The Structure of Economic News

Leland Bybee, Bryan T. Kelly, Asaf Manela and Dacheng Xiu

No 26648, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text content of 800,000 Wall Street Journal articles for 1984{2017, we estimate a topic model that summarizes business news as easily interpretable topical themes and quantifies the proportion of news attention allocated to each theme at each point in time. We then use our news attention estimates as inputs into statistical models of numerical economic time series. We demonstrate that these text-based inputs accurately track a wide range of economic activity measures and that they have incremental forecasting power for macroeconomic outcomes, above and beyond standard numerical predictors. Finally, we use our model to retrieve the news-based narratives that underly “shocks” in numerical economic data.

JEL-codes: C43 C55 C58 C82 E0 E17 E32 G0 G1 (search for similar items in EconPapers)
Date: 2020-01
New Economics Papers: this item is included in nep-big, nep-cmp and nep-mac
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