MATHEMATICAL FOUNDATIONS OF TOOLS FOR ANALYZING INFLATION RISK FACTORS
Abstract and keywords
Abstract (English):
The study uses the quantile regression methodology in combination with a local projection model to analyze the impact of macroeconomic and financial shocks on various areas of the distribution of inflationary indicators in the Russian economy. Empirical results show that the key factors in increasing inflationary pressure are the acceleration of nominal income growth, the expansion of consumer demand expressed through retail trade, as well as the devaluation of the national currency and a reduction in industrial production.It has been established that additional signals about the growth of inflationary risks may come from the geopolitical sphere, as well as from the field of debt financing, where a decrease in credit spreads on debt instruments may indicate excess liquidity. The analysis revealed the nonlinear nature of the effect of the exchange rate: its effect on consumer prices increases at the upper quantiles of the inflationary distribution. At the same time, in conditions of high inflation, there is an asymmetry - devaluation has a stronger effect on prices than revaluation of a comparable value.An important conclusion of the work is the conclusion about the limited effectiveness of monetary policy in containing extreme inflationary scenarios. An increase in the key rate demonstrates less effectiveness in reducing the likelihood of spikes in inflation compared to the impact on its medium-term expectations. This indicates the need for the Bank of Russia to apply comprehensive measures combining monetary instruments with macroprudential and structural solutions to manage inflationary risks in the face of supply shocks.

Keywords:
statistical analysis, mathematical tools, sampling analysis, exploratory analysis, statistics
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References

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