Template-type: ReDIF-Article 1.0
Author-Name: Anastasia Matevosova
Author-Email: nastya.m.2003@yandex.ru
Author-Workplace-Name: Lomonosov Moscow State University; Institute of Economics of the Russian Academy of Sciences
Title: Modelling Trust in the Central Bank Using Sentiment Analysis
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.
Classification-JEL: C22, C55, C58, C45, C82, D8, E52, E58
Keywords: trust, central bank, indicator, sentiment analysis, text sentiment analysis, inflation expectations, monetary policy
Journal: Russian Journal of Money and Finance
Pages: 3-25
Volume: 84
Issue: 1
Year: 2025
Month: March
DOI:
File-URL: https://rjmf.econs.online/upload/iblock/b2c/f07t5dq0abqjbamkj1v6rdd735frzy2j/Modelling-Trust-in-the-Central-Bank-Using-Sentiment-Analysis.pdf
Handle: RePEc:bkr:journl:v:84:y:2025:i:1:p:3-25