What does The Economist’s election model predict for the midterms | The Economist

Electoral Probability Forecasts

• The Economist model assigns Democrats a 98% probability of flipping the House of Representatives.
• The same model estimates a 48% probability of Democrats winning control of the Senate.
• The forecasting system integrates historical election results, national and state-level polling, presidential approval ratings, special election outcomes, and fundraising data.
• The model explicitly calibrates polling uncertainty, projecting potential error directions and magnitudes across districts based on historical precedents.

House of Representatives Outlook

• Midterm historical trends strongly favor the non-incumbent party, given the President's 20-point underwater approval rating.
• Generic ballot polling shows Democrats leading Republicans by approximately six points.
• Current Map Assumption: The 98% House confidence is conditional on current district maps remaining final; it does not account for potential judicial overturning of Democratic gerrymanders in Virginia.
• Redistricting Risks: Retaliatory gerrymandering is expected in Florida, though the model suggests such changes would not drastically alter the House projection even if they occur.

Senate Outlook

• The Senate race is modeled as a "coin flip" (48% probability) despite a map structurally favorable to Republicans.
• Republicans currently hold a majority due to the Vice President's tie-breaking power, requiring Democrats to flip four seats.
• Key States and Scenarios:
  • North Carolina: Former Governor Roy Cooper is projected to likely win, potentially providing a necessary Democratic seat.
  • Michigan: Democrats must hold an open seat amidst a divisive primary.
  • Maine: Democrats must unseat Senator Susan Collins in a state that supported Trump by double digits.
  • Additional Seats: Two further state flips in Trump-won territories are required for a Democratic majority.
• Candidate Quality: The forecast relies on strong Democratic recruitment, specifically in Ohio (Sherrod Brown) and Alaska (Mary Peltola), to reach the 51-seat threshold.

Variables and Risks

• Known Unknowns: Primary outcomes are the most significant variables; the model assumes incumbent renominations and cannot incorporate race-specific polling until nominees are selected.
• Political Environment Shifts: A significant swing in the national environment, such as a drop in the generic ballot lead from six points to zero, would fundamentally alter the forecast.
• Unforeseen Events: External shocks benefiting Trump/Republicans or harming Democrats remain a possibility outside the model's scope.