Modelling Trust in the Central Bank Using Sentiment Analysis

Anastasia Matevosova ()
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Anastasia Matevosova: Lomonosov Moscow State University; Institute of Economics of the Russian Academy of Sciences

Russian Journal of Money and Finance, 2025, vol. 84, issue 1, 3-25

Abstract: This study proposes a unique method that allows to create, using the sentiment analysis of textual data, a convenient tool to measure the dynamics of trust in the central bank. An indicator of public trust in the Bank of Russia in the 2014-2023 period is built based on the methodology proposed. The relationship between trust and inflation expectations is analysed using an autoregressive model of a moving average with generalised autoregressive conditional heteroskedasticity in residuals (ARMA-GARCH) with exogenous variables. It is revealed that, in the short term, positive trust shocks can reduce inflation expectations, increasing the effectiveness of monetary policy, but do not affect the volatility of inflation expectations. The indicator is proposed to be used in the development of decisions on the Bank of Russia's communication and monetary policy.

Keywords: trust; central bank; indicator; sentiment analysis; text sentiment analysis; inflation expectations; monetary policy (search for similar items in EconPapers)
JEL-codes: C22 C45 C55 C58 C82 D8 E52 E58 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bkr:journl:v:84:y:2025:i:1:p:3-25

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