Analysis of reproduction dynamics in Russian agriculture during the sanctions period

Achieving the priorities of ensuring the country’s food security, expanding the export potential of agriculture, as well as maintaining economic stability and social development under sanctions directly depends on the nature and effectiveness of reproduction processes in agriculture. During the sanctions the importance of reproduction in Russian agriculture increases, as the demand for domestic products increases due to the decrease in imports, there is a need to switch to domestic seeds, components and other resources. It is the expanded reproduction that provides agriculture with additional investment resources that can be directed to the development of the industry. To solve the problem of import substitution it is necessary to stimulate expanded reproduction in agriculture through the development and implementation of domestic breeding achievements, high-tech technologies, personnel training, and digitalization of the industry. The article analyzes the reproduction processes in Russian agriculture for the sanctions period from 2014 to 2022 on the basis of assessing the dynamics of key indices of agricultural production and reproduction factors; the nature of the dynamics of agricultural production is studied and the trend of development of this indicator is revealed; the characteristic of the reproduction processes and their effectiveness over time periods are characterized. The results of the study have shown that Russian agriculture, in the period of sanctions pressure adapts quite successfully to the external environment and with a certain improvement in the conditions of the reproduction process can not only maintain the existing trend, but also develop at a faster pace. For this purpose, it is necessary to provide the industry with sustainable investments that reduce imports of agricultural products, increase labor productivity, intensify production, attract qualified labor resources, and greenize production. As research methods, the article uses special statistical methods such as modeling the trend of a time series, analytical alignment and the moving average method, analysis of autocorrelation functions, construction of correlation and regression models, nonlinear dynamic models, etc.

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