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Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments

Author

Listed:
  • Gerardin Mathilde,
  • Ranvier Martial.

Abstract

In the context of the Banque de France’s monthly business survey, this document presents the main findings of the textual analysis of business leaders’ comments. First, the richness of these data is illustrated via an elementary sentiment index and the identification of the main social movements since 2009 by means of keywords. Then, the article presents two statistical applications whose reproducibility is discussed. The first one, applied to the 2018 yellow vests and the 2019 strikes, aims to estimate the impact on GDP of an event whose effect is unequivocal. The second, backed by the study of Brexit, aims to characterize, using a supervised learning model and word vectors, the effects of a complex event with multiple impacts.

Suggested Citation

  • Gerardin Mathilde, & Ranvier Martial., 2021. "Enrichment of the Banque de France’s monthly business survey: lessons from textual analysis of business leaders’ comments," Working papers 821, Banque de France.
    • Handle: RePEc:bfr:banfra:821
    as

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    File URL: https://publications.banque-france.fr/sites/default/files/medias/documents/wp821.pdf
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    References listed on IDEAS

    as
    1. Matthew Gentzkow & Bryan Kelly & Matt Taddy, 2019. "Text as Data," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 535-574, September.
    2. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
    3. Nicholas Bloom & Philip Bunn & Scarlet Chen & Paul Mizen & Pawel Smietanka & Gregory Thwaites, 2019. "The Impact of Brexit on UK Firms," NBER Working Papers 26218, National Bureau of Economic Research, Inc.
    4. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    5. Aprigliano, Valentina & Emiliozzi, Simone & Guaitoli, Gabriele & Luciani, Andrea & Marcucci, Juri & Monteforte, Libero, 2023. "The power of text-based indicators in forecasting Italian economic activity," International Journal of Forecasting, Elsevier, vol. 39(2), pages 791-808.
    6. Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
    7. Mogliani, Matteo & Darné, Olivier & Pluyaud, Bertrand, 2017. "The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey," Economic Modelling, Elsevier, vol. 64(C), pages 26-39.
    8. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    9. Ardia, David & Bluteau, Keven & Boudt, Kris, 2019. "Questioning the news about economic growth: Sparse forecasting using thousands of news-based sentiment values," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1370-1386.
    10. Larsen, Vegard H. & Thorsrud, Leif A., 2019. "The value of news for economic developments," Journal of Econometrics, Elsevier, vol. 210(1), pages 203-218.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Textual Analysis; Business Survey; Sentiment Index; Keywords; Word Vectors; Brexit; Social Movements.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis

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