RuEn

Journal section "Science, technology and innovation studies"

Scenario Modeling and Forecast of the Degree of Depreciation of Fixed Assets at Manufacturing Enterprises in Russia’s Regions

Naumov I.V., Nikulina N.L.

Volume 15, Issue 4, 2022

Naumov I.V., Nikulina N.L. (2022). Scenario modeling and forecast of the degree of depreciation of fixed assets at manufacturing enterprises in Russia’s regions. Economic and Social Changes: Facts, Trends, Forecast, 15(4), 155–171. DOI: 10.15838/esc.2022.4.82.10

DOI: 10.15838/esc.2022.4.82.10

Abstract   |   Authors   |   References
In a deteriorating geopolitical situation and under the pressure of sanctions on the Russian economy, its manufacturing enterprises are facing significant restrictions in the import of high-tech equipment and materials necessary for technical re-equipment and modernization of the fixed assets they use. These restrictions contribute to increasing the degree of their deterioration and will do so in the future as well. The hypothesis of our study consists in the assumption that the dynamics of fixed assets depreciation at enterprises is influenced not only by the volume of attracted investments, but also by other factors, and that the degree of their impact in different groups of regions is differentiated. The aim of the work is to design forecast scenarios that would show the changes in the degree of fixed assets depreciation at manufacturing enterprises, taking into account the differentiated influence of factors. The study presents a methodological approach based on statistical and regression analysis using panel data and autoregressive integrated moving average (ARIMA) model to identify factors affecting the dynamics of fixed assets depreciation at manufacturing enterprises in various regions and design a system of forecast scenarios for its changes in the future. We group the regions according to the degree of depreciation of fixed assets of manufacturing enterprises (we identify groups of regions with an extremely high level of fixed assets depreciation, and the levels above and below the Russian average). Using regression models we identify the differentiated influence of factors on the dynamics of fixed assets depreciation: in the first and third groups of regions, the key factor in increasing depreciation is the difficult financial situation of enterprises; in the second group – insufficient volume of attracted investments in fixed assets. For each group of regions, autoregressive modeling of the dynamics of these factors is carried out using a moving average to form the most likely forecast scenarios for changes in the degree of fixed assets depreciation at manufacturing enterprises until 2024. As a result of forecasting, we identify regions with the most likely dynamics of further increase in the degree of depreciation of fixed assets of enterprises; these regions should become a priority in obtaining state support for the implementation of industrial policy in Russia

Keywords

forecasting, depreciation of fixed assets, manufacturing industry, regression analysis, Russia’s regions, scenario modeling, ARIMA modeling

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