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Modelling Trust in the Central Bank Using Sentiment Analysis

Author

Listed:
  • Anastasia Matevosova

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

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.

Suggested Citation

  • Anastasia Matevosova, 2025. "Modelling Trust in the Central Bank Using Sentiment Analysis," Russian Journal of Money and Finance, Bank of Russia, vol. 84(1), pages 3-25, March.
  • Handle: RePEc:bkr:journl:v:84:y:2025:i:1:p:3-25
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    References listed on IDEAS

    as
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    Cited by:

    1. Mirzat Ullah & Kazi Sohag & M. Kabir Hassan, 2026. "Exploring the relationship between bank liquidity risk and the media sentiment index via big data technology: a study during the COVID-19 pandemic and the Russia–Ukraine conflict," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 12(1), pages 1-18, December.

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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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