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Main Authors: Barbaglia, Luca, Consoli, Sergio, Manzan, Sebastiano
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2401.07179
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author Barbaglia, Luca
Consoli, Sergio
Manzan, Sebastiano
author_facet Barbaglia, Luca
Consoli, Sergio
Manzan, Sebastiano
contents We evaluate the informational content of news-based sentiment indicators for forecasting Gross Domestic Product (GDP) and other macroeconomic variables of the five major European economies. 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 macroeconomic variables and their predictive content is robust to controlling for other indicators available to forecasters in real-time.
format Preprint
id arxiv_https___arxiv_org_abs_2401_07179
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Forecasting GDP in Europe with Textual Data
Barbaglia, Luca
Consoli, Sergio
Manzan, Sebastiano
Computational Engineering, Finance, and Science
Artificial Intelligence
Computation and Language
91B62, 91B84, 91B86
We evaluate the informational content of news-based sentiment indicators for forecasting Gross Domestic Product (GDP) and other macroeconomic variables of the five major European economies. 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 macroeconomic variables and their predictive content is robust to controlling for other indicators available to forecasters in real-time.
title Forecasting GDP in Europe with Textual Data
topic Computational Engineering, Finance, and Science
Artificial Intelligence
Computation and Language
91B62, 91B84, 91B86
url https://arxiv.org/abs/2401.07179