Business News and Business Cycles
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Abstract
<jats:title>ABSTRACT</jats:title><jats:p>We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 <jats:italic>Wall Street Journal</jats:italic> articles for 1984 to 2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and can forecast aggregate stock market returns. A text‐augmented vector autoregression demonstrates the large incremental role of news text in forecasting macroeconomic dynamics. We retrieve the narratives that underlie these improvements in market and business cycle forecasts.</jats:p>