Inflation Narratives and Expectations

Abstract

I study the extent to which the time-varying disagreement in inflation expectations between households and professionals can be explained by the differences in demand and supply narratives of newspaper articles read mainly by households and professionals. I measure demand and supply narratives via a Causality Extraction algorithm that can identify causal relationships between events in a text. Causal relations can explain why narratives affect people's beliefs and cannot be captured by dictionary methods, topic models, and word embeddings. General newspapers' demand and supply narratives correctly predict only households' demand-supply expectations, while specialized newspapers' narratives predict the demand-supply expectations of both professionals and households. I then use general and specialized newspapers' demand and supply narratives to measure narrative disagreement. Differences in inflation expectations between households and professionals rise when narrative disagreement increases. This increase is larger for households with low education levels and when newspapers disagree about supply chain and monetary policy narratives.

Keywords: Inflation, Survey expectations, News on inflation, Narratives, Causality extraction, Text analysis, NLP

JEL Classification: C53, D1, E3, D8