Nowcasting GDP Growth by Reading Newspapers

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Date

2018

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Persée

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MESR

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Copyright PERSEE 2003-2024. Works reproduced on the PERSEE website are protected by the general rules of the Code of Intellectual Property. For strictly private, scientific or teaching purposes excluding all commercial use, reproduction and communication to the public of this document is permitted on condition that its origin and copyright are clearly mentionned.



Sujets proches En

GDP Domestic product, Gross

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Clément Bortoli et al., « Nowcasting GDP Growth by Reading Newspapers », Economie et Statistique (documents), ID : 10.24187/ecostat.2018.505d.1964


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Résumé En

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 former, its results are less accurate.

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