TheEconomist/us-potus-model

Health v2 · maintenance only

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1268 stars · 189 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Code for The Economist's dynamic multilevel Bayesian model to forecast US presidential elections, written in R and Stan. It aggregates state and national polls with corrections for partisan non-response, survey mode, and population, producing state-level and electoral college predictions.

Use cases

• forecast us presidential election outcomes from polling data
• run a bayesian multilevel poll aggregation model in stan
• backtest election forecasting models on 2008 2012 2016 data
• adjust polls for partisan non-response and survey mode bias
• model state-level correlations for electoral college prediction

When to choose

• you need a well-documented, peer-reviewed Bayesian election forecasting model
• you want to reproduce or extend The Economist's 2020 US presidential forecast
• you work in R and Stan and need a real-world multilevel time-series modeling example

When to avoid

• you need forecasts for non-US elections or non-presidential races
• you want a maintained, actively updated tool - it was built for the 2020 election cycle
• you need a production service or GUI rather than R scripts

Facets

application · maturity maintenance

machine-learning data-science data-visualization data-science analytics python cli bayesian-model stan election-forecasting r polling political-science politics

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markdown · JSON · MCP: product_card(name="TheEconomist/us-potus-model")