Typological features of economic development in Russian regions under the conditions of development of continuous education

Автор: Kroshilin Sergei Viktorovich, Leonova Zhanna Konstantinovna, Medvedeva Elena Ilinichna, Ivanina Vera Mikhailovna

Журнал: Economic and Social Changes: Facts, Trends, Forecast @volnc-esc-en

Статья в выпуске: 6 (42) т.8, 2015 года.

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In the modern conditions the socio-economic paradigm is changing, on the one hand, due to the transition to knowledge economy and, on the other hand, due to the need to develop innovation that determine competitiveness and the development level of national economies in the world. It is obvious that the progressive upgrade and the improvement of production processes (change in technological modes) can not be implemented without the increase in the level of human capital in the society and the enhancement of potential and qualification of the workforce. These changes largely depend on the education system. In almost all world countries there is an active process of modernization and change in the system of training. New forms and approaches appear, for example lifelong education (concept “Lifelong education”), informal forms of learning, self-education, etc. Without the development of these approaches it is not possible to become a competitive state in changing social, political and economic environment...

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Typology of regions, lifelong learning, economic development of regions, classification of regions, socio-economic development of regions

Короткий адрес: https://sciup.org/147223793

IDR: 147223793 | DOI: 10.15838/esc/2015.6.42.4

Текст научной статьи Typological features of economic development in Russian regions under the conditions of development of continuous education

The modern society changes its socioeconomic development paradigm of the country’s development due to the transition to knowledge economy. The world economy determines the competitiveness of national economies depending on the level of innovation and knowledge, which, in turn, stimulates the growth of investment flows.

Today education is the most important factor in national security and welfare of the country and every citizen. Under the pressure of new conditions the rational choice is complicated; it will probably result in the impossibility for an individual to assess socio- economic prospects of his/her development correctly. J. Rawls considers this situation as a “veil of ignorance” [5]. The choice of the society as a whole and the individual in the short term can be evaluated as true in the context of obtaining short-term advantages and non-productive in the long term [3]. The rejection of education in a specific period of time can become more efficient as resources are re-distributed in favor of increasing the income of a person, but in the long term it can lead to the loss of professional competitiveness of an individual and the society as a whole [4]. The costs of educational services are repaid over several production cycles. The period of acquired knowledge validity can be defined as a payback period of investment in education and the change in the length of demand for knowledge leads to the containment of professional competence level growth [2].

According to the World Bank assessment, human capital, which includes education, accounts for 64% of the total wealth of the country [6]; in the countries, such as Germany, Japan and Switzerland, – for 80% of the total capital. Education is one of the most important components of human capital, with universal coverage and quality of services being taken into account.

A number of international organizations have their own ranking of countries by education level. The index (Education Index), regularly published by the UN with the help of UNESCO, is most famous. For this structure it is one of the components of the overall index of human development (Human Development Index), which indicates the development of countries in general. According to the 2014 data, our country ranged 57th among the countries with a high human development index (Belarus – 53, Latvia – 48, Lithuania – 35th, Georgia – 79, Ukraine – 83). By education index in 2013 Russia ranged 36th (Belarus – 21, Latvia – 24, Lithuania – 8, Georgia – 40, Ukraine – 30).

However, it should be understood that this well-known index characterizes not so much the quality of education, as its affordability. Ratings of public organizations are much more interesting from the point of view of an individual, choosing foreign higher educational institutions. There is the following example: Universitas 21 ranking [12], formed by the consortium of leading academic universities in the world. Its compilation involves the overall efficiency of education systems in different countries, as well as their popularity among foreign students. The overall assessment of the country is influenced by 4 main categories [12]:

– available educational resources (25% in the rating);

– educational environment (15%);

– cooperation in education (20%);

– performance (40% rating).

Hence, the leaders of the rating are differently distributed. In 2013 the first five places went to the U.S., Sweden, Switzerland, Canada and Denmark. New Zealand, leading in the UN rating, ranged 14th, Russia – 32th.

Obviously, to some extent the quality of education depends on the level of expenditure on its development. According to the World Bank: World Development Indicators 2014 (Ranking of world countries by level of expenditure on education) [13], the Russian Federation ranges 98th (4.1% of the national revenue), Belarus – 83 (4.5%), Latvia – 42 (5.7%), Lithuania – 46 (5.6 %), Georgia – 119 (3.2%), Ukraine – 57 (5.3%). The given data are calculated as at 2010–2012 (published in 2014). However, according to the Federal Treasury, in Russia over the past 10 years the expenditure on education has been slightly more than 11% on average (in relation to the consolidated budget expenditures). Despite the fairly serious investment in domestic education during this period, the competitiveness on the world market of educational services is very low. Physico-mathematical and chemical training areas are the only exceptions.

The studies of foreign (E. Denison, R. Easterling, U. Schweke, H. Haynes) and domestic (S.Y. Glazyev, N.D. Kondrat’ev, N.M. Rimashevskaya) scientists suggest that the population with a higher level of education makes the economy more productive.

In addition, such important attributive characteristics of human capital, as a degree of qualification, competence of employees and management personnel, i.e. so-called

“soft factors” for economic growth [1], have dualistic nature and are institutional determinants along with capital and labor in innovative economy.

The educational process is constantly being interpreted and the new social-economic paradigm will be transformed, creating the prerequisites for formation of the continuous professional education system ( table ). The current pace and the quality characteristics of scientific and technological progress involve the development of cognitive and intangible production factors; it, in turn, actualizes modernization of work organization and forecasting the consequences of scientific and technological progress.

Evolution of the educational process paradigm

Paradigm	Paradigm 1	Paradigm 2		Paradigm 3
Paradigm	Scientific	System		Network
Type of an educational organization	Scientifically managed	Open		“Skilled” (effective)
Type of an educational organization	Scientifically managed	Adaptive	Entrepreneurial	“Skilled” (effective)
Period	the 1960–1970s	the 1980s	the 1990s	the beginning of the 21st century
Structure of an organization	Hierarchical, divisional, functional	Adaptive (matrix), organic	Global, business, small	Network, adhocracy
Type of a graduate	Generalist	Innovator	Entrepreneur	Managing knowledge
Core competencies	Broad professional knowledge	Ability to adapt	Ability to leadership and changes	Ability to leadership and education
Dominant programs	Canonical	Flexible	Customer-oriented programs	Lifelong education program
Educational institutions	Classic university	Diversified university	Corporate university, training and consulting center	Virtual university, training centre
Dominant departments	Departments	Programs-departments (matrixes)	Designers-programs-departments	Research, training networks, training centers
Source: compiled by Zh.K. Leonova.

Obviously, the assessment of the prospects for medium-and long-term development of the national economy in modern conditions requires the definition of the role of the continuous education system, which is a significant element of intellectual capital formation in the country, in general, and regions, in particular.

The demand on the modern labor market depends not only on the scale of a given activity, but also on the level of labor resources quality. Collectively, formal and informal social determinants that affect aggregate demand on the labor market are associated with institutional changes [7], which illustrate a hypothesis about the change of external factors in one sphere and the manifestation of institutional change in another. On the basis of the concept of technological mode substitution, we can assume that the emergence of fundamentally new means of production will affect institutional factors in the labor market development.

Reforming of the Russian education system is very protracted and starts to “folter”. The main task of education is to provide and create conditions for person’s selfdetermination and self-realization in the society, as the acquired education level will give a person the opportunity to adapt to social and economic conditions and improve the society and raise the country’s competitiveness. Reforming of the system in the country compels the regions to take a fresh look at the problem of optimization of educational institutions their number and quality. The modern approach to the acquisition of knowledge requires the development of new forms of learning, such as self- and non-formal education, that become crucial in implementing the concept of lifelong learning.

Considering the described above, we can state that the lifelong learning concept involves adaptation to the changes in professional activity and formation of the ability to perform a social and economic role in a modern man. Upgrade of Russian economy, implementation of import substitution and refusal from the “raw material” development vector are impossible without analysis of the education system and clear idea of the age-sex population dynamics, which determines not only the nature and characteristics of the labor market, but also investment and innovative attractiveness of the regions. It is necessary to take into account differentiation of Russian regions in many areas and different approaches to their typology (classification).

Having the variety of models of socioeconomic development of Russian regions, we should understand that the level of education is heterogeneous. In the framework of this research (RFH grant No. 15-02-00066 “Lifelong education in the conditions of recession and demographic transition as a factor to increase competitiveness of Russia”) the article analyses economic development of some territories of the Russian Federation with different education levels and demographic structures of the population.

The analysis includes various classifications of the regions [8, 9, 10, 11]. The classification by innovation and investment characteristics is most relevant in terms of import substitution and necessity to develop own production in the regions. Using the classification of Russian regions by innovation indicator we can single out 3 types [8].

1. Static regions. These subjects are at the stage of economic growth that occurs within the existing technological system. Motivation for the emergence of a new trajectory of economic and technological development in such regions is weak or absent. As a rule, the necessity of transition to innovative way of development meets resistance from the current (existing) system.
2. Innovatively developing regions (or growing regions). These subjects form innovative approaches to the replacement of elements of the old system. There is a tendency to develop new intra-regional relations. In such regions the development of investment processes requires support from the federal center.
3. Depressed regions – these regions are at the low stage of socio-economic development, they are not able to make some significant changes and are focused on getting support from the state.

To pursue our task, we modify the method to classify regions by investment indicator, based on the findings of domestic scientists [9, 10, 11]. According to this approach, the regions are divided into 7 categories: “locomotives”, “supportive regions”, “growth poles” and “growth points”, “problematic regions”, “regions with undecided prospects” and “regions of special attention”.

Our analysis of investment attractiveness of Russian regions at the moment of time makes it possible to group them as follows [9, 10, 11]:

1. “Locomotives”, “supportive regions” , and “growth poles” are subjects that have high investment potential and considerable internal resources (31 regions, such as the Moscow Oblast, Moscow, the Rostov Oblast, etc.). Thus, they can develop without significant assistance from the federal government. If the whole Russia had the same socio-economic indicators and political preferences, as in “locomotives”, it would join the most advanced countries in the world.
2. “Growth points” are regions with small population, insignificant economic power, low investment risks, which in the next 10-15 years will “hit a ceiling” in their development (8 subjects, such as the Lipetsk Oblast, the Republic of Mordovia, etc.).
3. “Problematic regions” . Increasing the investment attractiveness, they can even “jump” over “growth points” and be among steadily-growing areas of Russia (13 regions, such as the Bryansk Oblast, the Komi Republic, etc.).
4. The largest group – “regions with undecided prospects” – is completely dependent on skills and professionalism of the regional authorities (20 regions, such as the Murmansk Oblast, the Ryazan Oblast, etc.).
5. “Regions of special attention” , apparently, will “always find themselves” in the discouraging zone of heightened attention (11 regions, such as the Magadan Oblast, the Kamchatka Oblast, etc.).

The Appendix presents the comparison of classifications of all Russian regions by “innovativeness” and “investment attractiveness”.

In modern conditions the consideration of investment and innovation dependency becomes critical. This article classifies regions by these indicators and analyzes the education level in the regions on the basis of indicators of the employed population structure by education level (according to the sample survey of the population by problems of employment; in percentage to total) for 2011–2013.

The study reveals, on the one hand, the heterogeneity of socio-economic development of the country’s regions and, on the other hand, the same region can include regions-locomotives and problematic regions:

1. Central region includes 2 problematic regions, 8 regions with undecided prospects, 4 regions-growth poles, 2 regions-locomotives, and 3 regions-growth points.
2. Northwestern Federal District includes 1 problematic region, 4 regions with undecided prospects, 1 region-pole growth, 1 regionlocomotive, and 2 regions-growth points.
3. Southern Federal District includes 2 regions with undecided prospects, 1 regiongrowth pole, and 2 supportive regions.
4. North Caucasian Federal District includes 1 problematic region, 5 regions of special attention, and 1 region-growth pole.
5. Volga Federal District includes 1 problematic region, 4 regions with undecided prospects, 5 supportive regions, 2 regions-growth points, 2 regions-growth poles.
6. Ural Federal District includes 1 problematic region, 2 regions-locomotives, 1 supportive region, 1 region-growth pole, 1 region-growth points.
7. Siberian Federal District includes 1 problematic region, 1 region of special attention, 2 regions with undecided prospects, 2 supportive regions, 4 regions-growth poles”.
8. Far Eastern Federal District includes 4 problematic regions, 2 regions of special attention, 3 regions-growth poles.

Obviously, such heterogeneity of the acquired results requires additional study to identify the causes and indicators that lead to such results. To identify the dependence of innovativeness and investment attractiveness on the level of education and the development of lifelong education we have decided to extend the proposed classification in the future: include the dependence of the level of economic development of the region on the educational level of economically active population. It is very interesting to analyze the possible implementation of lifelong education principles and the level of unemployment in the region, since this problem correlates with the need to work out the system of retraining and training with regard for regional characteristics. Aggregate demand on the labor market in modern conditions depends not only on the scale of production, but also on the level of innovation. Actively developing regions increase aggregate demand on the labor market through the production of goods and services. Therefore, we can say that innovative development, as a specific mode of material values production, is characterized by the specific content of social reproduction and the original system of economic relations. Any modern consumer wants the products to be innovative, but such products can not be created by specialists with a low level of education (primary, secondary). Innovations are created by professionals, whose training requires significant resources. For the innovative policy to be efficient, the Russian Government should provide the public with the ability to obtain the necessary level of education not only in central, but also in all other regions. Refusal from raw materials, implementation of import substitution and transition of the Russian economy to the innovative way of development are largely determined by human capacity: level and quality of education and training of specialists, possibility to realize a continuous process of re-training, all forms of self-education and informal education. The development of new professions and obtainment of required skills define the boundaries of technological, economic and social modernization of Russian regions and the country as a whole.

Appendix

Classification of Russian regions by investment innovation indicators and education level

Classification by indicators		Location of the subject	Location of the subject	Education level of the economically active population
Innivative-ness	Investment attractiveness	Oblast	Federal district	Basic general	Primary vocational	Secondary professional	Higher professional
о со	Growth pole	Belgorod Oblast	CFD	2.7	22.3	25.5	28.8
	Region with undecided prospects	Vladimir Oblast	CFD	4.5	23.4	25.2	23.9
	Region with undecided prospects	Ivanovo Oblast	CFD	4.6	23.3	21.9	26.2
	Growth pole	Kaluga Oblast	CFD	3.6	22.6	28.3	26.8
	Region with undecided prospects	Kostroma Oblast	CFD	5.0	23.7	33.6	25.2
	Region with undecided prospects	Ryazan Oblast	CFD	4.2	22.6	30.6	26.2
	Region with undecided prospects	Smolensk Oblast	CFD	3.9	16.9	32.4	28.6
	Region with undecided prospects	Tambov Oblast	CFD	4.6	17.7	29.7	23.9
	Growth pole	Tula Oblast	CFD	3.7	14.7	30.3	25.7
	Region-locomotive	Moscow	CFD	0.6	16.2	27.2	49
	Problematic region	Komi Republic	NWFD	5.1	32.8	22	24.8
	Growth pole	Leningrad Oblast	NWFD	3.1	26.3	25.2	25.9
	Region with undecided prospects	Pskov Oblast	NWFD	4.9	20.8	30.1	23.1
	Region with undecided prospects	Astrakhan Oblast	NWFD	5.5	18.3	30	27.6
	Problematic region	Mari El Republic	VFD	4.1	22.9	27.3	26.3
	Region with undecided prospects	Udmurt Republic	VFD	3.5	28.4	22.1	25
	Growth pole	Orenburg Oblast	VFD	5.1	21.4	30.2	22.9
	Problematic region	Kurgan Oblast	UFD	6.7	22.6	25.9	24.6
	Supportive region	Chelyabinsk Oblast	UFD	4.0	16.5	35.4	28.2
	Problematic region	Altai Republic	SFD	6.7	18.3	25.8	30
	Growth pole	Altai Krai	SFD	5.3	21	23.6	22.2
		Tomsk Oblast	SFD	3.5	21.4	20.4	31.9
	Growth pole	Primorsky Krai	FEFD	4.2	22	24.2	30.4
	Growth pole	Khabarovsk Krai	FEFD	4.9	19	25.7	31.9

Continuation of the appendix

Classification by indicators		Location of the subject	Location of the subject	Education level of the economically active population
Innivative-ness	Investment attractiveness	Oblast	Federal district	Basic general	Primary vocational	Secondary professional	Higher professional
g о	Growth pole	Voronezh Oblast	CFD	2.9	11.8	26.4	27.4
	Growth point	Lipetsk Oblast	CFD	2.56	24	28.1	25.1
	Region-locomotive	Moscow Oblast	CFD	1.8	12.2	27.5	38.7
	Growth point	Orel Oblast	CFD	3.1	25.8	23.8	29.6
	Region with undecided prospects	Tver Oblast	CFD	4.36	23.6	31.1	23.2
	Growth point	Yaroslavl Oblast	CFD	4.8	27.8	30	23.5
	Growth point	Novgorod Oblast	NWFD	6.7	21.2	27.2	23.9
	Region-locomotive	Saint-Petersburg	NWFD	0.83	15.2	23.2	44.5
	Region with undecided prospects	Republic of Adygea	SFD	4.03	13.4	22.6	33.7
	Growth pole	Volgograd Oblast	SFD	3.6	18.5	29.6	27.3
	Supportive region	Rostov Oblast	SFD	5.2	15.8	27.3	29.6
	Region of special attention	Republic of Dagestan	NCFD	5.2	6.2	16.6	29.2
	Region of special attention	Kabardino-Balkar Republic	NCFD	5.6	12.7	19.6	29.6
	Region of special attention	Karachay-Cherkess Republic	NCFD	2.3	18	19.2	34.8
	Region of special attention	Chechen Republic	NCFD	7.2	4.6	11.4	25.2
	Growth pole	Stavropol Krai	NCFD	4.5	11.5	25.1	31.2
	Supportive region	Republic of Bashkortostan	VFD	3.3	28.8	25.9	23.6
	Growth point	Republic of Mordovia	VFD	2.2	19.4	23.5	28.8
	Supportive region	Republic of Tatarstan	VFD	2.6	21.3	19.4	30.8
	Growth point	Chuvash Republic	VFD	3.8	24.7	21.9	27.3
	Supportive region	Perm Krai	VFD	4.6	28.6	27.1	23.2
	Region with undecided prospects	Kirov Oblast	VFD	5.3	26.6	26.1	22.2
	Supportive region	Nizhny Novgorod Oblast	VFD	3.5	23	27.9	27
	Region with undecided prospects	Penza Oblast	VFD	3.6	16.4	27.2	27.1
	Supportive region	Samara Oblast	VFD	2.4	15.4	29.8	35.9
	Growth pole	Saratov Oblast	VFD	4.9	18.7	27.9	28.2
	Region with undecided prospects	Ulyanovsk Oblast	VFD	4.2	17.9	27.6	25.8
	Region-locomotive	Sverdlovsk Oblast	UFD	5.3	22.4	25.9	25.8
	Growth pole	Novosibirsk Oblast	SFD	4.8	19.3	21.9	31.2
	Growth pole	Omsk Oblast	SFD	5.76	19.7	24.7	25.2
	Region of special attention	Magadan Oblast	FEFD	2.57	12.7	21.4	30.8

End of the appendix

Classification by indicators		Location of the subject	Location of the subject	Education level of the economically active population
Innivative-ness	Investment attractiveness	Oblast	Federal district	Basic general	Primary vocational	Secondary professional	Higher professional
о Q	Region with undecided prospects	Kursk Oblast	CFD	3.6	24.4	24.3	28.4
	Region with undecided prospects	Republic of Karelia	NWFD	4.36	27.2	28	24.2
	Region with undecided prospects	Arkhangelsk Oblast	NWFD	4.9	29.1	29.4	24.3
		Vologda Oblast	NWFD	6.03	26	26.2	22.3
	Growth point	Kaliningrad Oblast	NWFD	4.03	17.1	31.2	31.8
	Region with undecided prospects	Murmansk Oblast	NWFD	2.56	27.8	21.9	28.4
	Region of special attention	Republic of Kalmykia	SFD	2.7	12.3	25.2	34
	Supportive region	Krasnodar Oblast	SFD	3.8	16.2	28.3	26
	Region of special attention	Republic of Ingushetia	NCFD	1.2	10.1	28.8	31
	Problematic region	Republic of North Ossetia – Alania	NCFD	3.96	14.3	26.4	36.5
	Growth point	Tyumen Oblast	UFD	3.3	18.2	26.8	29.5
	Region with undecided prospects	Republic of Buryatia	SFD	5.5	23.1	24.7	27.6
	Region of special attention	Tyva Republic	SFD	3.9	16.4	25.6	33.5
	Region with undecided prospects	Republic of Khakassia	SFD	5.6	14	26.9	24
		Zabaykalsky Krai	SFD	7.5	16.4	22.9	21.8
	Supportive region	Krasnoyarsk Krai	SFD	5.96	16.9	28.2	26.1
	Growth pole	Irkutsk Oblast	SFD	6.9	21	23.2	25.8
	Supportive region	Kemerovo Oblast	SFD	5.3	23.9	26.5	24.7
	Growth pole	Sakha (Yakutia) Republic	FEFD	3	19.2	24.9	28.4
	Region of special attention	Kamchatka Krai	FEFD	3.16	20.4	22.6	34.9
	Problematic region	Amur Oblast	FEFD	6.6	20	27.6	27.7
	Problematic region	Sakhalin Oblast	FEFD	4.4	25.1	25.3	24.3
	Problematic region	Jewish Autonomous Oblast	FEFD	10.7	18.9	23.9	19.8
	Problematic region	Chukotka Autonomous Okrug	FEFD	5.5	20	25.3	26

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