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Forecasting with Economic News

Author

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  • Luca Barbaglia
  • Sergio Consoli
  • Sebastiano Manzan

Abstract

The goal of this article is to evaluate the informational content of sentiment extracted from news articles about the state of the economy. We propose a fine-grained aspect-based sentiment analysis that has two main characteristics: (a) we consider only the text in the article that is semantically dependent on a term of interest (aspect-based) and, (b) assign a sentiment score to each word based on a dictionary that we develop for applications in economics and finance (fine-grained). Our dataset includes six large U.S. newspapers, for a total of over 6.6 million articles and 4.2 billion words. Our findings suggest that several measures of economic sentiment track closely business cycle fluctuations and that they are relevant predictors for four major macroeconomic variables. We find that there are significant improvements in forecasting when sentiment is considered along with macroeconomic factors. In addition, we also find that sentiment matters to explains the tails of the probability distribution across several macroeconomic variables.

Suggested Citation

  • Luca Barbaglia & Sergio Consoli & Sebastiano Manzan, 2023. "Forecasting with Economic News," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 708-719, July.
  • Handle: RePEc:taf:jnlbes:v:41:y:2023:i:3:p:708-719
    DOI: 10.1080/07350015.2022.2060988
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    Cited by:

    1. Fève, Patrick & Assenza, Tiziana & Collard, Fabrice & Huber, Stefanie, 2024. "From Buzz to Bust: How Fake News Shapes the Business Cycle," TSE Working Papers 24-1516, Toulouse School of Economics (TSE).
    2. José Francisco Lima & Fernanda Catarina Pereira & Arminda Manuela Gonçalves & Marco Costa, 2023. "Bootstrapping State-Space Models: Distribution-Free Estimation in View of Prediction and Forecasting," Forecasting, MDPI, vol. 6(1), pages 1-19, December.
    3. Tiziana Assenza & Fabrice Collard & Patrick Fève & Stefanie Huber, 2024. "From Buzz to Bust: How Fake News Shapes the Business Cycle," ECONtribute Discussion Papers Series 287, University of Bonn and University of Cologne, Germany.

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