Does Central Bank Talk Matter for Forecasting? Evidence From Speeches of the BoE , ECB , and Fed
本文用LDA方法提取英、欧、美央行官员演讲的主题，发现加入演讲信息能降低多国宏观经济和金融变量的预测误差，2008年金融危机后效果更明显。
ABSTRACT This paper explores the information content of the untargeted narratives of the Bank of England (BoE), the European Central Bank (ECB), and the Federal Reserve (Fed) and whether it has the potential to improve forecasting performance. We apply the Latent Dirichlet Allocation (LDA) method to extract topics from the corpus of text data. We then evaluate the impact of these central bank officials' speeches on macroeconomic and financial variables forecasting from 1997 to 2018. Our results suggest that the forecasting model, incorporating information from speeches, produces estimates with a lower forecasting error for several variables in the UK, the EU, and the US. For certain variables, the forecast improvement is more pronounced after the global financial crisis of 2008.