A dataset of assessing the socio-ecological-economic sustainability of Russian regions of North Asia

Published: 16 January 2024| Version 1 | DOI: 10.17632/d456526sww.1


The dataset contains information on the indicators used in assessing the consolidated socio-ecological and economic sustainability for 25 regions of North Asia for the period 2010-2020. The dataset contains: the name of the subject, a list of initial indicators, their description and orientation, the meaning of these indicators, as well as the values of the levels of economic, social and environmental sustainability obtained during the assessment, and the integral indicator of socio-ecological and economic sustainability. The dataset can be used for analysis, synthesis and evaluation of information in the course of further scientific research, as well as in the development of scientific and practical recommendations for increasing the socio-ecological and economic sustainability of territorial natural and economic systems for policymakers. The dataset was created within the framework of the State assignment of the BINM SB RAS No. AAAA-A21-121011590039-6 (0273-2021-0003).


Steps to reproduce

To systematize data on various aspects and assess the socio-ecological-economic sustainability of the territorial natural and economic systems of North Asia, this dataset was created using Microsoft Excel and Open Source DEA. The dataset contains the data (11 indicators for 25 regions for 2010–2020) used in calculating economic, social, environmental sustainability and the results of assessing the socio-ecological and economic sustainability of these territories based on the author’s methodology using a two-stage network model DEA and an integral indicator determined on the basis of a multiplicative approach. Input data used were obtained manually based on data from the Federal State Statistics Service of Russia and the Ministry of Natural Resources and Environment of the Russian Federation.


Bajkal'skij institut prirodopol'zovania SO RAN


Environmental Science, Sustainable Development, Data Envelopment Analysis, Eco-Efficiency