Evaluation of the key rate impact on the inflation rate using vector autoregressive models

The article analyzes the relationship between the key rate value, inflation rate, and output gap. Studying the intricacies of this relationship is a cornerstone for developing an effective economic policy of the Russian Federation, making justified investment decisions, and gaining a deeper understanding of the forces shaping economic outcomes. Vector autoregressive models and a vector error correction model are used to evaluate the relationship. The objective of the study is to analyze the relationship between the key rate dynamics, inflation rate, and output gap based on empirical data for the Russian Federation. Monthly data on the key rate and the inflation rate were used in the research. Based on the index of goods and services output by basic types of economic activity, the monthly value of the output gap was estimated. The sample includes data from 2014 to 2024. All calculations and graph plotting were carried out using the R language and the corresponding libraries. Empirical data and calculations allow us to draw the following conclusions: The time series of the key rate and inflation are non-stationary, or rather, DS-series I(1), and the output gap is represented by a stationary series I(0). The time series of the key rate and inflation are cointegrated, which makes it possible to build regression models without any fear of false correlation influence. Since the time series under consideration have the same integration order and are cointegrated, a VAR model for series levels or a VECM model for level differences can be built to analyze the relationship between the variables under study, including the output gap as an exogenous variable. The VAR coefficients of the model mostly characterize the short-term relationship between variables, while the VECM reflects longterm dynamics. The analysis of the VAR coefficients of the model gives reason to suspect the presence of the reverse causality effect. The Granger causality analysis showed that the use of data on the dynamics of the key rate is appropriate when predicting the dynamics of the inflation rate and the output gap. In turn, the output gap is a causal variable for inflation and the key interest rate. The combination of the results of the evaluation of the VAR model and the Granger causality indicates a high probability of the reverse causality effect, which in turn indicates that the Central Bank in its decisions regarding the value of the key rate is guided not by the actual, but by the expected values of inflation. The IRF and FEVD analysis showed that the key rate affects the inflation rate, and the output shock affects the key rate and inflation. The key rate has a significant impact on inflation, and in the short term this impact may be positive. This phenomenon may be related to time lags in the transmission mechanism of monetary policy and the effects of inflationary expectations and costs. In addition, it may indicate that the Central Bank is focused not only and not so much on current inflation rates as on its projected dynamics, which creates an inverse causality effect in the short term. A flexible policy may be a reasonable approach, assuming relatively short periods of high interest, taking into account the expected time lag of its impact. This approach will minimize negative consequences for macroeconomic indicators, while maintaining the effectiveness of anti-inflationary measures. The relevance of these issues highlights the need for further research to clarify the mechanisms of interaction between the key rate and inflation, as well as to find the optimal duration of its application. The authors declare no conflicts of interests. The authors declare no conflicts of interests.

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