Economic uncertainty and natural language processing; The case of Russia

The paper proposes a method of constructing text-based country-specific measures for economic policy uncertainty. To avoid problems of translation and human validation costs, we apply natural language processing and sentiment analysis to construct such measures for Russia. We compare our measure with that developed earlier using direct translations from English and human validation. In this comparison, our measure does equally well at evaluating the uncertainty related to key events that affected Russia between 1994 and 2018 and performs better at detecting the effects of uncertainty in Russia’s industrial production.