FORECASTING INFLATION AT THE REGIONAL LEVEL IN THE SHORT TERM USING A VECTOR AUTOREGRESSION MODEL

  • E.A. Dolgikh Central Bank of the Russian Federation, Veliky Novgorod, Russia
  • T.V. Kudryashova Yaroslav the Wise Novgorod State University, Veliky Novgorod, Russia
DOI: https://doi.org/10.34680/BENEFICIUM.2023.2(47).41-56

Abstract

The paper presents the stages of constructing a vector autoregression model (VAR model) for forecasting inflation at the regional level and implements a short-term inflation forecast for the Novgorod region. For this purpose, the selection of possible indicators (20 units) for the VAR model was carried out, the need for their use was economically justified. As a result, 4 indicators were used for the VAR model. The explanatory variables included the following ones: Price indices of producers of agricultural products sold by agricultural organizations (products and services of agriculture and hunting); Retail turnover of non-food products, %; Average monthly real accrued wages of employees of organizations, %. The exogenous variable was the Index of the real exchange rate of the ruble to the US dollar, %. The necessity of using dummy variables to eliminate the impact of the identified shocks in the dynamics of inflation was also justified: the impact of the shocks of 2014–2015, when the Bank of Russia announced a floating exchange rate and started targeting inflation, was eliminated, as well as the shock of March 2022, when geopolitical instability intensified, which resulted in a short-term weakening of the ruble and a surge in consumer demand.

The resulting VAR model was found to be consistent after carrying out all the necessary econometric tests. The model was verified. Based on the simulated VAR model, a short-term inflation forecast for the Novgorod region was constructed. Subsequently, it was decided to adjust the resulting forecast series of inflation based on the available data of the non-monetary inflation factor.

It is worth noting that the developed VAR model is suitable only for the subject of the Russian Federation, selected in the study, since each region of Russia is unique, therefore, the selection of indicators should be carried out for each territory individually. At the same time, the algorithm for constructing a forecasting model is universal and can be applied to various territories. As a result, it has been concluded that it is important to construct an inflation forecast, since its impact must be taken into account in financial planning by absolutely all economic agents at all hierarchical levels including the government, business and citizens.

Keywords:inflation, vector autoregressive model, inflation forecasting, region, socio-economic development

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About the Authors

Evgeny A. Dolgikh – Head of the Economic Department of the Novgorod Region Branch of the North-Western Main Directorate of the Central Bank of the Russian Federation, Veliky Novgorod, Russia. E-mail: dolgikhea@live.com
Tatiana. V. Kudryashova – Cand. Sci. (Economics), Docent; Associate Professor, Head of the Department «The School of Project Learning», Yaroslav-the-Wise Novgorod State University, Veliky Novgorod, Russia.
E-mail: tatyana.kudryashova@novsu.ru. SPIN РИНЦ 5220-2148. ORCID 0000-0003-4056-3855. ResearcherID F-2694-2019

For citation: Dolgikh E.A., Kudryashova T.V. Forecasting Inflation at the Regional Level in the Short Term using a Vector Autoregression Model // Beneficium. 2023. Vol. 2(47). Pp. 41-56. (In Russ.). DOI: 10.34680/BENEFICIUM.2023.2(47).41-56

Published
2023-06-30
Issue
No 2 (2023)
Section
TRANSFORMATION OF SOCIAL AND ECONOMIC SYSTEM