Author
Listed:
- Valentin S. Batomunkuev
(Baikal Institute of Nature Management SB RAS, 670047 Ulan-Ude, Russia
These authors contributed equally to this work.)
- Bing Xia
(Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
These authors contributed equally to this work.)
- Bair O. Gomboev
(Baikal Institute of Nature Management SB RAS, 670047 Ulan-Ude, Russia)
- Mengyuan Wang
(College of Resources and Environmental Economics, Inner Mongolia University of Finance and Economics, Hohhot 010070, China)
- Yu Li
(Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)
- Zehong Li
(Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)
- Natalya R. Zangeeva
(Baikal Institute of Nature Management SB RAS, 670047 Ulan-Ude, Russia)
- Aryuna B. Tsybikova
(Baikal Institute of Nature Management SB RAS, 670047 Ulan-Ude, Russia)
- Marina A. Motoshkina
(Baikal Institute of Nature Management SB RAS, 670047 Ulan-Ude, Russia)
- Aleksei V. Alekseev
(Baikal Institute of Nature Management SB RAS, 670047 Ulan-Ude, Russia)
- Tumun Sh. Rygzynov
(Baikal Institute of Nature Management SB RAS, 670047 Ulan-Ude, Russia)
- Suocheng Dong
(Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)
Abstract
This paper proposes an innovative research algorithm “measurement—pattern—driving force—synergy” that determines the eco-efficiency of 83 Russian federal subjects (2000–2019) using the Slacks-Based Measure (SBM) model with non-desired outputs (incorporating comprehensive input indicators such as water resources and electricity input, and dual non-desired outputs of waste gas and wastewater). Combined with hot spot analysis, a gravity center model, and panel Tobit regression, we reveal the temporal-spatial evolution and driving mechanisms of eco-efficiency in resource-based economies. The research finds that the overall eco-efficiency of Russia is at a medium level and shows a dynamic correlation with the economic development stage. In the early stage of the period under review, there was a high degree of synergy, but the efficiency declined during the period of rapid economic growth. Later, it rebounded somewhat in tie with technological progress. Spatially, it presents a special pattern of low efficiency in the western European industrialized regions and high efficiency in the Arctic and Far East peripheral regions, reflecting the spatial heterogeneity of resource-dependent economies and the survival-constrained efficiency feature. The analysis of influencing factors indicates that per capita GDP has a significant positive driving effect on eco-efficiency, but the expansion of residents’ consumption, the improvement of education level and the dependence on foreign trade all have inhibitory effects, highlighting the path dependence of the current growth model on the structure of resource consumption. The research suggests that Russia should implement differentiated spatial governance in the future, promote the green transformation of consumption and trade structures, and strengthen the ecological orientation of the education and scientific research system to achieve a fundamental transformation of regional sustainable development from survival constraints to innovation-driven.
Suggested Citation
Valentin S. Batomunkuev & Bing Xia & Bair O. Gomboev & Mengyuan Wang & Yu Li & Zehong Li & Natalya R. Zangeeva & Aryuna B. Tsybikova & Marina A. Motoshkina & Aleksei V. Alekseev & Tumun Sh. Rygzynov &, 2026.
"Pathways to Green Transition for a Resource-Based Economy: Insights from the Eco-Efficiency Dynamics of Russian Regions,"
Sustainability, MDPI, vol. 18(6), pages 1-17, March.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:6:p:3071-:d:1899962
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