Russian Journal of Money and Finance: Inflation expectations, effects of policy rate, and power of AI
The Bank of Russia presents this year’s third issue of the Russian Journal of Money and Finance. The new issue includes five articles about how market participants estimate inflation, why industries and regions respond differently to the central bank’s actions, how economists explore financial cycles, and what experts think of the transforming power of artificial intelligence (AI). The authors suggest new research approaches and summarise important discussions of recent years.
How to measure financial market inflation expectations
Financial market inflation expectations are a critical factor to be taken into account when analysing the effectiveness of monetary policy and inflation risks. Therefore, it is essential to assess them. Evgeniy Tymchenko (HSE University) introduces a single measure of financial market inflation expectations integrating inflation estimates that are priced into government bond yields. This allows assessing the sustainability of financial market inflation expectations and their anchoring at the Bank of Russia’s inflation target. The measurements show that, by early 2026, market participants’ long-term inflation expectations approached the Bank of Russia’s 4% inflation target.
Why the effects of a key rate change differ across industries...
The sectoral effects of a key rate change are heterogeneous as they depend on an industry’s debt burden, its demand for credit, its proximity to the final consumer, regulated tariffs, and price flexibility. Viktor Antonenko (HSE University) and Ivan Darovskii (Bank of Russia) show that the strongest effects of a key rate increase are observed in construction, trade, manufacturing, and services, whereas electricity and gas supply, water supply, and agriculture demonstrate the weakest responses. This heterogeneity, however, does not alter the overall anti-inflationary pattern of a key rate increase in all industries.
... and regions
Another source of the heterogeneity of responses to key rate changes is variation in district banking concentration. Daniil Spiridonov (New Economic School) finds that Russian regions characterised by the highest concentration of the banking sector exhibit stronger short-run responses of corporate lending rates and investment to the key rate, while heterogeneity at longer horizons is weaker.
What indicators best describe financial cycles
Economic booms are followed by downturns, and therefore, it is essential to identify indicators that would help detect the risks of a decline promptly. The paper by Viktor Vorozhtcov and Yulia Vymyatnina (European University at St Petersburg) presents an overview of Russian and foreign studies on credit and financial cycles. The authors show that a universal set of variables and a unified methodology for macroeconomic forecasting based on financial cycle indicators have not yet been developed.
What AI will change in the economy
Alexander Eliseev and Ivan Krylov (Bank of Russia) summarise the studies presented at a workshop organised by the Bank of Russia, the New Economic School, and the National Research University Higher School of Economics. The workshop focused on the impact of AI on the economy. The participants discussed how large language models affect human behaviour and macroeconomic forecasts and how AI influences society, economic growth, the labour market, inequality, the financial market, and monetary policy.
All the papers are available on the Russian Journal of Money and Finance website.