Abstract: Democratic politics requires voters to infer how political actions map into outcomes, yet these causal links are often unclear, giving politicians scope to shape voters' causal accounts. This paper studies the supply and returns of causal rhetoric in politics: politicians' language linking political actions to outcomes through blame and credit. We fine-tune a language model to measure its use in 4.2 million congressional tweets spanning 2012--2023. Causal rhetoric is central to politicians' communication: it accounts for more than one third of tweets, is the language of political disagreement, and rises over time. The political returns of causal rhetoric are concentrated in blame. Combining campaign contributions with quasi-exogenous geographic variation in Twitter adoption, we find that exposure to blame has the largest effects on small donations. Using voting intentions from survey data and an event-study design around blame-only and credit-only days, we find that politicians' support rises after blame-only days. Finally, causal rhetoric appears rarely supported by economic knowledge, particularly blame.

For Information contact angela.baldassarre@unibocconi.it or giulia.zenoni@unibocconi.it