Manifesto Project Database

US election 2024: beware polling predictions as they can be wrong – but here's an approach which has often been on the money

Retrieved on: 
火曜日, 8月 22, 2023

Despite the avalanche of legal indictments, Donald Trump remains favourite to win the Republican nomination for the 2024 US presidential election.

Key Points: 
  • Despite the avalanche of legal indictments, Donald Trump remains favourite to win the Republican nomination for the 2024 US presidential election.
  • If he does win the Republican nomination the question is: can he win the presidential election in November next year?

Forecasting presidential elections

    • There is a lively community of political scientists using a variety of different methods to forecast elections, with many focusing on the US.
    • Most forecasting models use polling data, but since we are 15 months away from the presidential election, current polling should be treated with caution.
    • It should be noted that US pollsters have had a mixed record in forecasting elections.

Electoral college

    • The election is determined by who wins the electoral college, not the popular vote.
    • In the 2016 election Clinton won a larger vote share than Donald Trump but lost the contest in the electoral college.
    • The electoral college was created by the US founding fathers, with delegates chosen to reflect voting support for the candidates in each state.

A forecasting model

    • The analysis uses a century of elections from 1920 to 2020, and a relatively simple model has a good track record in predicting elections over this period.
    • It uses two variables to predict the Republican share of the delegates in the Electoral College, using a technique called multiple regression.
    • The first and most important predictor in the model is the state of the economy, with an incumbent being rewarded for a good record on economic growth and punished for a poor one.
    • The model takes into account unusual events occurring over the period that can distort the results if they are ignored.
    • Needless to say this is uncertain since the model is not a perfect fit to the data and so subject to errors.