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Evaluation of Sustainable Development Indicators for Regions of Russia E ISSN 1075-7007, Studies on Russian Economic Development, 2018, Vol. 29, No. 2, pp. 124–134. © Pleiades Publishing, Ltd., 2018. Original Russian Text © E.A. Tret’yakova, M.Yu. Osipova, 2018. REGIONAL PROBLEMS Evaluation of Sustainable Development Indicators for Regions of Russia E. A. Tret’yakova* and M. Yu. Osipova Perm State National Research University, Perm, Russia *e-mail: [email protected] Received May 25, 2017 Abstract⎯It has been shown how static and dynamic characteristics could be used for a comparative assess- ment of social, environmental, and economic development, as well as the development balance in social, eco- nomic, and ecological spheres. The proposed methodological toolkit has made it possible to identify problem areas and stably manifested dynamic disproportions in the investigated regions, which require corrective actions in order to ensure sustainable development. DOI: 10.1134/S1075700718020144 Instrumentation for assessing sustainable development We used the following social indicators: of regions. This study covers the following group of com- 1. per capita gross regional product; pared regions: Perm krai; Sverdlovsk, Chelyabinsk, 2. monthly average per capita income of the popu- Nizhny Novgorod, and Samara oblasts; the Republic of lation; Tatarstan; and the Republic of Bashkortostan.1 3. Gini ratio; Interregional comparisons were conducted using 4. unemployment rate calculated according to the the indicators that most clearly characterize the state ILO methodology, i.e., the ratio of the number of of the social, economic, and environmental spheres, unemployed of a certain age group to the size of labor as well as those available in official statistical reporting force for the same age group; in the regional context.2 5. consumer spending per capita per month; We used the following economic indicators: 6. population density, i.e., the number of inhabi- 1. industrial production index; tants per 1000 km2 of the region’s territory; 2. per capita turnover of organizations; 7. share of the population with cash income below 3. balanced financial result (profit minus loss) of subsistence level; organizations' activities calculated on per capita basis; 8. life expectancy at birth; 4. percentage of loss-making enterprises; 9. total area of living quarters per person; 5. full per capita accounting value of fixed assets; 10. total morbidity, i.e., the number of registered 6. depreciation of fixed assets; diseases in patients diagnosed for the first time in their lives per 1000 people; 7. volume of innovative goods, works, and services calculated on per capita basis; 11. the number of registered crimes per 100000 people; 8. internal costs of research and development cal- culated on per capita basis; 12. human development index. 9. labor productivity index; We used the following environmental indicators: 10. real accrued average monthly salary of an 1. the volume of production and consumer waste employee in relation to the previous period; utilization and treatment calculated on a per capita basis; 11. average annual share of the employed in the economy in the total number of economically active 2. the entrapment of air pollutant emissions from population. stationary sources calculated on a per capita basis; 3. current costs of environmental protection calcu- 1 To ensure the correctness of the comparison, we selected lated on per capita basis; regions with comparable conditions of development for eco- 4. reforestation calculated on a per capita basis; nomic and geographic characteristics. 2 The study is based on the data of the Federal State Statistics Ser- 5. the discharge of contaminated sewage into sur- vice: http://www.gks.ru. face water bodies calculated on per capita basis; 124 EVALUATION OF SUSTAINABLE DEVELOPMENT INDICATORS 125 6. emissions of pollutants into the atmospheric air from social) are group indices that characterize the level of stationary sources calculated on a per capita basis; dynamic balance of indicators in each component. 7. the volume of production and consumer waste The similarity measure calculated for all components generation calculated on a per capita basis; is an integrated dynamic index (Idin) that characterizes the degree of social, environmental, and economic 8. the volume of circulating and successively used balance of the regional system development. If a half water calculated on a per capita basis. or more than half of the rate-based characteristics of The group indices of indicators for each region the indicators are ordered in accordance with the ref- were calculated according to the formula erence model (Idin ≥ 0.5), then the level of balance is n characterized as sufficient (high). If less than a half of GXn= ∑ , (1) the rate-based characteristics of the indicators are jSi i=1 ordered in accordance with the reference model (Idin < 0.5), the level of balance is estimated to be low. where Gj is the group index of sustainable development for the jth component (economic, environmental, or Integration of static and dynamic estimates in the social), X are the standardized values for the ith indi- matrix of comprehensive assessment of the region's Si sustainable development (Fig. 1) made it possible to cator calculated as the ratio of the actual and reference identify four types of regions by combining the level of (maximum or minimum) values of this indicator in the development in the statics (Ist - axis of ordinates) and considered regions, and n is the number of indicators the level of socioecological and economic balance in used to evaluate this component. in dynamics (Idin – abscissa axis ). Group indices take values of 0–1 and enable gen- eral comparative characterization of the achieved level Regions belonging to the Type 1 are characterized for each individual component of sustainable develop- by a significant difference between the actual and best ment. The final comprehensive assessment of the level values of the indicators for the static measurements, as of socioecological and economic development of the well as the large-scale divergence of the reference and region is defined as actual modes of the system's functioning in dynamics. Type 2 is characterized by attaining a high level of 3 development albeit accompanied by unbalanced per- = 3 formance of indicators. Type 3 represents the state, IGst ∏ j, (2) j=1 which is optimal in terms of sustainable development as the values of most indicators are either the best or where Ist is the integrated static index of the region’s close to those and the actual performance of most of sustainable development. the rate-related characteristics of indicators are con- The values of group and integral indices in the sistent with their reference dynamics in terms of coor- range of 1.0–0.75 were considered to be fairly favor- dinated ordering. Type 4 is characterized by a high able for the region. Values of indices below 0.75 were level of proximity of the reference and actual modes of considered to be required management decisions the system functioning from the viewpoint of the aimed at raising the level of economic and social dynamic balance of the rate-related characteristics of development of the region while maintaining and the indicators albeit combined with a significant devi- improving the quality of the environment. ation of the actual values of sustainable development In order to compare the dynamic characteristics of indicators from their best values. regional development, we used the method of dynamic Calulation results. The proposed methodological standards. The dynamic standards are a set of indica- toolkit was used to compare the indicators of sustain- tors ordered by change rates such that the long-term able development of Perm krai and a group of compa- maintenance of this order ensures the best mode of rable regions. Over 2005–2014, the positions of Perm functioning for the economic system [1]. The method krai and the regions compared with it were predomi- of dynamic standards was proposed in 1980 [2]. Later, nantly concentrated in the type-4 quadrant (see it was used by different authors in various spheres (see, Appendix, Fig. 1). At the same time, it should be e.g., [3–7]). noted that positive dynamics was observed in Nizhny To assess the degree of proximity between the ref- Novgorod and Sverdlovsk oblasts, while in the Repub- erence and actual modes of the system functioning, a lic of Tatarstan their positions shifted towards the similarity measure is calculated, i.e., a coefficient that type-3 quadrant. shows the share of coincidences of the ordered ratios The positions of the considered regions in the of the characteristics of the actual dynamics with the matrix for the economic component are reflected in ordered ratios of the rate-based characteristics of the the Appendix, Fig. 2. The data indicate that, from the reference dynamics. The detailed consideration of the viewpoint of the economic component, the positions methodology for calculating the similarity measure is of the Perm krai are mainly concentrated in the type-3 presented in [8]. quadrant. During the studied period, Perm krai Similarity measures for each component of sus- demonstrated the best results for indicators such as the tainable development (economic, environmental, and balanced financial result of organizations and the per STUDIES ON RUSSIAN ECONOMIC DEVELOPMENT Vol. 29 No. 2 2018 126 TRET’YAKOVA, OSIPOVA Ist 1.0 Type 2 Type 3 High level of development High level of development, High with unbalanced dynamics balanced dynamics of indicators
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