Abstract
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.
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