Analyzing Presidential Re-Election Prospects: A Composite Score Approach using the Concordia Model
From Ford to Biden: Predicting Re-Election with the Concordia Composite Score
Predicting the outcome of presidential re-election campaigns has always been a complex endeavor, involving multiple factors such as approval ratings, economic performance, and public sentiment. This essay explores the use of the Concordia Model, a composite score approach, to evaluate the re-election prospects of U.S. presidents, from Gerald Ford in 1976 to the projected 2024 campaign of Joe Biden. By examining historical data and employing logistic regression, we aim to determine Joe Biden's win probability for the 2024 election based on his composite score.
Methodology
The Concordia Model incorporates key metrics:
These components are summed to produce a composite score for each president.
Historical Composite Scores
Using the above methodology, we calculated the composite scores for presidents seeking re-election from 1976 to 2020:
Analysis and Threshold Determination
From the historical data, we observe that presidents with a composite score above approximately 7 generally tend to win re-election, while those below 7 tend to lose.
The logistic regression model predicts a win probability of approximately 6.99% for Joe Biden with his composite score of 3.52.
Visualization
The following chart visualizes the win probability versus composite score, with historical presidents and Biden's projected 2024 score annotated:
Win Probability vs Composite Score
Green points indicate presidents who won re-election.
Red points indicate presidents who lost re-election.
Blue point represents Joe Biden's projected win probability for 2024.
Black dashed line indicates the threshold composite score (7) for re-election success.
Conclusion
Based on the Concordia Model and logistic regression analysis, Joe Biden's win probability for the 2024 re-election campaign is approximately 6.99%, indicating a low likelihood of winning. This analysis, grounded in historical data, provides a quantitative assessment of re-election prospects, highlighting the importance of various economic and approval metrics in determining electoral outcomes.