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Assessment of Clarity of Bank of Russia Monetary Policy Communication by Neural Network Approach

Alina Evstigneeva () and Mark Sidorovskiy ()
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Alina Evstigneeva: Bank of Russia
Mark Sidorovskiy: Bank of Russia

Russian Journal of Money and Finance, 2021, vol. 80, issue 3, 3–33

Abstract: Inflation targeting requires clear and transparent central bank’s communication. Analysts and market participants understand it as a broad list of information disclosed by the central bank. The general public understands it rather as the ability of a central bank to speak and explain its decisions in a plain language. In recent decades, monetary authorities in many countries have made significant progress in this direction. However, there has been no research on the quality of communication for the Bank of Russia. This paper aims to create a tool for automated evaluation of the readability of the Bank of Russia’s monetary policy communication, taking into account the available experience of linguistic and textual analysis, including machine learning methods, as well as to provide recommendations for its improvement. This can contribute to improving the effectiveness of the Bank of Russia communication on monetary policy, which is vital for its credibility, anchoring inflation expectations, and predictability of the regulator’s decisions.

Keywords: monetary policy; communication; text analysis; neural networks; NLP (search for similar items in EconPapers)
JEL-codes: D83 E52 E58 (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:bkr:journl:v:80:y:2021:i:3:p:3-33

DOI: 10.31477/rjmf.202103.03

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