You Lose, You Lag: Evidence from 2020 and 2024 on U.S. Partisan Bias, Presidential Election Defeat, and Perceived Future Real Income

Recent presidential elections, in particular the two most recent ones, have revealed striking partisan divides, not only in political attitudes but also in household economic expectations. This study investigates how partisan electoral loss shapes perceived changes in real income across income groups, using data from the University of Michigan Survey of Consumers surrounding the 2020 and 2024 U.S. presidential elections. I employ ordered logistic regression models for the baseline models and generalized ordered logistic regression models for those models with pertinent demographic controls in order to analyze the probability of respondents expecting real income losses, stability, or gains, respectively. Generating predictive probabilities for the typical voter with each specification, the results show that following partisan defeat, optimism among poor Republicans in 2020 fell by nearly 40%, while the likelihood of pessimism rose by 16 percentage points to approximately 58%. In 2024, poor Democrats exhibited a 60% collapse in optimism and a 40% surge in pessimism. These shifts persist after accounting for education, sex, and age, suggesting that political identity, rather than demographic composition, primarily drives expectation changes. The findings highlight that elections materially influence economic perceptions, which, in turn, shape broader narratives circulated through the financial press. Understanding these partisan biases is essential for researchers modeling consumer sentiment, policymakers interpreting survey data, and investors anticipating post-election market behavior.