MINISTRY OF EDUCATION AND SCIENCE, RUSSIAN FEDERATION
FEDERAL STATE AUTONOMOUS ORGANIZATION OF HIGHER EDUCATION
«NOVOSIBIRSK STATE NATIONAL RESEARCH UNIVERSITY»
(NOVOSIBRSK STATE UNIVERSITY, NSU)
Faculty
Economics
Chair
Chair of Economic Theory
Department
Economics
Master’s program
Quantitative Economics
GRADUATE QUALIFICATION PAPER
MASTER'S DISSERTATION
Leonova Anastasiya Aleksandrovna
Paper title
Human capital influence on production dynamics in Russia
«Admitted to defense»
Scientific Supervisor,
The head of the chair:
Ph.D. in Economics, Professor
Ph.D. in Economics, Professor
Baranov A.O./………...
Baranov A.O./………...
«……»………………2017 year
«……»………………2017 year
Date of the defense: «……»………………2017 year
Novosibirsk, 2017
2
TABLE OF CONTENTS
INTRODUCTION .................................................................................................................................... 3
CHAPTER 1. MAIN ASPECTS OF THE THEORY OF ECONOMIC GROWTH AND HUMAN
CAPITAL ................................................................................................................................................. 5
1.1 Basic provisions of economic growth ............................................................................................... 5
1.2 Theoretical bases of the modern concept of the human capital ......................................................... 7
CHAPTER 2. REFLECTION OF THE HUMAN CAPITAL IN MACROECONOMIC MODELS .... 12
2.1. Models with the human capital inclusion ........................................................................................ 12
2.2. Inclusion of human capital to Input-Output models....................................................................... 16
CHAPTER 3. ASSESSMENT OF HUMAN CAPITAL INFLUENCE ON PRODUCTION
DYNAMICS OF RUSSIA ..................................................................................................................... 23
3.1. Preparation of data .......................................................................................................................... 23
3.2 Calculation of size of the saved-up human capital at the macro level ............................................. 24
3.3 Calculation of size of the saved-up human capital at the regional level .......................................... 30
3.4 The Russian Federation territorial subjects rating on the human capital expenditures dynamics ... 34
3.5. Assessment of regression model on macro level ............................................................................ 35
CONCLUSIONS .................................................................................................................................... 38
REFERENCES ....................................................................................................................................... 40
APPENDIX 1 ...................................................................... ERROR! BOOKMARK NOT DEFINED.
APPENDIX 2 ...................................................................... ERROR! BOOKMARK NOT DEFINED.
APPENDIX 3 ...................................................................... ERROR! BOOKMARK NOT DEFINED.
3
INTRODUCTION
The relevance of the research. Up to the present time, the close interrelation of welfare and
quality of the labor is noticed, which was created by abilities of each certain person to use the
accumulated knowledge in the best way and to be improved by education. Therefore, one of the main
objectives of the developed countries economic policy is stimulation of individuals to these investment
decisions. In other words, now the human capital needs to be considered as the major factor promoting
economic growth.
Influence of the human capital on a development of economic system remains rather actual now.
In the last several decades, more and more attention is paid to this matter. In particular, the
understanding of the importance of the non-material factors of production defines quantitative
dynamics and qualitative nature of economic development. So the attention of researchers is even
more often attracted with the quality standard of workforces, their analysis, and influence. However,
this subject is very debatable as there is no uniform approach to an assessment of the human capital
and extent of its influence on economic dynamics.
Development of research in the field of the problem stated. The basis and foundation of this
work are surveys and papers of the leading foreign and Russian economists, who worked at the
theoretical and practical sides of the assessment of human capital size problem and its influence on
economic growth. It is necessary to mention works of the domestic researchers who were engaged and
engaged in development and extension of the human capital: A. V. Koritsky, R. M. Nureev, A. O.
Baranov, D. O. Neustroyev, S.A. Dyatlov, R.I. Kapelyushnikov, V.D. Matveenko, and also foreign
experts, in particular: A. Smith, T. Schulz, G. Becker, H. Uzawa, R. Lucas, U. Petty, K. Marx, P.
David, J. Lopez, E. Denison, R. Solow, J. Kendrick, S. Kuznets, S. Fabrikant, I. Fisher, E. Glazer, K.
Murphy, G. Mankiw, D. Romer, D. Weil, S. Park, H. Zhang and X. Chen.
Despite the significant contribution of above-mentioned economists to a development of the
human capital theory, the subject remains debatable, because the view about determining the volume
of saved-up human capital, its contribution to the economic development process and its positive or
negative influencing on economic growth have not formed yet. All that allow stating the aim and
objectives of the research.
The purpose of the research conducted below consists in an evaluation of saved-up human
capital influencing on economic growth of Russia. To achieve this goal, the following objectives have
been accomplished in the work:
1. To give the short characteristic of basic provisions of the human capital theory and to
characterize the extent of development of the researched problem on the part of the premier
and modern works.
2. To analyze reflection of the human capital in macroeconomic models in surveys of foreign
4
and domestic economists.
3. To create the approach for the volume of saved-up human capital assessment and analyze
dynamics of investments into the human capital generally in Russia, and in its regions.
4. To construct the factor model of economic growth with the inclusion of the human capital. To
carry out the approbation of the obtained data.
5. To evaluate the significance of the human capital in the constructed model and the model in
whole by the regression analysis holding.
6. To estimate interrelation between GDP and the human capital by the use of correlation
analysis.
The subject of the study is an assessment of the impact of human capital on economic growth.
The object of research is the Russian economy of the period from the 1993 to the 2015 year.
Research methods: the system analysis, the regression and correlation analysis, search in
electronic databases, generalization, and processing of statistical data.
The scientific novelty of the work is to assess the dynamics of human capital in a costly way in
the Russian economy in general and in its regions, as well as in assessing the impact of human capital
on economic growth in Russia.
The volume and structure of the work. The work consist of introduction, 3 chapters,
conclusions, bibliography (57 sources) and 3 appendixes. The main text of dissertation work is stated
on 43 pages.
This research consists of three main chapters, where each one of them contains several sections.
In the first chapter, we are considered a concept of economic growth and the factors influencing it:
development of the theory of the human capital in the historical aspect, and the main approaches to his
assessment. In the second chapter, we present the main models of economic growth, which consider
the influence of the human capital. In the last chapter, we present the results obtained and analyze
them. We finish our research with a summary of the conclusions and some thoughts about possible
areas of future research.
These results may be of interest to governments and organizations who are interested in
production efficiency increasing and possession of qualitative human resources.
5
CHAPTER 1. MAIN ASPECTS OF THE THEORY OF ECONOMIC GROWTH AND
HUMAN CAPITAL
1.1 Basic provisions of economic growth
In the work, "An Inquiry into the Nature and Causes of the Wealth of Nations" Adam Smith has
told that society is richer when each citizen is richer, but it is possible to paraphrase this statement as
follows: concerning the international economy, the world economy will be richer and more stable, than
each country will be richer and safer [Smith]. In addition, here the richness of each country will be
provided with the stable economic growth of the economy, if the country becomes richer, its potential
opportunities in the fight against poverty, hunger and in permission of other social problems extend
more. For this reason, the high level of economic growth is one of the main target reference points of
macroeconomic policy in many countries of the world.
However, what is economic growth? In modern foreign literature, there are several approaches to
the understanding of the concept "economic growth". Therefore, for example, there are approaches
where economic growth is identified with a quantitative type of growth of production or with an
increase in a potential national release, or potential real GDP, an increase in economic force for
expansion of production or with increase in production capabilities of society. In modern western
textbooks, economic growth is studied as an increase in real GDP, the pure national product (PNP) or
growth rates of economic welfare – the national income per capita for a certain period. The famous
American economist and the Nobel laureate Simon Kuznets considered that economic growth is the
long-term increase in production ability of the country based on technological progress, on
instrumental ideological adaptation, which promotes providing the population the growing variety of
material benefits. When determining economic growth he uses not only the quantitative review, but
also notes as a major factor the technical progress that provides economic growth, and notes its main
consequence (providing the population with the growing variety of material benefits).
Further, the concept of economic growth has included not only quantitative but also a qualitative
aspect. In general, it is difficult to find an unambiguous concept of economic growth. Some
economists connect it with quantitative changes that quite correspond to the development of economic
growth theories mainly within economic-mathematical methods.
It should be noted that quantitative interpretation of economic growth, promotion in the first
place of technical and economic characteristics of this process would lead to neglect its social and
economic aspect. Respectively, it is possible to distinguish two aspects of this phenomenon – purely
quantitative and considering both quantitative and high-quality changes.
Considering the above-mentioned definitions, it is possible to draw a conclusion. Economic
growth is a special type of economic dynamics, which provides an increase in the indicators
characterizing volumes of national production. Real GDP in gross and per capita terms, the average
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annual growth rate of GDP, and also the size of the national income and industrial output which are
measured similar to GDP in gross and per capita terms can act as such indicators.
As it was already noted above, the main goal of economic growth is the growth of welfare and
national wealth. However, all countries have the different level of this indicator. To explain why
particular countries develop quicker than others; how to accelerate economic growth; what determines
the speed of increase in GDP, i.e. to understand intercountry and intertemporal distinctions in the level
of real GDP (and real GDP per capita) and its growth rates, it is necessary to analyze types and factors
of economic growth. The increase in production capabilities and growth of potential GDP are
connected with the change of either quantity of resources or quality of resources.
On a way of impact on economic growth, it is possible to distinguish direct and indirect factors.
Factors, which do growth physically possible, are considered as direct. This group includes following
factors:
1. Quantity and quality of the workforce.
2. Quantity and quality of natural resources.
3. The volume of fixed capital.
4. Technology and organization of production.
5. The level of enterprise abilities development in society.
Indirect factors are the conditions allowing realizing the opportunities which are available for
society to economic growth. Such conditions are created by factors of demand and distribution. At the
same time factors of demand are:
1. The growth of the consumer, investment, and public expenditures.
2. Expansion of export deliveries.
Factors of distribution are:
1. Conditions for business development, including:
1) the extent of the market monopolization;
2) tax climate in the economy;
3) barriers to an entrance to the market.
2. Political stability.
3. Corruption volumes.
4. The efficiency of a credit banking system.
5. Possibilities of redistribution of production resources in an economy.
6. The operating system of distribution of the income.
The extent of an impact of these factors on economy causes the type of economic growth, which
is meant as the extent of impact on the economic growth of quantitative and qualitative variables.
Two main types of economic growth should be highlighted:
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1. Extensive: growth is carried out thanks to a quantitative increase in factors of production. It
means that society uses more natural, labor and investment resources, which helps to receive an
increase of a national product.
2. Intensive: growth is carried out due to a high-quality improvement of production factors and
its best using. The increase of a national product results from the introduction of the new equipment
and technology, professional development of the labor, the better organization of work, more optimum
redistribution of resources between branches of an economy, etc.
In reality, it is impossible to meet neither extensive nor intensive economic growth in a "pure"
way. Speak about mainly intensive and mainly extensive economic growth, depending on what factors
– intensive or extensive prevail in the economy.
1.2 Theoretical bases of the modern concept of the human capital
Supporters of the human capital theory consider it both in narrow and in a wide foreshortening.
In narrow sense, the determining form of the capital is education. In a broad sense, the human capital
is formed by investments (long-term capital investments) into the person in the form of expenses on
education, workforce tutoring on production, health protection, migration and information search about
the prices and the income. G. Becker, the supporter of this approach, considers it in detail in the book
"Human Capital, Fertility, and Economic Growth" (1964) [Becker, 2010].
From the point of view of western economists category of the human capital determined by the
investment approach, where the influential part is investments. Therefore the track of investment effect
is often loosed, which is considered as an independent element in a separation from the process of
work. However, capital investments form in the person only abilities and skills, but the process of life
realization and the value creation happens only in the course of work.
Professors of the Oxford and Stanford universities P. A. David and J. G. G. Lopez allocate the
tangible and intangible human capital as a part of the human capital. Such indicators characterize the
tangible human capital as longevity, health, physiological characteristics of the person (body height,
force, endurance, vigilance, hearing, etc.). These qualities correspond to a wide range of the kinds of
activity of the person which firstly relating to physical work. The intangible human capital includes
such components as the abilities based on psychomotor characteristics of the person ("the know how",
"to be able to do"); cognitive abilities ("the know why", "to know what to do"); the procedural
abilities including creativity and innovation; the learning ability (ability to provide the solution of
many tasks at the same time), leadership and ability to operate the solution of complex problems,
social qualities and abilities (loyalty, trust, diligence, ability to interaction in collective ("the know
how", "to know who").
The theory of the human capital is based on achievements of the institutional theory, neoclassical
theory, Neo-Keynesianism and other private economic theories. The demand of the real economy in
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life promoted the appearance of this theory in economics and sciences, which are close to it. There was
a problem of profound understanding of a role of the person and the saved-up results of his intellectual
activity on rates and quality of development of society and economy. Statistical data of economies
growth of the developed world countries which exceeded the calculations and which are based on the
accounting of classical factors of growth became a push to creation of the theory of the human capital.
The analysis of real development and growth processes in modern conditions promoted the statement
of the human capital as the major productive and social factor of development of modern economy and
society.
The contribution to development of the modern theory of the human capital was made by T.
Shultz, G. Becker, E. Denison, R. Solow, J. Kendrick, S. Kuznets, S. Fabrikant, I. Fischer, R. Lucas
and other economists, sociologists, and historians.
The economic category "human capital" was formed gradually, and at the first stage was limited
to knowledge and ability of the person to work. In so doing, the human capital was considered for a
long time only as a social factor of development, an expensive factor, from the point of view of the
economic theory, which considers that investments into education and fostering are unproductive,
expensive. In the second half of the XX century, the relation to the human capital and education has
cardinally changed.
Therefore, I. Fischer gave the following definition to the human capital: “Human capital is a
measure of the incarnation in human of an ability to bring income. Human capital includes the innate
abilities and talent, as well as education and acquired skills“. Now, this definition possibly to consider
as an definition of human capital in narrow sense [Fischer].
T. Schultz has made a huge contribution to the formation of the theory of the human capital at
the initial stage of its development and the acceptance it by scientific community and promoting
[Shultz, 2011]. He was one of the first who has entered the concept of the human capital as a
productive factor, made many things for an understanding of a role of the human capital as main
engine and base of industrial and post-industrial economies.
T. Schulz considered that the main results of investments into the person are an accumulation of
abilities of people to work, their effective creative activity in society, maintenance of health etc. He
believed that the human capital possesses necessary signs of productive character. It is capable of
being collected and reproduced. According to T. Schulz, 75 percent of an aggregate cumulative
product produced in the society will be used on the accumulation of the human capital opposite to the
majority of reproduction theories in the 20th century, which considers only 25 percent of total values.
G. Becker has defined the human capital of the enterprise as the number of skills, knowledge,
and abilities of the person. According to him, investments have considered as general expenses for
education and training. Becker has estimated economic efficiency of education, firstly for the worker.
9
He has defined the additional income from the higher education as follows. The income of those who
have left college was subtracted from the income of workers with the secondary general education.
The direct expenses on education are costs, and alternative expenses — the missed income during the
training. G. Becker has estimated return from investments into education as the relation of the income
to expenses, having got about 12-14% of annual profit.
It is possible to distinguish Russian economists S.A. Dyatlov, R.I. Kapelyushnikov, A.V.
Koritsky, D.O. Neustroyev, V.D. Matveenko, who are working in the sphere of human capital surveys.
S.A. Dyatlov has given definition of the human capital as the certain stock of health, knowledge,
skills, abilities, motivations created as a result of investments and saved up by the person which are
expediently used it in the sphere of public reproduction, promote growth of labor productivity and
production efficiency and by that influence growth of earnings (income) of this person [Dyatlov].
S.A. Dyatlov disclosed the human capital; on the one hand, a form of expression of productive
forces of the person, on the other hand – a monetary assessment of the person’s ability to bring in the
income, which was formed because of investments into the person. In all works written by S.A.
Dyatlov practically, it is possible to consider questions of preservation and development of the
available human capital of Russia as the main priority of socioeconomic development of the country
and the policy persistently pursued by the government.
R.I. Kapelyushnikov considers the human capital as the stock of knowledge, abilities, and
motivations, which the person possess. In his opinion, it forms the capital because its formation
demands derivation of financial means to the detriment of the current consumption, but at the same
time, it is a source of productivity increasing of earnings in the future. Development of the managing
and labor motivation will allow liberating human potential that can serve as an impulse of crisis
overcoming in the domestic economy [Kapelyushnikov].
In the opinion of A.V. Koritsky the human capital is understood as knowledge, skills, and
abilities of the person which promote the growth of his productive force. It consists of the acquired
knowledge, skills, motivations and energy which people have and which can be used during the certain
period for production of goods and services. The author claims that productive qualities and
characteristics of the worker have been recognized as a special form of capital on the basis that their
development demands considerable expenses of time and material resources and, like the physical
capital, provides the higher income to the owner. At the same time, A.V. Koritsky pays attention to the
provision on expanded reproduction of workforce, to the allocation of the second type of a social
production by K. Marx – production of the person (consumer production), to differentiation of the
simple and more developed (specific) workforce [Koritsky, 2011].
K. Marx considered production of the person as the second type of a social production and
wrote that work which matters higher and considered as a more difficult work in comparison with
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average social activities is manifestation of such workforce which formation demands higher expenses
which production demands more working hours and which therefore higher costs, than ordinary
workforce. If the cost of this force is higher, then it is shown in privileged work and substantiated
therefore in rather higher costs in equal periods of time [Marx].
The result of production of physical and mental capacities to work is the qualified workforce
which capable of doing qualitative work. Complexity and quality of work are characteristics of labor.
The developed workforce is shown in difficult work, which can be implemented also in simple
circumstances. However, the ordinary workforce under no circumstances could be shown in difficult
work. It is possible to tell that the size of again created value is defined by multiplication of working
hours during which work was carried out, on the complexity of work (the size of the workforce) if
other circumstances are equal. Thus, the qualified workforce is capable of creating big value during
working hours, than ordinary workforce, but as it demands the bigger size of social expenditure, which
spent for its production, it has also the big cost of reproduction.
The view on the human capital as on a factor of economic system development in total with
dynamics of natural resources belongs to D.O. Neustroyev. In his work modification of Uzawa – Lucas
growth model for the purpose of an influence factors assessment of the human capital and natural
resources on the development of economic system within the uniform macroeconomic model has been
offered [Neustroyev]. Production function of the model has been presented in the specific form as
follows:
𝑦 = 𝐴𝑘 ∝ 𝑠 𝛽 (𝑏ℎ)1−𝛼−𝛽 ,
(1)
where y - a specific gross domestic product, A - the general level of technological development;
k - specific size of fixed capital; s - specific size of natural resources; h - the volume of the specific
saved-up human capital, b - a share of the human capital used in production.
In the modern urbanized economy, the increasing population density caused by his growth
promotes specialization of people and growth of investments into the human capital, and acceleration
of new knowledge accumulation. The most important general factor of economy efficiency increasing
is the growth scales with growth of the population, its density and an urbanization. G. Becker, E.
Glazer, and K. Murphy note that concentration of the population in the cities is very important for the
economy as there is the extensive division of labor and more human capital and new knowledge is
made. Moreover, the dense population in them promotes advanced specialization in professions, and
production of new knowledge and transmission of knowledge, skills, and motivations to the next
generations.
Empirical spatial (intercountry and interregional) surveys of the human capital influence on
economic growth yield very inconsistent results which arise because of variability and complexity of
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measurement of the most problem indicators used for an assessment of the size of the human capital.
In Russia, the most densely inhabited and urbanized regions, and first of all the megalopolises of
Moscow and St. Petersburg belong to regions with the increased level of the saved-up human capital.
Really, in them and in million-strong cities, the research, design and project organizations, higher
education institutions and the advanced knowledge-intensive productions are concentrated. In
scientific and technological centers, new knowledge is most intensively made, accumulated and
applied, and as it is possible to assume, these phenomena have to be shown in a more high efficiency
of all factors of production and higher income of the population, in comparison with worse the
inhabited and less urbanized regions. As R. Lucas notes, the urbanization can be the brightest example
the external effects of the human capital [Lucas].
The concentration of highly skilled personnel and the knowledge-intensive productions in the
large cities facilitates and accelerates having poured (diffusion) of new knowledge and technologies
from particular firms and branches in others, provides emergence of network external. The information
modulations localized in the cities promote the accelerated accumulation of knowledge and the human
capital that does the cities by engines of endogenous growth of regions.
At the same time physical and intellectual development of the person, vocational training and a
state of his health directly depend on a level of development of education, healthcare, culture and
recreational services, on volume and structure of food, consumption of household services, and also
other fields of activity directly or indirectly influencing behavior of the person.
When determining the human being as capital units, economists refer to the following
arguments. Firstly, costs of education, education, medical care of individuals admit quite real.
Secondly, the product of their work increases national wealth. Moreover, at last, expenses on the
person, which increase this product, will increase national wealth.
In the course of investment into the person, it is possible to mark out the main features of similar
investments:
1. In process of accumulation profitability of the human capital increases until the termination of
active work.
2. Character and types of investments into the person are caused by historical, national, cultural
peculiarities and traditions. Education level and choice of child’s future profession depends on
family traditions and parents education level.
3. High risk of such investments because of impossibility to sufficiently guarantee the expected
result.
4. Depreciation of the human capital is defined, firstly, by the degree of natural depreciation of a
human body, and secondly, the degree of his obsolescence owing to knowledge obsolescence
and change of the value of the received education.
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CHAPTER 2. REFLECTION OF THE HUMAN CAPITAL IN MACROECONOMIC
MODELS
2.1. Models with the human capital inclusion
The human capital - one of the main factors of economic growth of modern economies now. At
the same time the treatment of the concept "human capital" is ambiguous, as well as ways of an
assessment of the human capital. All this leads to the creation of various methods of his calculation, in
particular, the model of economic growth with the human capital.
Now there were different approaches to modeling of the human capital and economic growth
communication. Researchers focus the attention on consequences of accumulation of the human
capital (Uzawa – Lucas growth model), on economic growth and the financing of education
connection (Glomm and Ravikumar model), for roles of the human capital in adaptation of
technologies when knowledge is considered as a factor of innovative activity (Nelson-Phelps Model).
The models of economic growth considering the human capital become complicated on the structure
more and more. Therefore, two-sector models are created after one-sector models of growth in which
the aggregated output is described by one function and determined by the physical and human capital.
In two-sector models along with the function of product output process of "production" of the human
capital is separately described, effects of the impact of the human and physical capital on the economic
growth of the countries are specified.
The simplest model of endogenous growth is the AK-model developed by Sergio Rebelo in
1990, which allow the existence of linear dependence between the general output volumes and the only
factor - the capital. Capital goods are made by means of themselves; therefore, the rate of return is
defined only by technology in sector of capital goods. Consumer goods are made by means of capital
goods [Rebelo, 1993].
The general output in this model is set by the following function:
Yt = F(K t , Lt ) = AK t ,
(2.1)
where А>0 - an exogenous constant (parameter), and К - the cumulative capital. For simplicity it
is supposed that population is not changed (n=0).
Intensive form of production function:
yt = ƒ(K t ) = AK t .
(2.2)
In the model, dynamic balance of the financial markets or balance of gross investments and
savings is supposed.
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Accession rate of a capital-labor ratio is equal in a steady state to accession rate of a national
product per capita and to accession rate of per capita consumption.
The model is on a steady trajectory of growth and has no transitional trajectory, and assumes the
existence of positive accession rate of per capita indicators of a national product with dependence on
behavioral parameter r, which reflects subjective preferences of consumers. Positive accession rate is
reached on the assumption of return of the capital exceeds depreciation rate and a subjective discount
rate which reflects preferences of consumers.
The growth of savings ratio in model positively influences accession rate. Higher investments
and savings will correspond to higher continuous growth.
If to introduce the public expenditures and a proportional tax rate then accession rate taking into
account a state policy will be equal to this model:
g ∗ = σ((1 − τ)A − δ − ρ).
(2.3)
That is the received accession rate of the national income per capita depends now also on
institutional parameter – a proportional rate of income tax. Therefore, it is possible to draw a
conclusion that not only preferences of consumers influence growth rates of the economy, but also the
state, by means of tax rates and the tax credit.
The growth rate of AK model is no other than (the increasing) function of savings ratio. Thus, to
reach growth the government has to pursue the policy directed to increase in savings of the population.
The growth rate of AK model does not depend on its initial stock of the capital, so there is no
convergence between economies with various initial stocks of the capital even if they have the same
savings ratio, levels of depreciation rate and technology. Economic growth is possible even at zero
stocks of the capital. At the same time, technological progress and an increase in population are not
obligatory for increasing the income per capita (for growth counting per capita).
Also one of the most known models – the model created by G. Mankiw, D. Romer and D. Weil
(MRW model) [Mankiw]. G. Mankiw, D. Romer and D. Weil, assuming as a basis Solow's model,
consider the economy with the aggregated output of Y(t) set by production function from work L (t),
the capital of K(t) and the human capital of H(t):
Y(t) = K(t)αH(t)β[A(t)L(t)]1–α–β,
(2.4)
where A(t) characterizes technological level and changes in time with the set rate of g:
A(t)=A0egt; α – a contribution of increase in the capital to output change; β – a share of the human
capital in output growth (0 < α < 1, 0 < β < 1).
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In this model the human capital acts as production factor and process of his accumulation is
accepted similar for the physical capital:
dH
dt
= IH − μH H = sH Y − μH H,
(2.5)
where μH – coefficient of leaving of the human capital; SH – savings ratio for investments into
the human capital.
Subsequently, many researchers have carefully analyzed the MRW model, alternative ways of an
assessment of the human capital are offered.
Therefore, for example, Hall and Jones (1999), Bils and Klenow (2000), Kassel (2004) defined
production function as
Y= Kα (AH) 1–α
(2.6)
Here work H is supposed the uniform and depending on number of years of training E:
H=e φ(E) L,
where L – the labor, and e
(2.7)
φ(E)
defines its efficiency. Authors use exponential dependence, as
they believe that the salary can be presented as logarithmic function of number of years for education
[Hall].
S. Park considers such approach not deprived of shortcomings in the cause of lack of human
capital estimating, considered only its influence through efficiency of work of labor. However, the
human capital directly influences the level of output and, so has to be estimated more obviously.
Therefore, S. Park has offered his own method of calculation of the saved-up human capital based on
an assessment of investments in education [Park].
The level of investments in the human capital of sh, according to this method, is supposed to be
equal to the sum of direct (sh1) and indirect (sh2) investments into education referred to GDP. Direct
investments in education are carried out by the state and the private sector while indirect investments
are accepted equal to the alternative cost of training – to the income, which the student could receive
by working, but not studying. S. Park approximately estimates this income, based on an average salary.
S. Park carries out calculations for 22 countries and draws a conclusion about the importance of
indirect investments into education as sh1 and sh2 have turned out approximately equal.
In R. Lucas's model, which has received the name of "AK-model", production function has linear
dependence both on capital volume, and on the worker's capital-labor ratio:
15
Y = AK; y = Y/L = A (K/L) = AK,
(2.8)
where A – the technological parameter characterizing the cumulative productivity of factors
[Lucas].
R. Lucas proceeded from a formula of Cobb-Douglas
Y= Kα (AH) 1–α,
(2.9)
where H – level of the human capital of the representative agent in economy. He has assumed
that the equations of accumulation of the human and physical capital are identical:
dK
dt
= IK − μK и
dH
dt
= IH − μH,
(2.10)
and I = IK + IH. Further, equating their marginal productivities, he has established connection
between them:
H
K
=
1−α
α
(2.11)
Substituting this expression in an initial formula R. Lucas has received Y = AK, where
̅(1−α)1−α L1−α,
A= A
α
(2.12)
The main property of "AK model" is the constant marginal productivity of the capital.
Continuous return becomes possible thanks to the fact that the capital is understood in a broad sense
and includes not only the physical capital but also the human capital.
It is possible to distinguish professor of National research university "Higher School of
Economics" V.D. Matveenko from the Russian economists researching the human capital.
In work "Spatial economic growth model with human capital", he investigates the option of
Lukas endogenous growth model on the simple direct spatial structure. Therefore, production function
has formed a basis for model:
𝑌(𝑥, 𝑡) = 𝐴𝐾𝛽 (𝑥, 𝑡)[𝑢(𝑥, 𝑡)ℎ(𝑥, 𝑡) × 𝑁(𝑥, 𝑡)]1−𝛽 [𝑢𝑎 (𝑥, 𝑡)ℎ𝑎 (𝑥, 𝑡)]𝛾 ,
(2.13)
where K (x, t) — physical capital; u (x, t) — the share of not free time spent in production; h (x,
t) — human capital of a representative individual; N (x, t) — population; ua (x, t) — the average share
of not free time in this location used in production; ha (x, t) — average level of the human capital in
this location. The central planner maximizes the following function:
∞
∫0 ∫R C(x, t)e−ρt dxdt
(2.14)
16
Utility function is supposed to be linear on consumption per capita:
U(C(x, t)) = C(x, t) = c(x, t)N0 (x)eλt ,
(2.15)
where  — rate of an increase in population at the assumption that the human capital doesn't
move in space and makes external impact on process of production with elasticity of . At the same
time, change of size of the physical capital in time and space is described by the differential equation
in private derivatives:
𝜕𝐾(𝑥,𝑡)
𝜕𝑡
−
𝜕2 𝐾(𝑥,𝑡)
𝑑𝑥 2
= 𝑌(𝑥, 𝑡) − 𝐶(𝑥, 𝑡)
(2.16)
Change of the human capital is described by the following differential equation in private
derivatives:
dH
dt
= [δ(1 − u(x, t))]h(x, t).
(2.17)
where 1  u(x,t— a share of not free time which is spent for training.
After the carried-out transformations, the model of consumption per capita has been received:
c(x, t) = N
1
δ+(1−β)λ
( β
K 0 (x)
(x)
0
+
∂2 K0 (x)
∂x2
)×e
ρ−σ−λ
t
β
(2.18)
V.D.Matveenko at the simplifying assumption found trajectories of development of the physical
and human capitals, distribution of time for work in the production of goods and accumulation of the
human capital, and consumption, which are the solution of a problem of function optimization of
public welfare in an explicit form. In addition, it has been revealed that the more an initial stock of the
human capital in this location, the bigger time is spent in this location for the accumulation of the
human capital at each time point. On the contrary, the more the initial stock of the physical capital, the
more time is spent for work in the production of goods. It quite corresponds to the specialization of
geographical areas on different types of activity, which takes place actually. In addition, the model
shows that the more a share of the physical capital in location, the more people work there. The society
is more impatient (the more value of the  parameter), the fewer people study and work in the
production of goods more [Matveenko].
2.2. Inclusion of human capital to Input-Output models
We will consider the description of dynamic models which structure joins the human capital. In
particular, one of them can be found in work Hongxia Zhang and Xikang Chen "An Extended InputOutput Model on Education and the Shortfall of Human Capital in China" [Zhang]. According to the
17
author, education is the form-building factor of the human capital which does not have physical
expression and consisting in an increase in knowledge, qualification, and skills which are gained by
students. At relative complexity of measurement of a quantity of these indicators, the author divides
students into various education levels. Therefore, students who intend to continue education in the
period following for investigated enter into the first group, the second includes students who stop
education and come to work.
In this article, the extended input-output model on education for the human capital including the
static and dynamic version with the purpose to analyze the interaction between education and other
sectors is used which based on the extended input-output table on education. We will consider the
formation of these models in more detail.
The extended input-output table on education, which purpose to show production and
distribution of the human capital and its interaction with growth and development of sectors have
formed for their removal base.
The table consists of three parts. The top part – input-output table including 19 sectors – the first
15 reflect not educational sectors (agriculture, mining and so on), and the last four - educational.
PP
W=[W EP
W
W PE ], c=(c P ), F=[F P ], y=(y P ), x=(x P )
W EE
cE
0
xE
0
(2.19)
The 19 x 19 matrix W gives the intermediate deliveries, the vector c the private and government
consumption, F the 19 x 19 matrix with the capital formation (including fixed capital formation and
changes in inventories), y the vector of other final demands, x the vector of gross outputs. The row
vector v' = ((vP)', (vE)') gives the value added items (including payments for labor and capital, imports,
and operating surplus). Input coefficients aij=wij/xj yields x = Ax + c + Fi + y, where i denotes the
summation vector consisting of ones. In the upper part of Table 1, the education sectors show the
relationship of educational funds and non-education sectors.
The middle part of Table 1 describes the education system for students, which is called "student
input table". Let element qj of the 4 x 4 matrix Q indicate the number of students that are in school
type i in period t and in type j in period t + 1. The element hj of the 4 x 19 matrix H gives the number
of students of school type i that leave the education system in period t and become a member of the
labor force in sector j ( = 1,..., 19). The vector r represents the students that leave the education system
but are not added to the Chinese labor force (for example, those who go abroad). The row vector s't+ 1
gives the inflow of new students in period t + 1 into the education system. The row sums (i.e. vector zt)
gives the total number of students participating in the education system in period t. The column sums
(i.e. row vector z't+1) give the total number of students in each school type in period t + 1. Defining
18
input shares as uij = qij/zj(t + 1) gives the share of students in school type j in period t + 1, who were in
school type i in period t. This yields zt = Uzt+1 + Hi + r. Because the education sector is reflected both
by educational funds and students, both parts in Table 1 reflect the same production: that of human
capital.
The lower part of Table 1 is for the holding of assets, including fixed assets, human capital, and
circulating capital. It shows the essential conditions and basic factors that the production in each sector
requires. The classification of fixed assets is the same as that in non-education sectors, and that of
human capital is the same as that in the education sectors.
In classical input-output (IO) tables, the education sector is a tertiary industry, a kind of service.
Its income recorded in the rows (i.e. the output in an IO table) refers to the sources of educational
funds, while its outlays recorded in the columns (i.e. inputs in an IO table) are the uses of educational
funds. These monetary flows are reflected in the "monetary IO table", i.e. the upper part in Table 1. If
to look at this sector as producing human capital, the output of education is students acquiring
knowledge and skills, it is reflected in the middle part of Table 1 by a separate table termed ‘student
input table’. Educational funds and students are two sides of the same production process of education.
For educational funds, the rows corresponding to the education sector in the monetary IO Table l
account for the sources of the funds while its corresponding columns account for the use of the funds.
For student flows, the rows in the student input table show the distribution or output of students, while
the columns represent the sources or input of students that will be educated. The purpose of the
extended IO table on education is to show the production and distribution of human capital and its
relation to the growth and development of sectors. It should be noted that human capital here refers to
students at different educational levels.
In the extended IO table and model on education, the economy is divided into two subsystems.
These are, non-education sectors (1… к=15) and education sectors (k + 1... n = 19). The upper part in
Table 1 shows that other sectors send the students to the education sector in order to increase their
human capital to the education sector. Consequently, the education sector obtains the funds, buys
products and equipment from other sectors, and performs the educational process in order to make the
students more qualified. Next, when students graduate, they will enter industries and become an
important factor of production.
The human capital production sector refers to the education sector (which does not include
public health or other related sectors). The output of the education sector is the students’ human capital
accumulation in the education sector during a certain period. The intermediate demand of the
education sector is the part of the student population in this period that remains in the education sector
in the next period to continue their education process. The final demand of the education sector is the
part of the student population that leaves the education sector and enters production in industries in the
19
next period. The intermediate inputs of the education sector are the students that were in the education
sector in the previous period and continue their education in this period.
Table 1. The extended input-output table on education
Monetary input-output table
Final demand
Intermediate demand
Fixed capital & inventories
Education
Consump
Noneducation
sectors k
Noneducation
Education
tion
sectors 1, . . . ,
+ 1, . . . ,
sectors
sectors
k
n
Noneducation
sectors 1, . . . ,
k
Education
sectors k + 1, .
..,n
Primary inputs
Total input
Othe
r
Total
output
WPP
WPE
cP
FPP
FPE
yP
xP
WEP
WEE
cE
0
0
0
xE
(v P) '
(x P)'
(v E)'
(x E) '
Student input table
Final demand
Human capital
Intermediate demand
Noneducatio
n sectors 1, .
..,k
Education
sectors k +
1, . . . , n
Primary
inputs
Total input
Education
sectors k + 1,
...,n
Consumpt
ion
Noneducation
sectors
Education
sectors
Other
HEP
HEE
zt
Q
Total
output
s't+1
z't+1
Asset holding table
Intermediate demand
Fixed
assets 1, . .
.,k
Human
capital
sectors k +
1, . . . , n
Noneducatio
n sectors 1, .
..,k
Education
sectors k + 1,
...,n
OPP
OPE
OEP
OEE
Final demand
Total
output
The source: Zhang J., Chen X. An Extended I-O Model of Education and the Shortfall of Human
Capital in China // Economic Systems Research. Vol. 20, No 2, 2008, p 208.
20
First of all the author pays essential attention to the creation of the statistical model, which has
been constructed based on Table 1. For a monetary part:
X = Ax + c + Fi + y,
(2.20)
where А=W Δx̂-1 the matrix of input coefficients aij = wij/xj
For student flows, the model is
Qi+Hi+r= zt.
(2.21)
The student input coefficient matrix was defined as U = Q(ẑt+1)-1, where uj represents the ratio of
the students from the ith education level in the current period to the total students of the jth level in the
next period (the percentage in level j that come from level i).
Then equation can be written as:
zt = Uzt+1+Hi+r=Uzt+1+h,
(2.22)
After a number of calculations, the author receives the equation
z = (I-U)-1h
(2.23)
Next, the connection of the student input model to the IO model was introduced. The total costs
for each education sector were given by the corresponding element of the vector x E. The costs per
student are then given by the vector p =(ẑt)-1xE, where pi means the funds consumed per student in the
ith educational level (i = 1,...,4).
Hence, xE = 𝑝̂ 𝑧t. Using equation (2.23) author got xE = 𝑝̂ (I— U)-1h. This means that the
educational funds in the current period related to the human capital formation in future years.
Based on the carried-out calculations, the author transforms the equations to the following form:
P
PP
(x E )=[AEP
x
A
APE ] (x P )+(c P + F PP i + F PE i + y P )
AEE x E
cE
(2.24)
or
x P = APP x P + APE x E + c P + F PP i + F PE i + y P
(2.25)
x E = AEP x P + AEE x E + c E
(2.26)
Here, an element (i, j) AEP is the relation between educational funds from the noneducational
sector of j which are used for formation of the human capital in the sector of formation of i, and
21
production of noneducational sector. AEE represents a matrix of educational coefficients of a stream of
funds among education sectors. The equation (2.26) describes the model for education in cash flows
from the point of view of educational funds sources; cE represents a vector of educational funds of
households and the government (a tuition fee and government grants).
One of the assumptions of the author were that the studying population is defined by formation
of the human capital (h), and educational funds (cE) have to adapt according to the studying
population. Here h and cP+yP+FPPi+FPEi are exogenous. Using z = (I-U)-1h, xE = 𝑝̂ (I— U)-1h and
(2.25), the author has received:
x P = (I-APP )-1 (APE p̂ (I— U)-1h+c P + F PP i + F PE i + y P
and substitute it into equation (2.26),
c E =(I-AEE )p̂ (I— U)-1h - AEP x P
The dynamic model became the following stage for a research. The purpose of dynamic interindustry model consists that it connects the current production with the future by means of a matrix of
the coefficient of expenses of fixed capital, dynamically analyzing sector interactions. In classical
dynamic inter-industry model only the material capital is included; in expanded inter-industry model
by training the human capital is also considered. The author provides the table where the accumulation
of the capital (gain of fixed capital and change in material stocks) and formation of the human capital
is given in a matrix form and reflects distribution among sectors of all types of the capital and human
capital. Meanwhile, fixed assets and the human capital, which are carried out or used, are also
presented in a matrix.
The sector of education does not promote the formation of fixed capital. BPP =FPP(Δx̂P)-1 and
BPE=FPE(Δ𝑧̂ ) -1, ΔxP=xPt+1 - xPt and Δz= zt+1 - zt. FPP - a matrix of the coefficient of expenses of fixed
capital in the noneducational sector and FPE a matrix of the coefficient of expenses of fixed capital in
the educational sector. An element (i, j) both F-matrixes shows the demand of j sector for the fixed
capital made by i sector or volume of the capital which the j sector buys from sector i. Therefore b ijPP
indicates the volume of the capital of i sector demanded an increase in production j noneducational
sector, but bijPE indicates the volume of i capital which is required if at j educational sector has
increased by one student.
The human capital coefficient matrices are defined in the same way. That is, BEP =HEP(Δx̂P)-1 and
BEE=HEE(Δ𝑧̂ ) -1. Note that bijEP is measured in students per monetary unit, and it represents how many
students of the ith type are needed if the jth non-education sector increases output by one unit. bijEE
22
indicates how many students of type i are required when the jth education sector increases by one
student.
Substituting xE = 𝑝̂ zt, FPP = BPP(AxP) and FPE = BPE(Δ𝑧̂ ) into equation (2.25), and substituting
HEP = BEP(Δx̂P) and HEE = BEE(Δ𝑧̂ ) into equation (2.22) yields
xPt =APPxPt + APEp̂zt+ BPP(xPt+1 - xPt)+ BPE(zt+1 - zt)+ cPt+ yPt
(2.27)
zt=Uzt+1+ BEP(xPt+1 - xPt)+ BEE(zt+1 - zt)+ rt
(2.28)
The model also can be solved by forwarding deduction, if we know xP0, z0 at the beginning of the
planning period, while the net final demands cPt, yPt and rt are given exogenously. Another way to
analyze the model is as follows: when we know that there is a stable growth rate (of l) in the output of
the non-educational sectors during the planning period, we can calculate how the output in the
education sectors changes and what the student population might be. This is what we will discuss in
the fifth section.
Material capital and human capital are both worn down during production, which means a loss of
productive capacity. Part of fixed capital formation and part of human capital formation will thus be
used as replacement requirements, while the other parts are used to expand production capacity. We
define the matrices with the asset coefficients for fixed assets and human capital as: C PP = OPP(ΔxP)-1;
CPE=OPE(Δz) -1; CЕP =OЕP(ΔxP)-1; CЕE=OЕE(Δz) -1. For example, fixed assets held and used per unit of
output in the jth non-education sector; сPPij means the amount of the ith human capital required per unit
of jth level students. Let the diagonal matrix with the replacement requirement rates of fixed assets be
given by βP, and the matrix for human capital by βЕ. Then the author got the following equations:
xPt =APPxPt + APEp̂zt+ BPP(xPt+1 - xPt)+ BPE(zt+1 - zt)+ β̂Р CPP xPt + β̂Р CPЕ zt + cPt+ yPt
(2.29)
zt=Uzt+1+ BEP(xPt+1 - xPt)+ BEE(zt+1 - zt)+ rt + β̂Е CЕP xPt + β̂Е CЕЕ zt
(2.30)
All above-mentioned models describe macroeconomic dynamics, relying on the idea of the
human capital.
23
CHAPTER 3. ASSESSMENT OF HUMAN CAPITAL INFLUENCE ON PRODUCTION
DYNAMICS OF RUSSIA
The finding of economic growth dependence on various factors growth is an important
diagnostic task. The optimum tool for the analysis and an assessment of economic growth, including
for definition of the key factors, which are directly influencing the economic growth of the economic
system, are regression models.
The regression analysis – a method of modeling of the measured data and a research of their
properties. Basic data consist of a combination of values of a dependent variable (a response variable)
and independent variables (explaining variables). It is supposed that the dependent variable is the sum
of values of the particular model and random variable. The regression analysis is used for the forecast,
the analysis of time series, testing of hypotheses and identification of the hidden interrelations in data.
In our work for an assessment of the saved-up human capital size influence on economic growth
in Russia, we will take regression model in which, respectively, GDP will be the dependent variable,
having five independent variables, namely:
1. The size of the saved-up human capital (billion rubles).
2. Investments into fixed capital (billion rubles).
3. The size of fixed capital (billion rubles).
4. Europe Brent Spot price (dollars per barrel).
5. The volume of money supply M2 (billion rubles).
The equation of regression can be written as:
∂ 𝑌𝑡 = 𝛼 ∂ 𝐵𝑟𝑡 + 𝛽 ∂ 𝑀𝑡 + 𝛾 ∂ 𝐻𝑡 + 𝜗 ∂ 𝐾𝑡 + 𝜑 ∂ 𝐼𝐾 𝑡 + 𝜀𝑡 + 𝑐,
(3.1)
where ∂ 𝑌𝑡 – GDP increasing at the moment of time t, ,∂ 𝐵𝑟𝑡 – increasing of the Europe Brent
Spot price at the moment of time t, ∂ 𝑀𝑡 – change of volume of money supply М2 at the moment of
time t, ∂ 𝐻𝑡 – increasing of the saved-up human capital size at the moment of time t, ∂ 𝐾𝑡 – increasing
of the fixed capital size at the moment of time t, ∂ 𝐼𝐾 𝑡 – increasing of investments size into fixed capital
at the moment of time t, 𝜀𝑡 - an error of the equation of regression, c – constant.
3.1. Preparation of data
For the creation of the information base, which is necessary for calculations implementation, the
state statistical committee editions, including the Russian statistical yearbooks from 1993 for 2015,
collections of Russian national accounts from 1993 for 2015 have been used. For calculation, we took
time series of data of 23 years, from 1993 to 2015. The reason of becoming 2015 the last year of our
research is what at the time of preparation the data of full statistics on the considered variables for
2016 has not been published in access.
24
Data on the volume of money supply equated to the comparable prices with using the GDP index
deflator. GDP, investments into fixed capital and the size of fixed capital was equated by means of the
corresponding growth rates. Data on the size of the saved-up human capital was equated to the
comparable prices with use of the GDP index deflator and consumer price index. Use of a consumer
price index is used due to the fact of the majority of human capital costs in our assumption represent
consumer expenses, therefore, we claim that equating of this indicator to the comparable prices by the
following method gives a more realistic idea of the considered value.
At the same time, it should be noted that for calculation also the qualifier of individual
consumption on the purposes adapted to a consumer price index (KIPC) has been approved. However
as it has been entered in 2010, we have stopped on a consumer price index of an elder sample. Now we
will present calculation of the size of the saved-up human capital in more detail.
In addition, we have carried out the calculation of the saved-up human capital at the regional
level, data on which have been provided to the comparable prices similarly by means of the GDP index
deflator and a consumer price index. For calculation a time row of 13 years, from 2003 to 2015 has
been taken. As the reason the fact that till 2003 regions published data generally on social and cultural
events where besides costs of the human capital, also other investments were included, in particular,
costs of mass media and others.
3.2 Calculation of size of the saved-up human capital at the macro level
There is a close interrelation between the development of the economy and the human capital,
investments into it in the long-term period are considered as more recoup. The concept of investments
is meant first as the financing of social policy, health care, culture, sport, and education. At the same
time, the main source of information for the analysis of these public social expenditures in Russia are
given to the budgetary reporting. The Federal Treasury publishes monthly, quarterly and annual
reports on budgets acting of all Russian budgetary system levels in open access on the Internet portal.
Data on the income, expenses, and sources of financing of deficiency of budgets are presented in it.
As it has been noted earlier, there is a set of approaches to an assessment of the size of the
human capital. The expensive approach will be used further whereas expenses on the accumulation of
the human capital expenses on social policy, education, culture and cinematography, health care,
physical culture and sport, which participate further in his formation, will be included. For an
assessment of the saved-up human capital, we will use a perpetual inventory method, which is used in
the European countries for an assessment of the saved-up fixed capital in an economy based on the
current investment streams due to the lack of the direct accounting of fixed assets by the state
statistical organizations.
Thus, accumulation of the human capital will take place according to:
25
Vt+1 = Vt + Jt+1 – St,
(3.2)
where Vt and Vt+1 — the overall cost of the capital for the beginning of t and (t + 1) years;
Jt+1 — investments into the capital in the t+1 year;
St — leaving of the capital in t year.
Further, there is a question of the size of left of the human capital. The human capital, also, as
well as the fixed capital, depreciate over time, so it has a certain service life. On average, the educated
person works 30-35 years that is the depreciation rate is approximately equal to 3%. However, there
can be also such situation that the person can work in a bigger term, and it gives other (smaller)
depreciation rate. Also besides physical depreciation of the capital and aging of an individual, there is
a moral obsolescence, for example, an emergence of the modern equipment, which demands new skills
of work and which the person does not have, so the worker cannot bring benefit in the same volume
anymore that brought earlier. That is the norm of depreciation of the human capital becomes higher
than average. In this work, we have considered three cases of depreciation: 2.5%, 3%, and 3.5%. We
will designate them for X.
Regard to this, we can rewrite a calculation formula as follows:
Vt+1 = Vt + Jt+1 –XVt.
(3.3)
Calculation of the human capital cost in the first year of the considered period will be calculate
by a perpetual inventory method:
1+𝑔
𝑉1 = 𝐽1 (𝑔+𝑠 ),
(3.4)
where g – average rate of an increase of investments (we take it equal 0,067, proceeding from
calculations);
s – leaving norm of the capital;
For calculation the following ranks of data were used, which forms the cost of the human capital
of 𝐽𝑡 (Table 2):
1. Expenses for education (𝐸𝑡 ).
2. Expenses on health care, physical culture, and sport (𝐻𝑡 ).
3. Expenses on culture and cinematography (𝐾𝑡 ).
4. Expenses on social policy (𝑆𝑃𝑡 ).
All data have been provided to the comparable prices with the use of the GDP index deflator for
investments in the sphere of social policy and a consumer price index for investments on health care,
physical culture and sport, culture and cinematography, and education (Table 2).
26
Table 2. Elements of the government investments into the human capital in the comparable prices of
2015 (billion rubles)
1993
Education
Health care, physical
culture and sport
Culture
Social policy
1943,5
1521,2
294,3
264,0
1994
1687,5
165,3
344,4
916,1
1995
1592,7
1112,5
313,0
584,6
1996
1623,0
1126,5
314,0
710,8
1997
1378,6
1278,6
347,2
1068,7
1998
942,5
835,6
189,0
915,3
1999
1110,1
996,6
222,4
760,3
2000
1354,2
1199,7
251,2
764,6
2001
1475,7
1158,5
218,5
1136,7
2002
1728,5
1239,9
243,1
2780,8
2003
1689,7
1191,8
247,9
1246,1
2004
1857,3
1289,6
254,6
1310,5
2005
2225,4
2632,8
459,7
5458,5
2006
2441,4
2485,1
475,4
5568,4
2007
2742,5
3132,7
542,0
5914,3
2008
2934,5
3015,9
592,1
6622,2
2009
2905,2
2829,8
555,6
8134,8
2010
2958,9
2700,0
557,2
9326,7
2011
3288,2
3011,3
440,1
8481,8
2012
3409,1
3267,0
442,9
9297,5
2013
3573,5
3079,4
444,1
10052,2
2014
3302,1
3095,9
439,3
9479,5
2015
3034,6
3115,9
395,6
10479,7
The source: Constructed by the author on the base of statistical data - Russian statistical
yearbook 1993-2015 year // The consolidated budget welfare expenditures – URL:
http://www.gks.ru/bgd/regl/b04_13/IssWWW.exe/Stg/d040/i041360r.htm (date of the access 11.04.
2016). Federal State Statistics Service // National accounts // GDP // Annual data // GDP indexdeflator – URL: http://www.gks.ru/free_doc/new_site/vvp/vvp-god/tab4.htm (date of the access
08.04.2017). Federal State Statistics Service // Central base of statistical data // Consumer price
indexes - URL: http://www.gks.ru/dbscripts/cbsd/dbinet.cgi?pl=1812002 (date of the access
05.02.2017).
Besides the government expenditures, we found the private investments on such components as
education, health care, physical culture and culture (Table 3). Data have been provided to the
comparable prices by using of a consumer price index.
27
Table 3. Elements of private investments into the human capital in the comparable prices of 2015
(billion rubles)
Education
1993
Health care, physical culture and sport
Culture
41,7
118,0
27,8
1994
55,5
145,4
30,9
1995
79,1
197,1
54,7
1996
116,7
238,2
71,1
1997
142,1
283,9
93,7
1998
166,5
285,2
70,7
1999
212,9
328,1
82,2
2000
262,0
364,0
87,9
2001
297,4
388,9
101,5
2002
307,7
392,8
111,3
2003
339,1
400,2
137,4
2004
382,2
440,6
153,9
2005
415,4
471,6
155,1
2006
453,9
504,1
157,1
2007
493,4
528,4
129,0
2008
507,1
544,7
127,0
2009
505,3
534,5
129,3
2010
41,7
118,0
27,8
2011
55,5
145,4
30,9
2012
79,1
197,1
54,7
2013
116,7
238,2
71,1
2014
142,1
283,9
93,7
2015
166,5
285,2
70,7
The source: Constructed by the author on the base of statistical data - Federal State Statistics Service //
Central base of statistical data // Volume of private investments - URL:
http://www.gks.ru/dbscripts/cbsd/dbinet.cgi?pl=1812002 (date of the access 05.02.2017). Federal State
Statistics Service // Central base of statistical data // Consumer price indexes - URL:
http://www.gks.ru/dbscripts/cbsd/dbinet.cgi?pl=1812002 (date of the access 05.02.2017).
28
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
Education
Healthcare, physical culture and sport
Culture
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
0%
Social policy
Figure 1. Investments structure change into the human capital 1993-2015 year
The source: Constructed by the author on the base of Table 2 and Table 3
To receive total investments (Figure 1), we plus all expenses on separate elements of investments
into the human capital, and then we summarize already all expenses on the social and culture sphere,
thus the equation of investments into the human capital has the following form:
𝐽𝑡 = 𝐸𝑡 + 𝐾𝑡 + 𝐻𝑡 + 𝑆𝑃𝑡
(3.5)
Then taking into account the previously mentioned, the equation of an assessment of the overall
cost of the human capital will have the following form:
𝑉𝑡+1 = (1 − 𝑋)𝑉𝑡 + 𝐸𝑡+1 + 𝐾𝑡+1 + 𝐻𝑡+1 + 𝑆𝑃𝑡+1
(3.6)
Substituting our data given in the equation to the overall cost of the saved-up human capital, we
will receive the time series presented in Table 4.
29
Table 4. The size of the accumulated human capital (billion rubles)
The size of the saved-up
human capital (2.5%)
The size of the saved-up
human capital (3%)
The size of the saved-up
human capital (3.5%)
1993
38901,4
37324,4
35870,2
1994
41273,8
39549,6
37959,8
1995
44175,6
42296,8
40564,9
1996
47271,4
45228,1
43345,3
1997
50682,4
48464,0
46420,9
1998
52820,2
50414,9
48201,0
1999
55212,3
52615,0
50226,6
2000
58115,6
55320,2
52752,3
2001
61439,8
58437,8
55683,1
2002
66708,1
63488,8
60538,4
2003
70292,5
66836,3
63671,7
2004
74223,8
70519,9
67131,8
2005
84186,7
80222,7
76600,7
2006
94167,4
89901,4
86005,0
2007
105295,6
100686,7
96477,2
2008
117006,6
112009,5
107443,9
2009
129675,8
124243,6
119277,7
2010
143154,0
137236,5
131823,2
2011
156001,1
149545,2
143635,2
2012
169752,8
162710,7
156259,8
2013
184028,6
176348,9
169310,3
2014
197115,9
188746,5
181072,4
2015
210609,5
201505,6
193156,4
The source: Constructed by the author on the base of the Table 2
In the received results, the positive dynamics of change of size of the human capital is traced.
After carrying out calculations of growth rates, it has been revealed that the size of the human capital
30
for the considered period has increased about 5.4 times. In addition, it should be noted the fact that a
share of expenses of the government on such important factor for accumulation of the human capital as
education, is reduced every year. However, the government expenditures have increased by education
for the considered period by 1.4 times, and the volume of private investments (service of paid
education) by 12.9 times.
3.3 Calculation of size of the saved-up human capital at the regional level
For calculation of the size of the saved-up human capital at the regional level, we will use also an
expensive approach whereas expenses on the accumulation of the human capital expenses on
education, culture and cinematography, health care, physical culture and sport, which participate
further in his formation, will be included. For an assessment of the saved-up human capital, we will
use a perpetual inventory method with the depreciation rate 3%.
For standardization of data and a competent assessment, we have considered regional reforms,
namely:
1.
Association of the Perm region and Komi-Permyak Autonomous Okrug to Perm Krai
(2005).
2.
Association of Taymyr and Evenki Autonomous Area to Krasnoyarsk Krai (2007).
3.
Association of the Kamchatka region and the Koryak Autonomous Area to Kamchatka Krai
(2007).
4.
Association of Ust-Orda Buryat Autonomous Area to the Irkutsk region (2008).
5.
Association of the Chita region and the Agin-Buryat Autonomous Area to Zabaykalsky Krai
(2008).
6.
Association of the Republic of Crimea and federal city of Sevastopol (2014).
All data have been provided to the comparable prices with the use of the GDP index deflator and
a consumer price index for investments on health care, physical culture and sport, and education
(Table 5).
In the results received by us, positive dynamics of human capital size change of all Russian
Federation subjects is traced. After carrying out calculations of growth rates, it has been revealed that
the largest growth is traced in the North Caucasian Federal District where the human capital size for
the considered period has increased by 3.2 times. This fact is explained by a big contribution of the
Chechen Republic where an increase by 10.4 times is traced. The most cardinal increase can be seen in
the St. Petersburg city – 11.8 times. The smallest gain is observed at the Siberian, Far Eastern and
Crimean Federal Districts (Table 6).
At the same time, it should be noted that for this period the city of Moscow became the leader in
a contribution to education, additionally in top five the Moscow region, the St. Petersburg city,
Khanty-Mansi Autonomous Okrug and Sverdlovsk region. In a research of such factor as health care,
31
physical culture and sport and culture remains the same situation with the only replacement of the fifth
place by Krasnodar Krai. Among the last such regions as the Altai Republic, the Jewish Autonomous
Oblast, the Republic of Kalmykia and the Republic of Adygea. The more detailed information about
investments and dynamics of saved-up human capital by regions is possible to see in Appendix 1.
Table 5. Expenses of the consolidated budgets of the Russian Federation subjects on the human capital in the comparable prices of 2015 on federal
districts (billion rubles)
2003
Central Federal
District
Northwestern
Federal District
Southern Federal
District
North Caucasian
Federal District
Volga Federal
District
Ural Federal
District
Siberian Federal
District
Far Eastern
Federal District
Crimean Federal
District
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
843,9
902,6
1072,2
1280,1
1453,2
1531,3
1636,6
1586,5
1701,6
1836,0
1738,8
1662,8
1560,8
345,5
375,2
441,8
500,7
552,6
606,6
625,0
593,1
593,3
552,1
577,9
599,6
578,4
211,8
219,2
242,5
276,0
318,2
326,3
648,6
363,4
360,5
408,3
392,5
399,6
380,7
121,7
163,3
136,0
157,8
190,2
200,1
421,4
220,1
229,9
241,0
250,3
259,1
254,6
545,5
557,1
656,8
717,8
794,6
774,1
848,0
850,5
872,3
903,0
917,8
917,8
858,7
373,8
410,1
494,9
542,1
613,8
592,5
544,1
543,2
568,9
607,8
614,2
596,3
567,3
453,0
476,0
530,0
591,5
656,6
653,2
675,6
661,4
684,3
714,8
729,8
725,1
682,2
239,2
239,4
259,1
279,1
304,4
306,5
335,5
335,9
344,9
362,5
398,1
398,1
375,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
107,8
66,0
The source: Constructed by the author on the base of statistical data - Regions of Russia // The consolidated budget welfare expenditures of regions –
URL: http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156 (date of the access
08.11.2016). Federal State Statistics Service // National accounts // GDP // Annual data // GDP index-deflator – URL:
http://www.gks.ru/free_doc/new_site/vvp/vvp-god/tab4.htm (date of the access 08.04.2017).
Federal
State
Statistics
Service
//
Central
base
of
statistical
data
//
Consumer
price
indexes
URL:
http://www.gks.ru/dbscripts/cbsd/dbinet.cgi?pl=1812002 (date of the access 05.02.2017).
33
Table 6. The size of the saved-up human capital of the Russian Federation subjects on federal districts (billion rubles)
Central Federal
District
Northwestern
Federal District
Southern Federal
District
North Caucasian
Federal District
Volga Federal
District
Ural Federal
District
Siberian Federal
District
Far Eastern
Federal District
Crimean Federal
District
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
10361,7
10953,5
11697,1
12626,2
13700,7
14821,0
16013,0
17119,1
18307,2
19594,0
20745,0
21785,4
22692,7
4729,7
4963,0
5255,9
5599,0
5983,6
6410,7
6843,4
7231,2
7607,5
7931,4
8271,4
8622,9
8942,6
1944,6
2105,4
2284,8
2492,2
2735,6
2979,9
3539,0
3796,3
4042,9
4329,9
4592,5
4854,3
5089,3
940,8
1075,8
1179,6
1302,0
1453,2
1609,7
1982,8
2143,5
2309,1
2480,8
2656,7
2836,1
3005,6
8054,2
8369,7
8775,4
9229,9
9747,6
10229,3
10770,5
11297,9
11831,2
12379,2
12925,7
13455,7
13910,7
5666,1
5906,2
6223,9
6579,2
6995,7
7378,3
7701,1
8013,3
8341,7
8699,3
9052,5
9377,3
9663,2
7104,1
7366,9
7675,9
8037,1
8452,6
8852,2
9262,2
9645,7
10040,6
10454,1
10870,3
11269,3
11613,4
3586,6
3718,4
3865,9
4029,0
4212,5
4392,6
4596,3
4794,4
4995,4
5208,0
5449,9
5684,4
5888,9
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
0,0
107,8
170,6
The source: Constructed by the author on the base of the Table 5
3.4 The Russian Federation territorial subjects rating on the human capital expenditures
dynamics
Also based on reports on the performance of the Russian Federation territorial subjects
consolidated budgets published on the website of Federal Treasury we have made the territorial
subjects rating on the human capital expenditures dynamics (Appendix 2).
The technique of rating assumes ranking of regions on a growth rate of the sum of indicators
"Expenses of the consolidated budget of the Russian Federation territorial subjects – Education,
Healthcare, Physical culture and sport, the Social policy" in 2015 in comparison with 2014. The rating
allows estimating a vector of focus of regional budgets on the development of the personality.
For the rating constructing, we needed such data as expenses of the Russian Federation regions
consolidated budgets on expenditures stated above, and in general, data on the population of regions.
For an assessment the following ranks of indicators we have been receiving: social expenditures of
consolidated budgets changing in 2015 year in compliance with 2014 year, share of social
expenditures in consolidated budgets in 2015 year, volume of social expenditures per capita in 2015
year (thousand rubles per capita), share of social expenditures in consolidated budgets in 2014 year,
volume of social expenditures per capita in 2014 year (thousand rubles per capita), consolidated
expenditures changing of 2015 year in compliance with 2014 year.
The first place in rating the Bryansk region holds, which has increased in 2011 expenses of the
consolidated budget on social policy, education, health care physical culture and sport by 17.1%. The
share of these expenses in the consolidated budget was 60.4%. On the 2nd place – the Chechen
Republic which has increased budgetary appropriations by 14.4%. In addition, the volume of
investment into the human capital and in terms of one inhabitant in the republic is higher than average
Russian. In top five of rating also Smolensk region (+11.8%), the Leningrad region (+11.7%) and the
Republic of Khakassia (+9.2%).
The greatest share of expenses on social policy, education, health care, physical culture and sport
in the structure of expenses of the consolidated budget at the Chechen Republic and Chelyabinsk
region where the indicator exceeds 67%, at the average Russian level of 58,7%. At 48 regions, the
share of expenses on social policy, education, health care, physical culture and sport exceeds 60%.
In per capita terms the absolute leader in expenses for social policy, education, the health care
physical culture and sport is the Nenets Autonomous Okrug (228,8 thousand rubles on the person
against 41.5 thousand rubles across the Russian Federation in general).
Among all Russian Federation territorial subjects in 2015, 31 regions decreased in volumes of
the budgetary expenses on social policy, education, health care physical culture and sport. However
high value of an indicator on the absolute volume of expenses of the consolidated budgets on social
policy, education, health care physical culture and sport on one inhabitant (more than 100 thousand
35
rubles on the person at the average Russian level of 42 thousand rubles) also at the Yamal-Nenets
Autonomous Area, Chukotka Autonomous Okrug, Kamchatka Krai, the Sakhalin region, the Magadan
region, the Republic of Sakha (Yakutia).
One of the main problems of distinction of the level of development of regions can be noted on
the example of an education system of Russia. Large higher education institutions are located in the
economic centers while in less large cities education level is significantly lower. It is expected that the
most capable representatives of youth will make efforts for receipt in the central higher education
institutions of the country, but not in local educational institutions. However, quality education is
necessary for various regions as highly skilled workers positively influence the overall performance of
the enterprises.
3.5. Assessment of regression model on macro level
For our research, we have the following ranks of data (Table 7):
Table 7. Basic data
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
The size of the
saved-up human
capital (3%)
Investments
into fixed
capital
(billion
rubles)
Size of fixed
capital
(billion
rubles)
Europe
Brent Spot
price
(dollars per
barrel)
Volume of
money
supply M2
(billion
rubles)
GDP size
(billion
rubles)
37324,4
39549,6
42296,8
45228,1
48464,0
50414,9
52615,0
55320,2
58437,8
63488,8
66836,3
70519,9
80222,7
89901,4
100686,7
112009,5
124243,6
137236,5
149545,2
9772,0
7397,4
6650,3
5446,6
5174,2
4553,3
4794,7
5628,9
6287,5
6469,8
7291,5
8516,5
9385,2
11055,7
13687,0
14987,3
12964,0
13780,7
15269,0
107249,7
107142,5
107249,6
107142,4
106713,8
106393,7
106606,4
107139,5
108103,7
109184,8
110604,2
112373,8
114508,9
117257,2
120892,1
125244,2
129252,1
133129,6
138454,8
17,0
15,9
17,0
20,6
19,1
12,8
17,9
28,7
24,5
25,0
28,9
38,3
54,6
65,2
72,4
96,9
61,7
79,6
111,3
9,3
6,7
6,2
5,6
6,3
6438,2
5879,7
6878,1
8258,9
9456,5
12503,7
14120,9
16397,9
21174,2
26691,1
22815,3
26320,0
30212,5
31887,9
52429,7
45771,1
43894,5
42314,3
42906,7
40632,7
43233,2
47556,5
49981,8
52352,9
56172,5
60203,4
64042,1
69263,7
75175,4
79084,5
72915,9
76199,9
79449,1
36
2012 162710,7
16307,3
143993,0
111,6
32958,9
82235,3
2013 176348,9
16437,8
150184,7
108,6
36048,9
83287,1
2014 188746,5
16191,2
155741,5
99,0
34577,0
83908,9
2015 201505,6
14555,9
160725,3
52,3
35809,2
80804,3
The source: Constructed by the author on the base of the Table 4 and statistical data - Appendix to a
yearbook "Socio-economic indexes of the Russian Federation 1991- 2015 year" // System of national
accounts – URL: http://www.gks.ru/bgd/regl/b15_13_p/Main.htm (date of the access 10.04.2017).
U.S. Energy Information Administration (EIA) // Europe Brent Spot Price FOB - URL:
http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=RBRTE&f=M/ (date of the access
11.04.2017).
Central
bank
of
Russia//
Monetary
and
credit
statistics-URL:
http://www.cbr.ru/statistics/?PrtID=ms&Year=2015 (date of the access 18.04.2017).
Further, we have substituted the obtained data in the regression equation (3.1) in which
dependent variable is GDP increasing, and regressors are growth rates of other factors presented in the
table. We checked regression for the significance and on t-statistics estimated the significance of
factors of the used model. For calculations, the growth rate of the human capital with different
depreciation rates has been used, but as results were similar, we will present in this chapter results for
the model where the human capital is counted with depreciation rate 3%. Results were the following
(Table 8):
Table 8. Regression estimates for human capital and statistics
Variable
Coefficient
Standard error
t-statistics
Significance
1 Constant
-0,0225
0,0029
-7,7544
[0.0162]
2 HK [-17]
0,4852
0,0471
10,2946
[0.0093]
3 I
0,3382
0,0076
44,2931
[0.0005]
Statistics
Value
Significance
F(2,2) - statistics
1890,564
[0.0000]
DW statistics
3.3776
du < DW < 4-du
R-squared
99.9%
The source: Constructed by the author on the base of the Table 7
Also during the research, one more result has been received (Table 9):
37
Table 9. Regression estimates for human capital and statistics
Variable
Coefficient
Standard error
t-statistics
Significance
1 Constant
-0,2349
0,0631
-3,7196
[0.0205]
2 HK [-15]
2,6815
0,857
3,1290
[0.0352]
3 I [-7]
0,6249
0,1641
3,8075
[0.0190]
Statistics
Value
Significance
F(2,4) - statistics
8,5616
[0.0359]
DW statistics
2,6122
du < DW < 4-du
R-squared
81.06%
The source: Constructed by the author on the base of the Table 7
Here HK – increasing the saved-up human capital size, I– increasing of investments size into
fixed capital. In the course of carrying out a research, it has been found out that in regression without
logs the most significant factor is the increasing of investments size into fixed capital. Interrelation
with GDP gain very strong (correlation with GDP at the level of 95.2%). It explains the choice of this
variable for the regression analysis together with a factor the human capital.
We have considered a factor of increasing of the saved-up human capital size on GDP increasing
with delay because the main contribution to the size of the human capital is carried out due to
education. In addition, receiving the only secondary education will require 11 years, without speaking
about the higher education which receiving requires 16 years. By our calculations in the first case, it
has turned out that the human capital is a significant regressor when the lag makes 17 years. The quite
big lag is explained by long process of return of investments. As well in the second case, the size of the
human capital and size of investments undertake with lags of 15 and 7 years respectively. The
empirical check has also shown that with increase or reduction of a lag for the human capital the
importance of factors and regression in general decrease, as confirms fidelity of the assumption of
period duration after which investments into the human capital will begin to yield results.
This result cannot be considered positive because with the size of this lag the number of
observations is too small – 5 and 7 years respectively. However when carrying out the correlation
analysis it has been noted that influence of the human capital on GDP is essential (human capital with
depreciation rate of 2,5% correlates at the level of 21,27%, human capital -3% at the level of 21,9%,
and human capital -3.5% at the level of 22,7%). Therefore, it is possible to conclude that the human
capital makes the impact on economic growth in Russia (Appendix 3).
38
CONCLUSIONS
Thus, following the results of work it is possible to draw the following conclusions:
1. The role of the human capital and its influence on economic growth are an object of research
during several centuries. The human capital appears in many surveys in which its essential importance
as a factor of economic development is emphasized. The concept of the human capital is rather wide
and includes education level, health, skills, and the saved-up professional experience. The most
important element of the human capital, which it becomes the frequent object of the analysis, is
education level. In economic literature, various approaches to an assessment of the human capital are
discussed. A number of researchers estimate this size proceeding from the period duration of the
person appearing in the educational system. Another approach is the assessment of the human capital
proceeding from the general expenses for education, health care, science and other factors, which find
the reflection in the formation of the human capital. We carried-out the review of approaches to
determination of the human capital value, and also models of economic growth with inclusion in it the
size of the saved-up human capital.
2. The methodic of determining saved-up human capital was developed by using an expensive
approach. For the assessment of the saved-up human capital, we used perpetual inventory method
applied to the calculation of fixed capital cost. In this approach, not only education investments but
also investments into other spheres were considered, which influence on the quality of the formed
human capital. This linear model includes investments into health care, education, culture, sport and
social policy. According to calculations, the size of the human capital for the period from 1993 until
2015 has increased about 5.4 times.
3. A share of expenses of the government on such important factor for accumulation of the
human capital as education during the following period is reduced every year. However, the
government expenditures have increased by education for the considered period by 1.4 times, and the
volume of private investments (service of paid education) by 12.9 times.
4. We also measured the saved-up human capital for all regions in Russia in the period from
2003 until the 2015 year by also using the perpetual inventory method. For calculations, we used
investments into health care, education, culture, and sport. The positive dynamics of human capital
size change of all Russian Federation subjects is traced. After carrying out calculations of growth rates,
it has been revealed that the largest growth is traced in the North Caucasian Federal District where the
human capital size for the considered period has increased by 3.2 times. This fact is explained by a big
contribution of the Chechen Republic where the increase by 10.4 times is traced. The most cardinal
increase can be seen in the St. Petersburg city – 11.8 times. The smallest gain is observed at the
Siberian, Far Eastern, and Crimean Federal Districts.
39
5. For this period, the city of Moscow became the leader in a contribution to education,
additionally in top five the Moscow region, the St. Petersburg city, Khanty-Mansi Autonomous Okrug
and Sverdlovsk region. In a research of such factor as health care, physical culture and sport and
culture remains the same situation with the only replacement of the fifth place by Krasnodar Krai.
Among the last such regions as the Altai Republic, the Jewish Autonomous Oblast, the Republic of
Kalmykia and the Republic of Adygea.
6. Development of the human capital directly influences the development of the economy of
Russia. At the same time process of investment into the human capital including such sections as a
financing of social policy, education, healthcare and the sport remain very important. Based on the
carried-out analysis on regions of Russia, it is possible to notice the decrease in these expenses in 31
regions that has an adverse effect on the social and economic development of regions.
4. The offered and estimated model of regression was significant on F-statistics and R2, the
human capital does not give immediate impact on GDP gain, and begins to make impact with a lag in
seventeen years in the first case and with lag of 15 years with the assistance of fixed capital
investments lag 7 years in the second case. The quite big lag is explained by long process of return of
investments. However, this result cannot be considered positive because taking into account the size
of this lag the number of observations is too small – 5 and 7 years respectively.
5. However when carrying out the correlation analysis it has been noted that influence of the
human capital on GDP is essential (human capital with depreciation rate of 2,5% correlates at the level
of 21,27%, human capital -3% at the level of 21,9%, and human capital -3.5% at the level of 22,7%).
Therefore, it is possible to conclude that the human capital makes the impact on economic growth in
Russia.
40
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