This paper studies the role of narratives for macroeconomic fluctuations. Micro-founding narratives as directed acyclic graphs, we show how exposure to different narratives can affect expectations in an otherwise-standard macroeconomic framework. We identify such competing narratives in news media reports on the US yield curve inversion in 2019, using techniques in natural language processing. Linking this to data from Twitter, we show that exposure to the narrative of an imminent recession causes consumers to display a more pessimistic sentiment, while exposure to a more neutral narrative implies no such change in sentiment. Applying the same technique to media narratives on inflation, we estimate that a shift to a viral narrative of inflation damaging the real economy in 2021 accounts for 42% of the fall in consumer sentiment in the second half of the year.
