Forecasting GDP in Europe with textual data

B-Tier
Journal: Journal of Applied Econometrics
Year: 2024
Volume: 39
Issue: 2
Pages: 338-355

Authors (3)

Luca Barbaglia (European Commission) Sergio Consoli (not in RePEc) Sebastiano Manzan (not in RePEc)

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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 dataset includes over 27 million articles for 26 major newspapers in five 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.

Technical Details

RePEc Handle
repec:wly:japmet:v:39:y:2024:i:2:p:338-355
Journal Field
Econometrics
Author Count
3
Added to Database
2026-01-24