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economic measures applied to the Russian Arctic. The study's relevance stems from the need for a comprehensive assessment of trends and outcomes associated with the use of such measures under current conditions. The goal of the research is to develop a method for measuring the performance of the Russian Arctic as a preferential treatment zone. The proposed method employs a system of indicators that capture various aspects of the measures' effectiveness, ranking methods, and the creation of integral indices designed to identify regional characteristics. Additionally, correlation analysis, specifically Spearman's rank correlation coefficient, is used to demonstrate the complexity and co-directionality of processes within regional economies, which influence the effectiveness assessments. The article provides integral evaluations of using preferential economic measures in the regions of the Russian Arctic. The Chukotka Autonomous Okrug ranks first in terms of implementation intensity, followed by the Republic of Karelia and the Arkhangelsk Region. The Murmansk Region occupies third place, while the Nenets and Yamalo-Nenets Autonomous Okrugs are positioned at the bottom. This ranking does not reflect the overall level of economic development in these Arctic regions but highlights the specific contributions of processes driven by preferential treatment. The correlation analysis between the indicators reveals the complex impact of preferential treatment on economic processes across the Arctic regions. The study's exploration of co-directionality through integral indices shows a spatial mismatch due to variations in the relationships between indicators across different regions. The scientific novelty of the research lies in the development and testing of this methodology, as well as the identification of regional specificities in implementing preferential economic measures. The practical significance of this research lies in its justification for the need to systematically monitor regional specificities in the implementation of preferential economic measures. This monitoring can serve as the foundation for developing targeted local measures with higher economic efficiency.
Volkov et al. (Tue,) studied this question.