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Nowcasting GDP Growth by Reading the Newspapers

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  • Clément Bortoli, Stéphanie Combes, Thomas Renault

Abstract

[eng] GDP statistics in France are published on a quarterly basis, 30 days after the end of the quarter. In this article, we consider media content as an additional data source to traditional economic tools to improve short term forecast / nowcast of French GDP. We use a database of more than a million articles published in the newspaper Le Monde between 1990 and 2017 to create a new synthetic indicator capturing media sentiment about the state of the economy. We compare an autoregressive model augmented by the media sentiment indicator with a simple autoregressive model. We also consider an autoregressive model augmented with the Insee Business Climate indicator. Adding a media indicator improves French GDP forecasts compared to these two reference models. We also test an automated approach using penalised regression, where we use the frequencies at which words or expressions appear in the articles as regressors, rather than aggregated information. Although this approach is easier to implement than the for¬mer, its results are less accurate.

Suggested Citation

  • Clément Bortoli, Stéphanie Combes, Thomas Renault, 2018. "Nowcasting GDP Growth by Reading the Newspapers," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 505-506, pages 17-33.
  • Handle: RePEc:nse:ecosta:ecostat_2018_505-506_2
    DOI: https://doi.org/10.24187/ecostat.2018.505d.1964
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    References listed on IDEAS

    as
    1. Fondeur, Y. & Karamé, F., 2013. "Can Google data help predict French youth unemployment?," Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
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    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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