The Central Bank of Russia has released the first 2025 issue of its scholarly quarterly Russian Journal of Money and Finance, featuring research on measuring trust in the central bank using social media data, improving inflation forecasts with news texts, and identifying drivers of inflation risks. One article proposes an alternative to survey-based trust measures by constructing a sentiment indicator from comments on the VK social network, which can be produced at different frequencies; short-term modelling using weekly data finds that a positive credibility shock with a two-week lag reduces inflation expectations. Another paper applies neural network text analysis to mass-media news and combines news indices with standard macro variables such as wage dynamics, the production index and crude prices, reporting higher forecast accuracy when news indices are included. A third study examines factors shaping the risk that inflation exceeds the forecast, linking higher inflation risks to wage growth and a decline in production over a one-year horizon, and to rising retail turnover and a weaker ruble over a one-month horizon.
Central Bank of Russia 2025-03-26
Central Bank of Russia publishes new Russian Journal of Money and Finance issue on social media based trust measures and news driven inflation forecasting
The Central Bank of Russia's Russian Journal of Money and Finance explores innovative methods for measuring trust in the central bank and improving inflation forecasts. Research includes using VK social network sentiment as a trust indicator, neural network text analysis for enhanced forecast accuracy, and identifying inflation risk drivers such as wage growth and currency fluctuations.