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Instability of socio-economic and sustainable development of Ural regions

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Problems of development stability of regional economies are of particular importance in current conditions. The article presents the analysis of the sustainability of the development of Russian regions included in one of the most industrially developed federal districts - the Ural. The study used data from Rosstat for 2001-2019. The tendencies of the instability of indicators of socio-economic development of regions are revealed: gross regional product, investments in fixed assets, industrial production, and consumer prices. It has been established that the dynamics of the growth rates of these indicators are volatile. At the same time, all trends demonstrate a reasonably rapid recovery after the external shocks of 2008 and 2014. These indicators’ volatility was assessed using the variation coefficient in three different periods: 2001-2008, 2010-2014, and 2015-2019. The conclusion is made about the high instability of regional socio-economic development, while the level of instability in regions with a lower level of development turned out to be higher than in more developed ones. Particular attention is paid to trends in the level of instability, and it is noted that over time, less developed regions increase instability at a faster pace.
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Instability of socio-economic and sustainable
development of Ural regions
Victor Barkhatov1,*
1Chelyabinsk State University, 454001, 129, Br.Kashirinykh str., Chelyabinsk, Russia
Abstract. Problems of development stability of regional economies are of
particular importance in current conditions. The article presents the
analysis of the sustainability of the development of Russian regions
included in one of the most industrially developed federal districts - the
Ural. The study used data from Rosstat for 2001-2019. The tendencies of
the instability of indicators of socio-economic development of regions are
revealed: gross regional product, investments in fixed assets, industrial
production, and consumer prices. It has been established that the dynamics
of the growth rates of these indicators are volatile. At the same time, all
trends demonstrate a reasonably rapid recovery after the external shocks of
2008 and 2014. These indicators' volatility was assessed using the variation
coefficient in three different periods: 2001-2008, 2010-2014, and 2015-
2019. The conclusion is made about the high instability of regional socio-
economic development, while the level of instability in regions with a
lower level of development turned out to be higher than in more developed
ones. Particular attention is paid to trends in the level of instability, and it
is noted that over time, less developed regions increase instability at a
faster pace.
1 Introduction
New normal requires new approaches and methods of analysis and assessment of trends
in regions' economic development. In the formation of the region's financial stability, it is
faced with internal influences that did not exist in the previous period
. At the same time,
they have a direct impact on the stability of the regions. First of all, the regional economy's
stability is influenced by the transition to its turbulent development, the growth of entropy,
that is, the instability of socio-economic development. A group of factors arises that
enhances instability and reduces the region's economy's stability, transforming it, and a
relatively stable ecosystem is unstable, unable to ensure the unity of socio-economic
institutional, ecological development. During this period, there is a reduction in the region's
resource potential, which cannot meet the vital needs of people living in the region to create
zones of their favorable residence in these territories. The factors of the instability of the
regional economy in turbulence conditions include, first of all, external factors that must be
taken into account when assessing the level of their dynamic development.
Instability is associated with such economic factors as a decline in production, rising
*Corresponding author: ieo-science@csu.ru
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https://doi.org/10.1051/e3sconf/202125806020
© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
inflation, weak investment activity, and a reduction in aggregate demand; also, a decrease
in the capacity of the market for goods, a decrease in demand for goods and services, an
increase in monopoly in the national economy, which is reflected in the costs of pr oducers
and a decrease in the production activity of economic entities. External factors of instability
make adjustments to the increase and decrease in the estimated sustainable development
indicators of the regional economy.
The issues of regional develo
pment and its instability are considered in the works of A.
Naydenov [1], Y. Willi et al. [2], K. Rentkova [3], Lovric et al. [four]. National
characteristics of sustainable development and factors influencing it are described in A.A.
Davidescu et al. [5], H. Rahma et al. [6], A.M. Bercu [7], R. Eversole and M. Walo [8], V.
Barkhatov et al. [9]. The formation of effective public policy is analyzed in P. Lee and D.
Keegan [10]. The authors note the importance of the regional level in public administration
and the focus of scientific research due to the increasing role of regions in the country's
socio-
economic development.
The article aims to analyze trends in the instability of regional development of Russian
regions belonging to the Ural Federal District (Sverdlovsk, Chelyabinsk, Tyumen, and
Kurgan regions).
To achieve this goal, the following tasks were consistently solved:
1. Analysis of trends in indicators of socio-economic development (gross regional
product, investment in fixed assets, industrial production, and consumer prices) in order to
identify instability in the values of their growth rates
2. Calculation of the coefficients of variation of the selected indicators for three periods:
2001-2008, 2010-14, and 2015-2019
3. Analysis of the degree of variation (stability) and tendencies of its change by periods.
2 Data and Methodology
Sustainable development, everything should be based on an assessment of trends in the
factors of the instability of the regional economy, reflecting the dynamics of development
indicator s and allowin g conclusions to be drawn about the actual tr ends of regional
development. Such an assessment of sustainable development trends allows us to determine
the regional economy's stages to a new normal in a turbulent external environm ent. At the
same time, entropy grows, and the region's economy loses its ability to move forward to a
stable state, goes into a stagnation regime. The existing production, scientific and technical,
human potential, and accumulated innovations cannot independently, without state support,
move to a new higher level of development. We will assess the sustainable development of
the Ural Federal District's regions based on factors and indicators of instability. Assessment
of the stability of regions depends on the instability of socio-economic development, which,
in turn, is understood as a decrease in the growth rate of external and internal development
indicators.
The article uses the official data of Rosstat, in particular, four indicators of regional
development: gross regional product, investment in fixed assets, industrial production,
consumer prices. To assess the instability of development, the increments of all the above
indicators were calculated in dynamics for 2001-
2019. Separately, these indicators'
variation coefficient was assessed for three time-intervals: 2001-2008, 2010-2014, and
2015-2019. It allows concluding the trends of instability both in individual regions and in
the Ural Federal District. 2009 is excluded from the analysis as an anomalous observation
that distorts the summary analysis.
The conclusion about the indicator's stability was made based on the analysis of the
values of the indicator of variation -
if it was less than 0.33, then the indicator was
recognized as stable. The conclusion about the presence of a trend was made based on
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comparing the indicator for different periods: if these values had a certain tendency to
increase or decrease, then this was recorded in the table, if there were high fluctuations,
then the trend was designated as up and down rally, and if the values in different periods
were close, it was concluded "no tendency".
3 Results
Let us consider the first indicator's dynamics: the gross regional product's growth rate (fig.
1). Visual trend analysis reveals two important points. Firstly, different regions do not have
uniform trends in the change in this indicator, which is influenced by various factors,
including internal and external economic and the amount of state support sent to the region.
Secondly, with a general decrease in the indicator's growth rate (primarily explained by a
significant decrease in inflation, from 10 to 4%), the degree of variation of individual
values remains very high, which indicates instability.
Fig. 1. Gross regional product growth rate (%) in 2001-
2019, Ural federal district.
Much smoother and more stable dynamics characterize the analysis of the following
indicator of consumer price growth rate (fig. 2). This is because the Central Bank of Russia
is implementing a reasonably strict policy to curb inflation and other executive authorities'
price control. The graph shows a downward trend in the rate of growth of the price level,
which was violated twice - in 2008 and 2014-15, when due to external factors (primarily
the growth of foreign exchange rates) there was a sharp rise in p
rices for imported goods
and services, and also production resources. It should be noted that the tendencies of this
indicator change in different regions are not repeated but have similar dynamics. The values
for the least developed Kurgan region are subject to the smallest fluctuations.
The third considered indicator, the growth rate of investments in fixed assets, demonstrates
high volatility (fig. 3). After 2008, there was also a growth slowdown but remained
reasonably high - about 20% per year. This trend is explained by the overheating of the
economy in the period before the 2008 global crisis. Today, investment plans of enterprises
-20
-10
0
10
20
30
40
50
Sverdlovsk region Chelyabinsk region
Tyumen region Kurgan region
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and the state are drawn up more systematically and wisely. At the same time, it should be
noted the growth of this indicator in 2018-19 in the leading regions (Sverdlovsk and
Tyumen regions) to the levels of 2005-06.
Fig. 2. Consumer prices growth rate (%) in 2001-2019, a Ural federal district.
Fig. 3. Investment in fixed assets growth rate (%) in 2001-
2019, a Ural feder
al district.
The fourth indicator is the industrial production growth rate (fig. 4). This indicator
demonstrates relatively high stability (except for shocks in 2009 and 2015 caused by
external factors. Simultaneously, the regional economies are synchronously adapting to the
new economic conditions of management, and since 2015 have been demonstrating a
steady growth of this indicator (in fixed prices).
Fig. 4. Industrial production growth rate (%, in fixed prices) in 2001-
2019, a Ural federal district.
0
5
10
15
20
25
30
Sverdlovsk region Chelyabinsk region
Tyumen region Kurgan region
-40
-20
0
20
40
60
80
100
Sverdlovsk region Chelyabinsk region
Tyumen region Kurgan region
-30
-20
-10
0
10
20
Sverdlovsk region Chelyabinsk region
Tyumen region Kurgan region
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At the next stage of the study, we will analyze the coefficients of variation of the
calculated indicators for three periods: 2001-2008, 2010-2014, and 2015-2019. These
periods are between two external shocks that have had a severe impact on the Russian
economy: 2008 - the global financial crisis and 2014 - Western sanctions (see Table 1).
Table 1.
Variance coeffici ents of inst ability indicators Ural’s regions of Russia
.
Growth rare of
Variance coefficients, by period.
Stability
Tendency
2001-2008
2010-2014
2015-2019
Gross regi onal product
0.2927
0.5695
0.1451
stable
decreased
Investments in fixed
assets
0.4700
0.9164
0.5407
unstable
up and
down rally
Consumer prices
0.2389
0.2060
0.3749
unstable
increased
Industrial
production
0.6050
0.7329
0.4736
unstable
up and
down rally
Gross regi onal product
0.2333
0.4163
0.3677
unstable
up and
down rally
Investments in fixed
assets
0.4682
0.4756
0.5820
unstable
increased
Consumer prices
0.3460
0.2254
0.3280
stable
no
tendency
Industrial production
0.9127
0.8298
0.8312
unstable
no
tendency
Gross regi onal product
0.3289
0.5150
0.0954
stable
decreased
Investments in fixed
assets
0.4468
61.5769
0.7122
unstable
up and
down rally
Consumer prices
0.3824
0.2656
0.3683
unstable
no
tendency
Industrial production
2.1757
0.9355
0.3491
unstable
decreased
Gross regi onal product
0.4891
0.4906
0.5179
unstable
no
tendency
Investments in fixed
assets
0.3687
0.4427
0.4986
unstable
increased
Consumer prices
0.2702
0.2339
0.3911
unstable
increased
Industrial production
0.7237
5.6921
0.9699
unstable
up and
down rally
Analysis of variance coefficients for selected indicators reveals trends such as:
1. In general, the sample is characterized by instability in the values of leading
indicators' growth rates. Simultan eously, on ly the values of the gross regional product in
highly developed regions - Sverdlovsk and Tyumen regions can be called stable.
2. In the same regions, there is an instability decrease tendency in indicators, but there is
no such tendency in other regions, and the opposite is presented.
4 Conclusion
As a result of the study, trends in the instability of the socio
-economic development of the
Urals regions were revealed. First, the indicators reflecting economic growth and industrial
development and the investment attractiveness of regions are in a state of high fluctuations
from year to year. Secondly, these indicators fluctuate asynchronously. Each region and
each indicator has its logic of changes and its specific factors. Thirdly, the reaction of the
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considered indicators to the external shocks of 2008 and 2014 is generally positive, and the
restoration of the indicators' values to the "normal" level occurs relatively quickly. Fourth,
the indicators themselves are characterized by their values' instability, even if we consider
them in the relatively homogeneous periods of 2001-2008, 2010-2014, and 2015-2019.
Fifth, relatively more prosperous regions are characterized by less instability in socio-
economic development indicators.
Further research is advisable to conduct in the following three areas: (1)
analysis of a
more significant number of regions, throughout Russia and in other countries with a similar
economic structure; (2) analysis of a more significant number of indicators, including those
reflecting demographics, living standards, and innovation; (3) analysis of specific and
general factors affecting the instability of the socio-economic development of the economy.
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... At the same time, consistent with Zhou (2019) [62], the social system development levels of Beijing, Shenzhen, Guangzhou, Shanghai, Suzhou, and Hangzhou were at the forefront. Barkhatov (2021) and found that the quality of urban life interacts with the level of economic development, and the stability of economic development greatly affects the level of sustainable development in the region; they also observed that the GDP per capita was an important indicator for measuring the level of economic development [63,64]. This point of view is consistent with the results of our study, which also revealed that there is a strong correlation between the per capita GDP and the spatial pattern of the sustainable development level of urban human settlements. ...
... At the same time, consistent with Zhou (2019) [62], the social system development levels of Beijing, Shenzhen, Guangzhou, Shanghai, Suzhou, and Hangzhou were at the forefront. Barkhatov (2021) and found that the quality of urban life interacts with the level of economic development, and the stability of economic development greatly affects the level of sustainable development in the region; they also observed that the GDP per capita was an important indicator for measuring the level of economic development [63,64]. This point of view is consistent with the results of our study, which also revealed that there is a strong correlation between the per capita GDP and the spatial pattern of the sustainable development level of urban human settlements. ...
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A.M. Bercu, Procedia Soc. Behav. Sci 188, 144-150 (2015)