CC BY
1DOI: 10.29141/2658-5081-2022-23-2-3 EDN: SZNDDK JEL classification: 014, R12, R13
Valentina S. Antonyuk South Ural State University, Chelyabinsk, Russia Elena L. Kornienko South Ural State University, Chelyabinsk, Russia
Economic development of Russia's old industrial border regions
Abstract. Among the old industrial constituting entities of the Russian Federation there are the territories with middle and border location. Both types perform important functions in the national economy, however, their average gross regional product per capita is less than the average of non-old industrial regions. The article aims to hold a theoretical and methodological study of the specifics and factors of development of Russia's old industrial border regions in comparison with old industrial middle regions to identify the thrusts of modernisation of the industrial space for the former. The theories of economic development and border studies as well as the concept of old industrial regions form the methodological basis of the research. The authors apply systems approach, abstraction and generalisation, factor and comparative analysis. The paper presents a method for assessing the economic development of old industrial border regions. The employment of this method allowed (1) revealing that border regions outperform middle regions in such indicators as GRP, value of fixed assets, investments in the fixed capital per capita; (2) identifying the factors limiting GRP per capita; (3) rating old industrial regions and providing a system of suggestions for accelerating their development. The findings can be useful for federal and regional authorities for fueling the economic growth of old industrial border regions.
Keywords: old industrial regions; border regions; middle regions; economic development; GRP.
For citation: Antonyuk V. S., Kornienko E. L. (2022). Economic development of Russia's old industrial border regions. Journal of New Economy, vol. 23, no. 2, pp. 45-63. DOI: 10.29141/2658-5081-2022-23-2-3. EDN: SZNDDK.
Article info: received February 9, 2022; received in revised form February 28, 2022; accepted March 11, 2022
Introduction
Over the past decade, the global economy has undergone dramatic changes caused by a variety of reasons, such as the international economic sanction policy used as an alternative to military conflicts after the Cold War of 1947-1989 [Bergeijk, 1989; Kaempfer, Lowenberg, 2007]; the Fourth Industrial Revolution [Schwab, 2016]; new industrialisation [Silin, Animitsa, Novikova, 2017]; the COVID-19 pandemic [Schwab, Malleret, 2020; Silin, Animitsa, 2021], etc.
Global processes intensify the problems of the socioeconomic development of the constituent territories of the Russian Federation. These issues can be categorised into two groups:
1) socioeconomic inequality and instability in old industrial regions; a weak focus of old industrial economy with a high proportion of low-productivity and low-tech industries on innovation; slow entrepreneurial activity; increased negative expectations in the business sector;
2) geographical regional concentration of industry with a heterogeneous spatial socioeconomic development system and trunk infrastructure in the border regions of the Russian Federation of particular geostrategic importance with an active migration outflow heightening the risks of demographic collapse.
These trends becoming increasingly prominent necessitate examining the economic condition of old industrial regions and emphasise the relevance of studying development trends in old industrial border territories.
The implementation of the priorities of the Strategy for the spatial development of the Russian Federation for the period until 20251, both in the medium and long term, is hampered by the contradictions inherent in the old industrial regions, namely:
• differences in the structure of gross value added stemmed from of historical, climatic, geographic, and market processes;
• collisions in the structure of labour resources influenced by demographic trends causing an increase in the demographic burden on the working age population, an outflow of highly-skilled specialists, a decrease in migration inflows to the region, and negative natural population growth;
• discrepancies in the investment attractiveness resulting from differentiated economic development of old industrial border regions accompanied by a decline in the efficiency of intra-regional interaction, the trunk infrastructure and the energy sector, integration of the RF constituent territories with the centres of economic growth, renewal of fixed production assets, etc.;
1 On approval of the Strategy for the spatial development of the Russian Federation for the period until 2025: Resolution of the Government of the Russian Federation of February 13, 2019 no. 207-r. https://docs.cntd.ru/docu-ment/552378463. (In Russ.)
• deformations in innovative development based on the uneven funding of innovative infrastructure facilities due to the lack of a scientifically based strategy for innovative development of the constituent entities of the Russian Federation [Antonyuk, Korinenko, Shmidt, 2018].
The above contradictions affect the main factors of economic growth (land, labour, capital, technology) and at the same time establish the primary objectives of the strategic development of old industrial border regions.
The paper aims to perform a theoretical-methodological study of the specificities and factors in the economic development of old industrial border regions in comparison with old industrial middle regions in order to formulate practical avenues for renewing their industrial space and ramping up their socioeconomic potential.
To attain the stated purpose, the following objectives are to be accomplished:
• to systematise common and distinctive features of old industrial border regions and old industrial middle regions;
• to analyse the major factors (labour, capital, technology) of old industrial border regions that impede their economic development;
• to substantiate the avenues for accelerating the economic development of old industrial border regions in the paradigm of technological industrial renewal.
Economic development of old industrial middle regions and old industrial border regions
To complete the set research objectives, it is necessary to formulate a unified approach to interpreting the concept of 'old industrial region' (OIR), and then separate old industrial border regions (OIBRs) and old industrial middle regions (OIMRs) from the corresponding regional group.
The first attempt to comprehend the problems and successes of industry was made by Chandler [1962], who explored a number of industrial enterprises, such as DuPont, General Motors, Standard Oil Company (New Jersey), Sears, Roebuck and Company, and analysed their successes and failures when introducing innovation and the influence of social factors on the companies' economic development.
The term 'old industrial region' was conceptualised as a research category in the studies on the problems of the heavy industry functioning, which experienced a decline in the 1960s [Hudson, Sadler, 1983; Robinson, Sadler, 1984; Steiner, 1985; Carney, 1988]. Among a plethora of works devoted to the strategic management of the old industrial regions in England and Europe, the following ones are of special interest:
• research studies by Hudson and Sadler covering various issues of strategic management of old industrial enterprises [Beynon, Hudson, Sadler, 1991] and the functioning
of three nationalised industrial sectors (coal, steel and water supply) in the north-east of England [Hudson, Sadler, 1987];
• publications on organisational modernisation focused on functional integration, outsourcing and increasing employees' competence in the older industrial region of South Wales [Panditharatna, Phelps, 1995];
• work by Hohenberg [2004], who performed a historical analysis of changes in European urban economies in terms of a dual systems model combining central place and network relationships. The author highlights that the shift from older to newer industries, as well as growth in leisure and high human capital pursuits, has shifted activity away from many 19th century industrial centres and towards revitalised older cities and urbanized regions with higher amenity levels;
• Harpel's findings about the Detroit regional economy, which has been evolving from its dependence on manufacturing to a more diversified service-based economy [Harpel, 2011];
• studies by Chapman and Meliciani, who by means of both non-parametric and spatial regression analyses assessed geo-sectoral groups (urban areas, old industrialised areas and peripheral areas) in order to introduce an effective policy for restructuring new industrial regions [Chapman, Meliciani, 2018].
The next step in developing scientific thought on the topic under discussion was tracing the evolution of heavy industry based on innovation and diversification, the application of best practices founded on developments in high-tech industries and regions with the highest rates (Northern Virginia and Silicon Valley (USA); Cambridge (UK)) [Bresnahan, Gambardella, Saxenian, 2001; Todtling, Trippl, 2005], as well as the consistent implementation of industrial policy pursued by the governments of the United Kingdom [MacNeill, Bailey, 2010], Taiwan [Lee, 2006], China [Geng, Weiss, 2007; Cao, Xi, Zeng, 2008] and countries in Latin America (Brazil, Argentina, Uruguay) [Bertola, Porcile, 2006].
The Russian economists delve into the problems of functioning and developing old industrial regions. Let us note the most significant research trends and works:
• evolution of the fundamental theoretical approaches to determining the substance of old industrial regions [Granberg et al., 1998; Animitsa et al., 2001; Nesterova, 2006; Glonti, 2008; Maltsev, Mordvinova, 2016; Sorokina, Latov, 2018];
• issues and challenges faced by regions or territories, which are depressed or stagnant due to the progress of science and technology and changes in demand [Granberg et al., 1998] (these issues are investigated from the standpoint of cyclic-wave methodology [Animitsa, Tertyshnyy, 2001]), as well as those shifted the structure of the regional economy at different stages of industrial development [Gorkina, 2019; Akberdina, Romanova, 2021], including due to an increase in imports [Sakharova, Samarina, Stenkina, 2014];
• problems of the Russian industry development in the economy of old industrial regions [Uskova et al., 2017], including the evolution of these regions in the context of the transformational recession of the 1990s [Sorokina, Latov, 2018; Akberdina, Romanova, 2021] and institutional management of technological future [Kulagina, Rakhmeeva, Ly-senko, 2020], etc.;
• regions of old technological waves in the context of new industrial development [Tatarkin, Romanova, 2013; Romanova, Akberdina, Bryantseva, 2013].
As part of the evolution of theoretical and methodological views on the concept of 'old industrial region', three key approaches have been introduced to identify the old industrial regions of the Russian Federation.
According to the historical-geographical approach, OIRs are characterised by a high concentration of industries, the structure of which started forming as early as the 18th century. Such OIRs include territories of the Russian Federation that are at various stages of industrial and post-industrial evolution [Uskova et al., 2017; Lukin, Leonidova, 2017; Proskurnova, 2019; Mitrofanova, Chernova, 2019].
According to the administrative-territorial approach, OIRs cover the constituent entities of the Russian Federation that are part of the federal districts (for example, the Urals Federal District [Mordvinova, 2020] and Central Federal District [Sorokina, Latov, 2018]) and have certain interregional ties with them.
The economic approach is based primarily on the dependence of the RF constituent entity on a specific industry, as well as on an inflexible institutional structure, and products gradually leaving the market [Maltsev, Mordvinova, 2016; Kulagina, Rakhmeeva, Lysenko, 2020; Mordvinova, 2020].
In accordance with the abovementioned approaches, we have identified the RF constituent entities falling into the category of OIRs (a total of 41 entities, excluding the Khanty-Mansiysk Autonomous Okrug and the Yamalo-Nenets Autonomous Okrug), of which 24 entities are OIMRs and 17 entities are OIBRs (Figure 1).
Old industrial middle regions Old industrial border regions
Fig. 1. Old industrial regions of Russia
The OIMRs include the oblasts of Vladimir, Vologda, Ivanovo, Kaluga, Kemerovo, Kirov, Kostroma, Lipetsk, Moscow, Nizhny Novgorod, Novgorod, Orel, Ryazan, Sverdlovsk, Tambov, Tver, Tomsk, Tula, and Yaroslavl, as well as Perm krai, the Udmurt Republic, the Republics of Bashkortostan, Komi, and Khakassia. The OIBRs embrace the oblasts of Arkhangelsk, Belgorod, Bryansk, Volgograd, Voronezh, Kursk, Leningrad, Magadan, Murmansk, Omsk, Rostov, Sakhalin, Smolensk, Tyumen, and Chelyabinsk, as well as Krasnoyarsk krai, and the Republic of Karelia.
Method for assessing the economic development of old industrial border regions of the Russian Federation
The proposed method is premised on the following principles:
1) the old industrial border regions are identified according to the results of the studies by Uskova et al. [2017], Proskurnova [2019], Mitrofanova and Chernova [2019], So-rokina and Latov [2018];
2) the old industrial border regions (17 constituent entities of the RF) were analysed through comparing them with the old industrial middle regions (24 constituent entities of the RF);
3) all the OIBR metrics are interpreted from the position of, firstly, the indicator that characterises the main outcome of their economic activity (gross regional product per capita), and, secondly, the major groups of factors affecting it and reflecting the aspects of 'labour / capital / technology'.
In our previous works [Antonyuk, Kornienko, 2016], we have found that the driving forces in the border regions were the peculiarities of a general and specific order and described by a combination of specific features (Table 1).
The method for analysing the economic development of the old industrial border regions involves comparing them with the old industrial middle regions and is implemented in four stages.
During Stage 1, there is provided the dynamics of the main resulting economic indicator (gross regional product per capita) and the indicators showing the change in the key economic factors in the OIBRs in comparison with the OIMRs, which include:
• the value of fixed assets per capita;
• annual average population numbers;
• investment in the fixed capital per capita.
At Stage 2, the correlation between gross regional product per capita and the indicators reflecting the economic factors in the OIBRs and the OIMRs is examined.
A comparative analysis of these groups of regions is carried out in accordance with the following modules.
Table 1. Specificities of the OIMRs and OIBRs socioeconomic development analysis
Features OIMRs OIBRs
Common features Geographical anc climatic conditions
Level of the productive forces development
Industries of regional specialisation
Level of human potential development
Characteristic features of forms of ownership
Level of innovation susceptibility
Single-industry economic base
Distinguishing features State policy of accelerated industrialisation
Level of technological development
Vulnerability of the region's economy to environmental challenges
Specific features Specific nature of cooperation with the countries within the former Soviet Union and beyond, as well as the presence of stable interregional ties with border regions Geographical position and specifics of the socioeconomic development of countries bordering the region (developed, developing, transitioning economies, etc.)
Type of transport infrastructure (rail, sea, road, etc.)
The state of the production infrastructure (customs service network; service and production buildings; terminals, special control facilities; buildings, warehouses for customs equipment, etc.)
Level of involvement in international trade and cooperation
Source: own representation based on [Antonyuk, Kornienko, 2016; Mordvinova, 2020].
Module 1. Indicators characterising the development level of the economic factor 'labour':
• the share of the economically active population, %;
• employment rate of the working age population, %.
Module 2. Indicators characterising the flow of investment resources in the analysed groups of the RF constituent entities (the economic factor 'capital'):
• the value of fixed assets (gross book value) per capita, thousand rubles;
• investment in the fixed capital per capita, rubles;
• the share of investment coming to reconstruction and modernisation in the total volume of investment in the fixed capital, %.
Module 3. Indicators characterising the amount of innovation efforts and the level of technological development (the economic factor 'technology'):
1) in innovation activity:
• the level of innovation efforts of organisations, %;
• the share of organisations implementing technological innovation, % in the total number of the surveyed organisations;
2) in digital environment [Gryaznova, Antonyuk, Kornienko, 2019]:
• the share of organisations using personal computers, % in the total number of the surveyed organisations in the corresponding RF constituent entity;
3) in the field of technological development:
• the share of products in high-tech economic sectors in GRP;
• advanced technologies developed in the constituent entities of the Russian Federation, units;
• advanced technologies used in the constituent entities of the Russian Federation, units.
At Stage 3, for each Russian region ranked among the OIBRs (i) a composite ranking of indicators CRoibr (CRn) is obtained, which characterise the development level of economic factors:
CRn = nyll1xl2xl2x...xln^ (1)
where Ih„n are indicators (ranks) describing the development level of the economic factors (labour / capital / technology) in the RF constituent territory (i) in comparison with the rest of the OIBRs in the group.
At Stage 4, the 'problem field' is identified, i.e., the matrix demonstrating, on the one hand, the problem areas of the old industrial border regions that impede their economic development, and, on the other, stimulating factors that positively affect the economic development of the OIBRs. Constructing such a matrix allows these regions to present the entire set of priority problems and factors, and their identification and resolution will relieve tension in the economic development of the old industrial border regions of the Russian Federation.
Economic development of the OIBRs in the Russian Federation:
The analysis results
Initially, of all constituent entities of the Russian Federation, only 41 regions were selected, which, based on the chosen criteria, belonged to the old industrial regions. Of them, 17 territories were old industrial border regions having land and/or sea border with the countries within the former Soviet Union and beyond.
According to the proposed method, we first compared the absolute indicators of the OIBRs and the indicators of the OIMRs in dynamics for the period of 2000-2019, namely:
• the key indicator characterising the performance of business activity in the region (gross regional product per capita);
• indicators proving the importance of the main factors affecting the previous criterion (labour / capital / technology).
The comparative analysis revealed the following trends for 2000-2019 (Figure 2).
Rubles 700 000 600 000 500 000 400 000 300 000 200 000 100 000 0
OIMRs OIBRs
OOOOOOOOOOT—IT—I T—I T—I T—I T—Ii—IT—II—IT-H
OOOOOOOOOOOOOOOOOOOO (NiN(N(N<N(NcN(N(NfN(Nr<l(NtNfN(N(N(NrvlfN
a) GRP per capita
Thousand rubles
2 500
2 000 1 500 1000 500
OIMRs OIBRs
OOOOOOOOOOl—I^T-HIt—Ii—li-HT—IT—IT-HIT-HI OOOOOOOOOOOOOOOOOOOO <N<NfN(N(N(N(NtN(N(N(NiNr<lr<l<Nrslr<l(N(NrN
b) value of fixed assets per capita
Thousand people
2 000 1900 1800 1 700 1600 1 500
OIMRs OIBRs
es m
in vo
oo o\
O^CSfOTtiinvOt^OOONO
OOOOOOOOOOT—1 T—IT-HIT—It-HI ,—IT—IT—IT-H OOOOOOOOOOOOOOOOOOOO (N<N(NfNr<ir<l<NC<lfN<N(N(N(NfNcN(NfN(N<N(N
c) annual average population
Rubles
3 000 000 2 500 000 2 000 000 1 500 000 1 000 000 500 000 0
— OIMRs OIBRs
tNcOTfinvOtvOOOS
O'-ifNcnTfinvOtvOOOSO'-i OOOOOOOOOO^H^ OOOOOOOOOOOOOOOOOOOO (N<N(N<N(N<N(N(NfN(NfN(N(N<N(NCNiNfN(N(N
d) investment in the fixed assets per capita Fig. 2. Dynamics of the socioeconomic indicators of the Russian old industrial middle regions (OIMR) and old industrial border regions (OIBR) in 2000-2019, average values1
1 Source: own calculations based on data from the Federal State Statistics Service of the RF. https://rosstat.gov.ru/.
In terms of the factors affecting the performance of the regional economy, we can state that:
• annual average population calculated as the mean value for all the OIBRs was significantly lower than that for the OIMRs during the whole period under consideration;
• the value of fixed assets per capita tended to exceed similar indicators in the old industrial middle regions since 2005;
• the average value of investment in fixed assets per capita in the border regions is lower than that in the middle ones.
At the same time, the average value of GRP per capita in 2019 was as follows:
• all constituent entities of the Russian Federation (85) - 646.1 thousand rubles;
• OIRs (41 entities of the RF) - 569.8 thousand rubles;
• OIMRs (24 entities of the RF) - 472.5 thousand rubles;
• OIBRs (17 entities of the RF) - 707.2 thousand rubles;
• entities of the RF (44) excluded from the analysis - 811.2 thousand rubles.
It is obvious that the OIBRs are lagging behind the territories not ranked as old industrial ones in terms of GRP per capita. This fact indicates the relevance of identifying the factors that hamper the economic development of the OIBRs. Therefore, at the next stage, a correlation analysis was performed in order to establish the depth of the relationship between GRP per capita in the OIRs, OIMRs, OIBRs and the indicators characterising the economic development factors (labour / capital / technology) in these regions (Table 2).
Table 2. Correlation indicators showing the dependence of GRP per capita in the OIRs, OIMRs and OIBRs on the economic factors (labour / capital / technology), 2019
Indicators OIRs, total OIMRs OIBRs
Number of the RF constituent entities
41 24 17
Indicators characterising the development of the economic factor 'labour'
Economically active population, % 0.7086 0.3656 0.7681
Employment rate of the working age population, % 0.1234 -0.0681 0.3701
Indicators characterising the development of the economic factor 'capital'
Value of fixed assets (gross book value) per capita, thousand rubles 0.8705 0.8415 0.9335
Investment in the fixed capital per capita, rubles 0.9336 0.7271 0.9503
Table 2 (concluded)
Indicators OIRs, total OIMRs OIBRs
Number of the RF constituent entities
41 24 17
Share of investment coming to reconstruction and modernisation in the total volume of investment in the fixed capital by the RF entities, % -0.4648 -0.2718 -0.5404
Indicators characterising the development of the economic factor 'technology'
Innovation activity
Level of innovation efforts of organisations, % -0.1496 -0.0746 -0.1409
Share of organisations implementing technological innovation, % in the total number of the surveyed organisations -0.1762 0.0453 -0.2124
Digital environment
Share of organisations using personal computers, % in the total number of the surveyed organisations in the corresponding RF constituent entity 0.1376 -0.1307 0.2652
Technological development
Share of products in high-tech economic sectors in GRP, % -0.4924 -0.1815 -0.6826
Share of advanced technologies developed in the constituent entities of the Russian Federation, % -0.0019 0.4257 -0.1974
Share of advanced technologies used in the constituent entities of the Russian Federation, % -0.1131 0.3672 -0.3762
Source: own calculations based on data from Rosstat. https://rosstat.gov.ru/.
Note: The bold italics tag emphasises the correlation indicators pointing to a strong relationship between GRP per capita in the OIRs, OIMRs and OIBRs and the economic factors (labour / capital / technology).
As shown in Table 2, among the factors stimulating the economic development of all OIRs, as well as the OIMRs and the OIBRs are the following:
• the level of the economically active population;
• the value of fixed assets (gross book value) per capita;
• investment in the fixed capital per capita.
At the same time, the factors that impede the economic development of the OIRs, OIMRs and OIBRs or do not have an effect on it are:
• the share of investment coming to reconstruction and modernisation in the total volume of investment in the fixed capital;
• the level of innovation efforts of organisations;
• the share of organisations implementing technological innovation in the total number of the surveyed organisations.
The old industrial border regions also have quite a specific set of stimulating and limiting factors.
Among the drivers of their economic development are:
• the factors of the group 'labour': the level of the economically active population and the employment rate of the working age population;
• the factors of the group 'capital': the value of fixed assets (gross book value) per capita; investment in the fixed capital per capita.
It should be noted that none of the factors of the 'technology' group identified in the method (characterising innovation activity, digital environment, technological development) has a stimulating effect on the old industrial border regions.
The following factors hamper the economic development of the OIBRs or exert no effect on it:
• the factors of the group 'capital': the share of investment coming to reconstruction and modernisation in the total volume of investment in the fixed capital;
• the factors of the group 'technological development': the share of products in hightech economic sectors in the region's GRP; the share of advanced technologies developed in the region; the share of advanced technologies used in the region.
The employment of absolute indicators of the economic development factors made it possible to categorise the old industrial border regions using the ranking method (Table 3).
The leaders in the composite index are the Chelyabinsk, Belgorod, Magadan, Rostov, Voronezh oblasts and the Tyumen oblast (excluding autonomous districts) ranked from 1st to 6th place, respectively. The regions with the least favourable features, such as the Bryansk, Omsk, Volgograd and Kursk oblasts and the Republic of Karelia, occupy the lowest-ranking positions.
Table 3 shows the crisis developments of certain factors in each region (grey indicates a negative situation, blue indicates a satisfactory situation, and dark blue indicates a positive situation). Relying on this information, authorities can establish the most relevant areas for resolving problems.
The results of the analysis of the composite economic factors allow us to arrive at the next four conclusions.
Table 3. Composite ranking of the indicators characterising the development level of the economic factors (labour / capital / technology) in the OIBRs, 2019
RF constituent entity Composite ranking by the indicators characterising the development levels of the economic factors Overall composite ranking
labour capital technology
Arkhangelsk oblast (excluding autonomous districts) 16 5 12 12
Belgorod oblast 4 7 2 2
Bryansk oblast 14 16 9 13
Volgograd oblast 13 6 14 15
Voronezh oblast 10 11 4 5
Krasnoyarsk krai 5 12 8 10
Kursk oblast 7 14 16 16
Leningrad oblast 9 4 7 8
Magadan oblast 1 3 6 3
Murmansk oblast 6 2 13 7
Omsk oblast 11 17 11 14
Republic of Karelia 17 10 15 17
Rostov oblast 12 15 3 4
Sakhalin oblast 3 1 17 9
Smolensk oblast 15 9 10 11
Tyumen oblast (excluding autonomous districts) 8 8 5 6
Chelyabinsk oblast 2 13 1 1
Source: own calculations based on data from Rosstat. https://rosstat.gov.ru/.
1. The positive value of the factors was found in the Belgorod, Voronezh, Leningrad and Magadan oblasts, the Krasnoyarsk krai, as well as in the Tyumen oblast (excluding autonomous districts).
2. The most negative state of economic development in terms of the composite factor 'labour' was observed in the Volgograd, Bryansk, Smolensk oblasts, the Republic of Karelia, and in the Arkhangelsk oblast (excluding autonomous districts).
According to our assumption, the main thrusts of their transformations should be:
1) proactive assistance of employment centres, providing:
• support and help to not only the unemployed, but also to those who are at risk of dismissal;
• assistance with temporary employment;
• additional retraining opportunities for the population to generate employment in the 'vacated' niches and industries;
• organisation of internal labour mobility with the simplest procedures for registration and residence in other subjects of the Russian Federation in need of labour resources;
• free consultations on the development of private business, etc.;
2) targeted social payments for the most vulnerable groups of population, as well as incentive and compensation measures for employers when hiring these categories of citizens;
3) assistance with young people's employment, their active involvement in the progressive industry of the domestic market (creative professions, IT industry, etc.), grant support and participation of promising young people in science in order to develop and increase human capital.
3. A very negative economic situation in terms of the economic factor 'capital' is observed in the Omsk, Bryansk, Rostov, Chelyabinsk and Kursk oblasts.
The stimuli to the economic development in these regions should be:
• the policy on the development of local production, especially for key sectors of the national economy, through subsidies, grants, tax preferences, etc.;
• introduction of effective tools for additional capitalisation of regional industrial development funds (for example, tax-exempt bonds (income tax), coupon yield, long-term loans at preferential interest rates, compensatory grants for developments in the application of import substitution technologies in industry and agriculture, etc.);
• financing and support of transport and logistics infrastructure, especially in the constituent entities of the Russian Federation bordering the EAEU countries and foreign countries friendly to Russia, etc.
4. The negative value of the 'technology' factor in the border regions was revealed in the Sakhalin, Murmansk, Kursk and Volgograd oblasts and in the Republic of Karelia.
The main possibility of accelerating the economic development of these Russian regions is to support the country's ideology - "Scientific and technological independence". This implies the implementation of a stimulating policy in terms of the development of high-tech industries in the border regions that are focused on vivid foreign economic activity and have the shortest possible foreign trade transportation leg
(for example, the formation of free economic zones for foreign trade, tax preferences for foreign trading companies, etc.).
These measures will intensify the economic development of the old industrial border regions of the Russian Federation, thus helping to ensure its national security.
Conclusion
The problems of old industrial regions development are widely debated by academics in Russia and abroad. At the same time, as indicated in the literature review, most researchers, when studying the factors influencing the economic growth of these regions, do not take into account their geographical and territorial peculiarities.
It is topical to analyse the economic development of the OIBRs in Russia due to the significance of their geographical position for the country's economic security, as well as due to the great length of their borders. The theoretical-methodological study of the development factors in comparison with the development factors of the old industrial middle regions in Russia allows, using composite assessments, examining the driving forces of a general and specific order to produce recommendations for building up the regional economic potential. Therefore, the composite ranking was based on the indicators characterising the development level of the economic factors (labour / capital / technology), reflecting the main trends in the functioning of the OIBRs and determining their principal strategic interests.
The current trends that create special external conditions presumably need to be studied further, which would indicate a comprehensive research of the special features and factors of the economic situation in the OIBRs and the OIRs. However, the proposed method for assessing the economic development of the old industrial border regions in the Russian Federation is based on an express analysis of key indicators that display the problem areas, which impede economic growth, negatively affect the quality of life and the formation of human capital, and also lead to a sustained technological decline.
The results of the analysis of the economic factors' composite values can be used to develop strategies for the socioeconomic development of the studied regions of the Russian Federation and the development of relevant industries until 2030.
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Information about the authors
Valentina S. Antonyuk, Dr. Sc. (Econ.), Prof., Head of Economic Theory, Regional Economics, State and Municipal Governance Dept., South Ural State University, 76 Lenina Ave., Chelyabinsk, 454080, Russia
Phone: +7 (351) 267-90-09, e-mail: antvs@list.ru
Elena L. Kornienko, Cand. Sc. (Econ.), Associate Prof., Associate Prof. of Customs Dept., Associate Prof. of Economic Theory, Regional Economics, State and Municipal Governance Dept., South Ural State University, 76 Lenina Ave., Chelyabinsk, 454080, Russia Phone: +7 (351) 267-93-32, e-mail: kornienkoel@susu.ru
© Antonyuk V. S., Kornienko E. L., 2022
