the polls, weighting them by their sample sizes and correcting them for tendencies to overestimate support for one party. It then combines this average with our forecast based on non-polling data, pulling vote shares on each day slightly towards the final election-day projection.

Our model also simulates what would happen if the race moves, or the polls are biased, in similar amounts in like states. We calculate similarity between states by comparing their demographic and political profiles, such as the share of voters who live there, how religious they are and how urban or rural the state is.

(TL: DR; The Economist's current modeling shows Biden ahead of Trump 54.1 to 45.9 percent nationally. Their simulations predict a victory by about 100 votes in the electoral college. It gives Joe Biden a 92% chance of victory in the election.)

[projects.economist.com]