Nowcasting Euro area GDP with news sentiment: A tale of two crises
研究发现，将15家欧洲主流报纸的新闻情绪指标纳入模型，能显著提升欧元区实际GDP增长的实时预测精度，尤其在季度初期其他数据尚未发布时效果更佳。
Summary This paper shows that newspaper articles contain signals that can materially improve real‐time nowcasts of real GDP growth for the Euro area. Using articles from 15 popular European newspapers, which are machine translated into English, we create sentiment metrics that update daily and assess their value for nowcasting, comparing with competitive and rigorous benchmarks. We find that newspaper text is especially helpful early in the quarter before other indicators are available. We also find that general‐purpose sentiment measures perform better than more economics‐focused ones in response to unanticipated events and nonlinear supervised models can help capture extreme movements in growth but require sufficient training data to be effective.