Year: 2025
Type: article
Abstract: This study presents an examination of the predictive power of narrative reports from German economic institutes beyond traditional quantitative forecasts in anticipating economic recessions and directional changes in the business cycle. I transform qualitative narratives into quantitative sentiment scores using four different dictionaries and methods and use fixed-effect logistic regression to analyse their impact. To evaluate model performance, I use the Area under the Receiver Operating Characteristic Curve (AUROC) to compare models with versus without sentiment scores. Additionally, I employ DeLong’s test and bootstrapping to test the significance of AUROC improvements. Furthermore, I explore the potential of combining multiple sentiment scores to enhance forecasting accuracy. The results show that sentiment scores significantly enhance forecasting accuracy. This suggests that narrative information provides valuable insights beyond quantitative forecasts alone.
Author: Tim Köhler
Institution: Merseburg University of Applied Sciences
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,190
OpenAlex ID: W4416100598