Forecasting GDP in Europe with Textual Data

45 Pages Posted: 1 Sep 2021 Last revised: 1 Jul 2022

See all articles by Luca Barbaglia

Luca Barbaglia

European Commission-Joint Research Centre

Sergio Consoli

European Commission-Joint Research Centre

Sebastiano Manzan

City University of New York, Baruch College - Zicklin School of Business - Department of Economics and Finance

Date Written: June 28, 2022

Abstract

We evaluate the informational content of news-based sentiment indicators for forecasting the Gross Domestic Product (GDP) of the five major European economies. The sentiment indicators that we construct are aspect-based, in the sense that we consider only the text that is related to a specific economic aspect of interest. In addition, the sentiment is fine-grained as each word is assigned a score in the interval [-1, 1]. Our data set includes over 27 million articles for 26 major newspapers in 5 different languages. The evidence indicates that these sentiment indicators are significant predictors to forecast GDP and their predictive content is robust to controlling for macroeconomic and survey confidence indicators available to forecasters in real-time. We also discuss the application of the sentiment indicators during the COVID-19 pandemic and demonstrate their relevance in nowcasting GDP.

Keywords: economic forecasting, COVID-19, nowcasting, sentiment analysis, text mining

JEL Classification: C22, C55, F47

Suggested Citation

Barbaglia, Luca and Consoli, Sergio and Manzan, Sebastiano, Forecasting GDP in Europe with Textual Data (June 28, 2022). Available at SSRN: https://ssrn.com/abstract=3898680 or http://dx.doi.org/10.2139/ssrn.3898680

Luca Barbaglia (Contact Author)

European Commission-Joint Research Centre ( email )

Joint Research Centre, European Commission, Rue du

Sergio Consoli

European Commission-Joint Research Centre ( email )

Joint Research Centre, European Commission, Rue du
Brussels, Brussels 1050
Belgium

Sebastiano Manzan

City University of New York, Baruch College - Zicklin School of Business - Department of Economics and Finance ( email )

17 Lexington Avenue
New York, NY 10010
United States

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