Construction and analysis of uncertainty indices based on multilingual text representations
利用多语言词嵌入和主题建模方法，为德国、俄罗斯和乌克兰构建经济政策不确定性指数，并验证这些指数对经济活动具有格兰杰因果关系。
The work by Baker et al. (2016), who propose a dictionary based method and estimate the level of economic policy uncertainty (EPU) based on the occurrence of specific terms in ten leading newspapers in the USA, is among the first ones to detect the potential of text data in economic research. Following this line of research, this paper proposes automated approaches to construction of EPU indices for different countries based on newspapers’ texts. Multilingual fastText word embeddings, (S)BERT embeddings, and a novel multilingual topic modeling approach are used to construct EPU indices for Germany, Russia, and Ukraine. It is shown that constructed EPU indices based on multilingual word embeddings are Granger causal to the economic activity in all of the considered countries.