Krasnodar, Krasnodar, Russian Federation
Krasnodar, Krasnodar, Russian Federation
The article analyses the impact of various economic and structural factors on the development of agriculture in Russian regions based on statistical data and a variety of economic and mathematical methods. The research uses calculation of relative and average values, multivariate grouping, and regression analysis. The cluster analysis revealed two groups of regions in terms of gross value added. The first group includes regions with highly developed agriculture significantly exceeding the indicators of the second one. This is confirmed by the results of regression analysis. Investments in fixed assets turned out to be the most significant factor affecting gross value added. Additionally, research forecasts a variable with fluctuations in independent characteristics by simulation modelling. It demonstrates the resilience or vulnerability of the agricultural sector to changes in the economic environment. The research results have practical significance for development of state support measures and increase the efficiency of the agrarian sector in Russian regions, providing food security and sustainable economic development.
agriculture, clusters, cluster analysis, regression model, economic model, simulation modelling
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