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DOI: 10.47026/2499-9636-2023-4-22-32

Ladykova T.I.

Cluster analysis of indicators characterizing decarbonization processes in the regions of the Russian Federation

Keywords: decarbonization, quality of economic growth, regional economy, cluster analysis, indicative planning, machine learning

The article is devoted to the study of decarbonization processes in the Russian Federation based on cluster analysis using machine learning methods. The purpose of the study is to assess decarbonization processes in the subjects and federal districts of the Russian Federation. Materials and methods. The information basis of the study consists of statistical data from Rosstat for the period 2000-2021 for 82 subjects of the Russian Federation, federal districts, the cities of Moscow, St. Petersburg, Sevastopol and the Russian Federation as a whole. In the process of the proposed study, correlation and cluster analysis was carried out ("k-means" methods and determining the median indicators of each cluster). Estimate indicators of the ratio of GRP to the level of atmospheric air pollution and the level of water bodies’ pollution were used as determining indicators. Results. Based on the analysis, 7 clusters were identified, differing from each other by levels of the main aspects of decarbonization. The first cluster includes 5 subjects (brief description – maximum fresh water per capita, minimum emissions per capita, average carbonisation level), the second – 43 subjects (minimum emissions, minimum discharge and minimum carbonisation of GRP by air), the third – 8 subjects (maximum discharge and maximum carbonisation of GRP by water), in the fourth – 22 subjects (minimum of fresh water), in the fifth – 2 subjects (significant maximum of carbonisation by air and maximum positive balance between capture and emissions), in the sixth – 4 subjects (balance of capture and emissions, minimum carbonisation of GRP by water, minimum discharge and maximum emissions) and the seventh cluster included 12 subjects of the Russian Federation (maximum efficiency of water resources use). Cluster analysis has shown that about half of the subjects of the Russian Federation are characterized by minimum of emissions, minimum of discharge and minimum of GRP carbonisation by air. Conclusions. The conducted cluster analysis of decarbonization processes in the subjects of the Russian Federation makes it possible to conclude that most of the subjects are characterized by efficient use of water resources. There are also subjects with opposite extremes in air and water (maximum emissions and minimum use of fresh water per capita and vice versa). In addition, in the aspect of decarbonization of the Russian economy, it can be concluded that water resources per capita in the subjects of the Russian Federation are used more efficiently than air resources.


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About authors

Ladykova Tatiana I.
Candidate of Economics Sciences, Associate Professor, Department of Macroeconomic Policy and Strategic Management, Lomonosov Moscow State University, Russia, Moscow; Associate Professor, Department of State and Municipal Management and Regional Economy, Chuvash State University, Russia, Cheboksary (; ORCID:

Article link

Ladykova T.I. Cluster analysis of indicators characterizing decarbonization processes in the regions of the Russian Federation [Electronic resource] // Oeconomia et Jus. – 2023. – №4. P. 22-32. – URL: DOI: 10.47026/2499-9636-2023-4-22-32.