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What’s in a headline? News impact on the Brazilian economy

Author

Listed:
  • Gustavo Romero Cardoso
  • Marcio Issao Nakane

Abstract

The purpose of this paper is to explore the impact of textual data on the Brazilian economic cycle. Utilizing a dataset of articles from †Valor Econômico†newspaper spanning from July 2011 to December 2022, we employ the topic model Latent Dirichlet Allocation (LDA) to transform this textual data into a series of monthly topic proportions. From this output, we have developed two news indices, each with distinct methodologies but sharing the objective of assessing the influence of news topics on asset prices. We incorporate these indices into a structural VAR model to differentiate between news and noise shocks and to analyze their effects on macroeconomic variables. Our results reveal that news shocks, as captured by the news indices, significantly impact both asset prices and a range of macroeconomic indicators. Both news and noise shocks are found to be crucial in explaining a considerable proportion of the variance in asset prices over short and longterm periods, underscoring the pivotal role of news information in market dynamics.

Suggested Citation

  • Gustavo Romero Cardoso & Marcio Issao Nakane, 2024. "What’s in a headline? News impact on the Brazilian economy," Working Papers, Department of Economics 2024_12, University of São Paulo (FEA-USP).
    • Handle: RePEc:spa:wpaper:2024wpecon12
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    More about this item

    Keywords

    News; textual data; Latent Dirichlet Allocation; Brazilian business cycles;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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