Preliminary draft
Abstract
This paper turns more than 40,000 hours of financial-TV dialogue from 2012 to 2026 into speaker- and topic-resolved Q&As, providing high-frequency, cross-sectional observations on sentiment, uncertainty, and dispersion in expressed beliefs. TV-based uncertainty measures display greater topic specificity than their newspaper counterparts, co-move more closely with matched market benchmarks, and expand topic coverage. Using LLMs, we score forward-looking statements along two dimensions: direction and expressed self-uncertainty. The resulting topic-specific disagreement measures align systematically with disagreement-based benchmarks, but their relation with other uncertainty benchmarks is topic- and period-specific. The paper then studies disagreement in predictions about the future policy rate. Controlling for differences in macro projections, a mismatch in speakers' interpretations of the Fed's priorities is associated with a roughly six percentage point higher probability of a large rate-path disagreement, on par with a one-standard-deviation increase in inflation-projection disagreement. The result does not weaken when restricting the comparison to explicit conditional Fed statements and survives a battery of robustness tests. TV discourse is also rich in mental-state attributions. Fed-attribution language shows a tighter relation with market-based rate-uncertainty measures than both our own text-based uncertainty measure and standard text-based alternatives.