Assessment of the Paradox of the Formation of Economic Systems in
Different Types of Countries
Nadezhda M. Goreeva
1a
, Larisa N. Demidova
2b
and Olga V. Savchina
3c
1
Department of Economics and Statistics, KF FSBEI HE RT SAU, Kaluga, Russia
2
Department of Statistics, Plekhanov Russian University of Economics, Moscow, Russia
3
Department of Accounting, Audit and Statistics, Peoples’ Friendship University of Russia (RUDN University), Moscow,
Russia
Keywords: Social Institutions, Dualism of the World Economic System, Factors of Efficiency of Public Institutions,
Global Productivity, Public Utility, Global Economic System.
Abstract: The modern economic system demonstrates the inconsistency of the redistribution of gross value added
(GVA) and gross domestic product (GDP) in the direction of developed consumer countries. On the basis of
the system of indicators that characterize the effective socio-economic development of countries and the
optimal combination of statistical methods that allow us to classify and model the factors that form such a
performance of the economies of countries, the authors have established the reasons for their leading positions.
The article examines the systems of models of countries with different levels of socio-economic development,
their social utility and different degrees of development of institutions in each group of countries: developed
and developing. The evaluation and modeling showed that the Gini coefficient, which shows the degree of
social differentiation, has a high correlation with 4 indicators that characterize the efficiency of economic
development (consumer confidence index, human development index, inflation index, and the share of high-
tech industries in the GDP of countries). The authors proved that it is social utility that should ensure the
multilateral development of human potential, which, in turn, contributes to economic growth. The paper also
reveals the intensity of structural changes that may occur in the structures of gross value added and the
employed population in order to determine the trends of their further distribution by industry.
1 INTRODUCTION
After the end of the Second World War and collapse
of the colonial system there appeared a group of
countries in the world map that were named as the
third world counties.
At that time USSR and the United States were the
major political rivals, with USSR heading the so-
called socialist block countries, while the United
States heading the capitalist countries. There was an
unreconciled conflict between the rival systems for
the future of developing countries in all the domains
from industrial espionage and infamous “brain wash”
to political sabotage and expansive military intrusions
aimed at overthrowing the undesired regimes.
a
https://orcid.org/0000-0002-2749-4720
b
https://orcid.org/0000-0001-5906-1455
c
https://orcid.org/0000-0003-3391-8785
Until the end of the 80-ies, each of the
antagonistic parties made attempts to spread their
influence, including in Europe, in order to maximize
their power in the third world countries. This lead to
the emergence of countries with socialist orientation,
that fell into the zone of interest of the USSR.
However, in the very beginning of the 90-s, after
the USSR disintegration and the socialist camp
collapse, the situation changed dramatically. The
unipolar economic world, headed by the United
States, evolved into a bi-polar one, with the second
pole being divided between the European countries
and Japan. Other countries were considered to be
satellites equally distant from the center and
depending on the functions, which they performed in
a newly formed system of coordinates. Russia found
Goreeva, N., Demidova, L. and Savchina, O.
Assessment of the Paradox of the Formation of Economic Systems in Different Types of Countries.
DOI: 10.5220/0010587401430150
In Proceedings of the International Scientific and Practical Conference on Sustainable Development of Regional Infrastructure (ISSDRI 2021), pages 143-150
ISBN: 978-989-758-519-7
Copyright
c
2021 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
143
itself among second-tier countries with relatively low
level of economic development, shrinking
population, and lack of own development strategy. At
the same time the country had a vast territory and,
most importantly, contrary to China, India, and
Brazil, military and nuclear potential that was
comparable to that of the United States.
The transition to market economy meant in fact a
complete rejection of the previous ideology of
development that was based on the public property.
This transition resulted in privatization of the public
property in 1991 when the enormous Soviet empire
disintegrated.
The cutoff of the existing economic structure and
the sharp decline in revenues from exports of mineral
resources due the structural changes in the world
markets, did not allow Russia to change the model of
economic development and occupy a deserved place
in the international division of labor.
At the same time, in the 90s, Russia began to form
a socio-economic structure, which developed into a
structure with fundamental features that distinguish
the transition economy from developed countries.
The authors attempt to identify the factors of
development of a particular socio-economic model of
the state, the place that Russia occupies in the
international division of labor, and the role of public
utility.
2 METHODOLOGY
Our research methodology encompasses the
following three key components:
1. design of the system of indicators, which
characterize the processes of social and economic
development of models of state (both developed and
developing);
2. high-level overview of the process of collecting
and processing of data and selection of analysis
methods;
3. calculation and interpretation of research
results.
As the first step of the study, we evaluated the
trends in structural factors and indicators of labor
productivity in domestic economies.
As the second step, we built a factor model based
on the data from 42 countries: 27 EU countries (main
developed countries); 5 BRICS countries (the semi-
developed countries); 10 Asian and Latin American
countries (where the model of social and economic
development for the last decades permitted to take
leading positions in their respective regions).
As the third step of the study, we identified the
main basic factors that form social utility of an
economic model, determining the basis for selection
of an effective feature of economic structure.
One of the aspects of comparative analysis is the
classification of OKONKH and OKVED. To
characterize the identification of gross value added,
the structural differences indices of Salai and
Ryabtsev were used.
3 RESULTS
Let us attempt to answer the complex question about
the development of a social and economic model of
the country.
The first aspect that distinguishes a country with
transitional or, as it is often said, developing
economy, from a developed country is the dualism of
its social-economic structure. What is its essence?
First of all, in such a country, the structure of the
economy as well as its social and cultural life are
divided into two parts, while the interpenetration and
interaction between them are rather limited.
This statement is proved in the first place by
comparison of structure of economic sectors of GDP
with the corresponding distribution of the working
population.
For example, from the distribution of gross value
added by sector and the number of workers employed
in respective sectors in Russia, we can see the duality
of the system in the distribution of production surplus
(Table 1).
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Table 1: The structure of gross value added (GVA) and the average annual number of people employed in the economic line
of business (OKVED) for 2002 and 2018 in Russia.
Type of economic activity 2002 2018 The rate of
labor
efficiency
growth in
2016 to
2002, %
structure,
%
Economic
sector
labor
efficiency
structure Economic
sector
labor
efficiency
GVA employed GVA employed
Agriculture, hunt and
forestr
y
5,99 12,552 0,477 4,5 6,5 0,692 145,073
Fishing and fishery secto
r
0,3 0,183 1,639 0,2 0,2 1,000 61,013
Excavation of mineral
resources
6,7 1,774 3,777 9,4 2,2 4,273 113,132
Process plants 17,2 18,430 0,933 13,6 14,4 0,944 101,179
Production and distribution
of energy, gas and wate
r
3,6 2,883 1,249 3,4 3,2 1,063 85,108
Construction 5,4 6,800 0,794 6,2 7,2 0,861 108,438
Wholesale and retail trade;
repair of vehicles,
motorbikes , household
goods and personal demand
items
22,9 15,091 1,517 15,9 16,6 0,958 63,151
Hotels and restaurants 0,9 1,641 0,548 0,8 1,9 0,421 76,825
Transport and
communication
10,2 7,802 1,307 8,8 9,5 0,926 70,849
Financial activit
y
2,9 1,091 2,658 4,5 2,0 2,250 84,650
Operations with real estate,
rent and rendering services
10,6 7,494 1,414 11,8 7,2 1,639 115,912
Public administration and
providing military security,
obligatory social insurance
5,1 4,790 1,065 7,8 7,4 1,054 98,967
Education 2,9 9,209 0,315 7,3 9,4 0,777 246,667
Health care and rendering
social services
3,3 6,707 0,492 3,7 8,0 0,463 94,106
Rendering other community
facilities and personal
services
1,9 3,553 0,535 2,1 4,3 0,488 91,215
Source: Authors’ calculations based on the data from the site
http://www.aero.garant.ru/?utm_source=ivo&utm_medium=text&utm_content=demo-regional&utm_campaign=lead-from-
dri#form_title;
Authors’ calculations based on the data from the site http://www.gks.ru
*highlighted the sectors with labor efficiency growth in 2018 compared to 2002.
We can see from the table above that the main part
of added value was created in extractive industries
during the previous two decades, whereas
approximately 2,2% of all labor power was engaged
in it by 2018.
It is evident that the correlation of a sector added
product and the employment gives, as a result, a
sector level of output or a sector labor efficiency.
The considerable superiority of the extracting
sector of economy is also evident here. It also
confirms a superior rate of a labor efficiency growth
which in extracting industries is equal to 13.2%. What
are the consequences of such state of things?
The most evident part of this phenomenon lies in
the fact that extracting industries generate both the
largest part of profit in the economy, the lion’s share
of which is actually a natural resource rent; these
industries also create more than 50% of all payroll
fund (without accounting undisclosed earnings)
(Okediji, 2011; Luca Ferrini, 2012; Petrov, 2015).
As far as the most important element of an added
value is concerned, only about 22% of the total sum
of depreciation expenses fall into the share of an
extracting industry, based on capital consumption,
which is one of the key priorities of economic growth.
Besides, it is natural to assume that as far as these
sectors are mainly consumers of innovations created
in the economy, their role in a scientific and
technological progress, compared with the processing
industry, is, mildly speaking, meager
Assessment of the Paradox of the Formation of Economic Systems in Different Types of Countries
145
(Kapelyushnikov, 2014; Marinov, 2014; Goreeva et
al, 2013).
Economies, that exist at the expense of
exploitation of natural resources and as a result
position the international division of labor for long-
term inactivity, can be characterized by the common
feature: underdevelopment of social and economic
structure.
Besides, it should be noted that the year 2002 was
chosen for a comparative evaluation due to the
transition of the Russian statistics from the Russian
Classification of Sectors of the Economy (OKONH)
to application of Russian National Classification of
Economic Activity (OKVED) (Chernyaev et al.,
2014).
The GVA (Gross Value Added) indicators broken
down by Russian Classifier of Economy Branches
(OKONH) were calculated for the period from 1997
to 2004 and by OKVED sectors – from 2002 to 2012.
The structures of industry sectors related to Russian
Classification of Economy Branches and OKVED
differ rather considerably; that is why the year 2002
was taken as a reference period to eliminate the lack
of the results comparability. All evaluations were
calculated in both Russian Classification of Economy
Branches and OKVED versions for 2002 year.
The comparative evaluation of sectors included
into classifiers shows that the transition from Russian
Classification of Economy Sectors (ОКОNH) to
OKVED lead to the increase of a labor remuneration
share in GVA industry by approximately 4 percentage
points just as the GVA share of this sector started to
reduce considerably faster.
Thus, the labor force becomes cheaper. Notably,
in Kapelyushnikov’s opinion, the range of a relative
reduction in price of labor force in extracting
industries was rather impressive: the share of labor
remuneration in GVA of this sector reduced by more
than two and a half times from 37,5% in 2002 to
almost 15% by 2013. Therefore, the growth of labor
productivity was mainly achieved in the country at
the expense of reduction in direct labor costs
(Chaykovsky, 2011; . Druzhinin and Prokopiev,
2015).
An important aspect of the study was the
identification of the intensity of structural changes
that may occur in the structures of gross value added
and employed population in order to determine the
trends of their future distribution by industry. We
used data from 2016 and 2002 to calculate the
coefficients. The main indicators characterizing the
materiality essentiality of structural changes are:
A. Salai index
𝐼


 (1)
where:
V1-the share of the industry in gross value added
(the structure of the employed population by industry)
in 2016;
V2-share of industry in gross value added
(employment by industry) in 2002;
n-the number of specific weights in the structure
of industries.
This indicator takes its values in the range from 0
to 1. The closer the index value of A. Salai to one, the
more significant are the structural differences.
Already at index values above 0.2, structural
differences are considered significant. However, it
should be taken into account that the value of the
index will depend heavily on the number of elements
to which the whole set is divided. The more of them,
the more the index will be leveled.
Ryabtsev index does not take into account the
number of specific weights of the structure and does
not depend on the number of parts of the population:
index V. M. Ryabtseva
𝐼
∑

∑

(2)
Rating scale measures of importance of
distinctions of structures according to the criterion of
V. M. Ryabtseva presented below in table 2.
Table 2: Border force structural differences on the criterion
of V. M. Ryabtseva.
The range of values
of the criterion
Characteristics of the
structural differences
0,000
0,030 identit
y
of the structures
0,031 – 0,070 very low level of
differences
0,071
0,150 low difference
0,151
0,300 si
g
nificant level differences
0,301
0,500 significant difference
0,501 – 0,700 rather significant level
differences
0,701
0,900 o
osite t
e of structures
0,901 and above total opposite of structures
Source: (Shakhnovich, 2014).
Calculations of the index A. Salai showed that this
coefficient on gross value added amounted to 0,18. In
the structure of employment it is 0,14. Thus, A.
Salai index showed no significant differences in the
structure of employed by industry. There are
noticeable changes in the structure of gross value
added. However, it is necessary to take into account a
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sufficiently large number of gradations of the specific
weight of the indicator 15 sectors, which
significantly reduces the scientific significance of the
result and confidence in it.
The index of V. M. Ryabtsev calculated by us
does not depend on the number of gradations of the
aggregate structure. During the same period, the
index for the structure of the employed population
was 0,13, which can be interpreted as a low level of
differences in the structure of employed by industry
for the period from 2002 to 2016. However, this
index calculated on the gross value added and equaled
to 0,16 shows a significant level of variation in VDS.
Thus, the index suggests that there are significant
differences in the structure of gross value added.
In the short run, attempts to improve the social and
economic structure leads, as a rule, to the situation
chasing the economic efficiency. However, the
efficiency of state should be determined by the level
of the public utility, rather than solely by the
economic efficiency of national activity. The income,
generated in effective industries and fields of national
economy, is transferred to the state to support
distributive relations amongst the recipients. As a
result, the effective industries, do not receive back
enough funds for their own development.
As a result, there arises a strong differentiation of
incomes across the industry sectors and groups of
population. This does not permit to use a human
capital to the full extent. Evaluation of the factors,
which lead to such a situation, is one of the vital tasks,
as it would permit to successfully solve the problem
of creating favorable conditions for development of
the society and the economy.
The most convenient form for factorial analysis is
building correlation models, which permit to
quantitatively evaluate the influence of each taken
indicator on a social efficiency of life of every
member of a society (Moskovskaya et al., 2011).
The countries with high living standards
(European Union countries), average living standards
(BRICS countries, i.e. developing countries such as
China, Indonesia, Malaysia), and low living
standards (Peru, Columbia, Chile and others) were
taken into a regression model.
The analysis of 2015 correlation of the Gini
coefficient, which shows the degree of social
differentiation, with 4 indicators, which characterize
the economy development efficiency (index of
consumer confidence, index of a human potential
development, inflation index, and a share of high-tech
industries in GDP of countries) prove the presence of
a rather strong relationship.
The three-factor model included only the index of
a human potential development, inflation index, and
the share of high-tech industries in GDP of countries.
The results of modelling are presented in Table 3.
Table 3: Countries grouping according to the index of the absolute level of 1% increment of growth for high-tech industries
share in GDP in 2018.
Groups of
countries
according
to the
absolute
level of 1%
increment
of growth
for high-
tech
industries
share in
GDP, %
Numb
er of
count
ries in
a
group
Share
of EU
countrie
s in
each
group
Coefficient
of funds
renewal and
upgrade, %
Investments
in a fixed
capital
Inflatio
n level,
%
HPDI
(human’s
potential
developme
nt index),
%
Proportion of
the population
with incomes
below
minimum
subsistence, %
Coeffi
cient
of the
lost
earnin
g
s*
2018
2015
2018
2015
2018 / 2015
2018
2018
2015
2018
2018
0,007-0,04 28 100 28,6 18,7 19,3 100,
6
100,3 85,9 86
,2
5,4 5,2 1,64
0,04-0,072 2 50 23,5 21,5 22,0 102,
2
101,8 83,7 84
,0
2,5 3,0 2,69
0,072-0,09 4 25 33,5 20,9 21,5 104,
2
104,7 81,9 82
,1
4,1 4,2 2,57
0,09-0,121 8 0 31,9 25,6 20,4 104,
6
104,2 73,6 77
,7
5,9 6,0 4,29
Source: Calculated by authors on the basis of Eurostat data.
*Correlation of an average occupational earning to an average pension in the country
Assessment of the Paradox of the Formation of Economic Systems in Different Types of Countries
147
Thus, the majority of developed countries in
grouped data does not have a high share of high-tech
industries in GDP. At present developing countries
represent the main flagships for the economy growth
driven by technological development. The level of
social protection of the population and differentiation
of incomes is ambiguous given the similar inflation
expectations in the countries.
A deflation scenario of development can be
observed in the world economy that is related to a
gradual slowdown of investments the main driver
of countrieseconomies. This situation is related not
to the lack of resources, but rather to the excess
supply due to the end of dollar emission. Besides that,
the problems caused by the dollar being the world
currency, have aggravated.
It had an especially adverse effect on developing
countries where the level of investments declined by
more than 5% in 2016 compared to 2015, which in
turn affected the rates of industrial production. In the
other two groups of countries the level of investments
declined by more than 1%. As a result, the degree of
a social inequality and uncertainty of the society
regarding its future have increased. The coefficient of
lost earnings showed its 2,6 times growth related to
the last group.
4 CONCLUSIONS
In the past two decades, a unipolar world transformed
into a bio-polar world in which Russia found itself in
a group of developing countries. At the same time,
having vast territory, natural resources, and cheap
labor and providing a considerable contribution to the
world GDP, the country remains socially ineffective.
In Russia, as a representative of developing
countries, an analysis of the structure of gross value
added and purchasing power conducted for the period
from 2002 to 2018 inclusive showed that the bulk of
gross value added during this period was created in
the extractive industries, however, they employ only
2.2% of the total labor force, which causes high rates
of productivity growth in this sector. The main part of
the profit received in this sector is rent from natural
resources and in the absence of its own high
technologies, the main directions of supply of high-
tech goods are imports. Thus, the average annual
share of exports of high-tech goods from China to
Russia over the past 5 years was more than 30%
(Birdsall, 2010).
The share of high tech goods in the total volume
of the Chinese export showed steady growth and
reached 40% (The economic system of modern
Russia: ways and objectives of development:
Monograph Ed. A.A. Porokhovsky, 2015).
Transformations and economic growth in countries-
beneficiaries without investment and reduction of
purchasing power of both households and producers
adversely affect the economic efficiency of Russia
(Demidova et al., 2018).
This is proved by models for developing and
developed countries which showed that in modern
conditions the state’s emphasis on superiority of
market mechanisms over social policy can lead to
stable economic growth but not to increased welfare
of a society.
The constructed correlation and regression
models for developed groups of countries and
developing groups of countries showed that both in
most cases do not have a significant share of high-
tech industries in GDP. Today, developing countries
are the main engine of economic growth and
technology development. However, the level of social
protection of the population and income
differentiation are very ambiguous. In this regard, the
global economy is developing a scenario of deflation
of development, which is characterized by a
slowdown in investment activity associated with
oversupply due to the cessation of dollar issuance.
This has a particularly negative impact on the group
of developing countries, where the level of
investment decreased by more than 5% in 2018
compared to 2015. As a result, the rate of industrial
production has decreased and social inequality in the
community has increased. According to the authors,
the coefficient of lost earnings showed an increase of
2.6 times compared to wages in developed countries.
The economic development in the majority of
countries does not actually lead to effectiveness of
social institutions or reduction of income inequality.
And this holds true even for developed countries. In
this case the basic strategy of state programs should
be aimed at development of human potential of every
member of a society.
Russia as a country-consumer, rather than a
manufacturer of modern technologies, cannot
develop its economy without creating an effective
social infrastructure aimed at the development of
human capital through the formation of intellectual
and innovative environment. Institutional
transformations should involve an innovative value
chain that would include fundamental research,
applied R&D, and commercial technologies. Only in
this case the Russian domestic economy can compete
with China, India, and other countries. Institutional
developments in the form of the fund of national
welfare and state funds for development should
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148
become the key tools to solve the strategic problems
of the economy formation. It is also required to form
such institutions of development as techno parks,
business incubators, and technology transfer centers,
all in in the conditions of insufficient financing.
The efficiency of the Russian economy should
contribute to a correspondingly fair distribution of
resources. This can lead to emergence of consensual
ideology, which is aimed at the growth of social
effectiveness of the economy and protection of the
country population.
A high-level objective to focus solely on
economic rational of any economic institution at the
expense of its actual utility is explained by the
increased requirement for lowering costs and
increasing labor productivity. However, a low
technological level of production and lack of
opportunity to produce a variety of industrial products
knowledge-based components, which would have
high domestic demand, lead to a high import
substitution and dependence on foreign supplies of
ready-made products. In addition to that, the problem
is further aggravated by a depressive state of the
science.
The implications for Russia are the lack of
financing for research and development and, as a
result, current incapability to occupy any niche in the
world production.
In most sectors, forming the GDP of Russia, a
share of high-tech products is fairly low and involves
only production of raw materials or semi-finished
goods and, therefore, does not give a possibility to get
a bigger share of value added.
The solution to this problem, which resonates in
the experience of some countries, can be the increase
of a part of expenses for R&D from the Federal
Budget allocated on a competitive basis. However,
there arises a question about changing the
institutional component of state aimed at ensuring
social utility of every member of the society. The
share of gross value added and labor productivity in
any sector of the national economy should be
proportional and correspond to the labor
remuneration which a worker receives. This
proportionality should also be taken into account
while implementing the redistributive relations in the
economy of the country.
The required and sufficient condition here is a
creation of a successful anti-inflationary monetary
policy and a fiscal policy, which will permit to
distribute the resources in the country, activity of the
state in the field of foreign trade turnover, allowing to
mitigate negative consequences of declining trade
cycle in the economy. Favorable living environment
for the population and their confidence in the future
should be maintained.
The main dilemma today encompasses the role of
the state in the Russian Federation as a subject of
economic activity and the necessity of cardinal
changes in the legal and judicial system. If these
changes do not take place, the differentiation between
poor and rich countries will deepen even further.
Furthermore, the obsolete structure of the economy
creates a dependent development path. The current
challenges are due to the fact that from the one side,
there is a requirement to develop market institutions,
and from the other side, there arises a requirement to
increase social purposes of these institutions. Today
such dualism remains one of the most important
issues of many states.
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