Volume 04 Issue 08-2024
52
International Journal Of Management And Economics Fundamental
(ISSN
–
2771-2257)
VOLUME
04
ISSUE
08
P
AGES
:
52-70
OCLC
–
1121105677
Publisher:
Oscar Publishing Services
Servi
ABSTRACT
The development of the higher education system in the Republic of Uzbekistan, as well as the growth of higher
education services in the volume of gross services and gross domestic product, its dynamics are analyzed and
forecasts are developed on its basic, inertial and mobilization perspectives.
KEYWORDS
Higher educational institutions, educational services, educational services market, competition, gross domestic
product, gross services, forecasting, exponential smoothing method, regression equation.
INTRODUCTION
The economy of the 21st century has been
characterized by several trends along with potential
changes and developments that are shaping the way
we live and work. This is not only due to the modern
technological revolution and the genesis of new
technological structures, but also to the qualitative
changes affecting the person himself (needs, motives,
goals, etc.) and the content with his work. The
development of knowledge on intensive production
led to the acceleration of the transition from
Research Article
DYNAMICS AND PROSPECTS OF DEVELOPMENT IN THE FIELD OF
HIGHER EDUCATION SERVICES
Submission Date:
August 20, 2024,
Accepted Date:
August 25, 2024,
Published Date:
August 30, 2024
Crossref doi:
https://doi.org/10.37547/ijmef/Volume04Issue08-05
Mamatov Akhmetjon Atajanovich
Doctor Of Economic Sciences, Tashkent State University Of Economics, Uzbekistan
Mamatov Mamajan Ahmadjonovich
Phd Associate Professor Tashkent State University Of Economics, Uzbekistan
Mamatova Dilnoza Bekpulatovna
Phd Associate Professor Tashkent State World Language University, Uzbekistan
Journal
Website:
https://theusajournals.
com/index.php/ijmef
Copyright:
Original
content from this work
may be used under the
terms of the creative
commons
attributes
4.0 licence.
Volume 04 Issue 08-2024
53
International Journal Of Management And Economics Fundamental
(ISSN
–
2771-2257)
VOLUME
04
ISSUE
08
P
AGES
:
52-70
OCLC
–
1121105677
Publisher:
Oscar Publishing Services
Servi
reproductive industrial labor, which dominated the
previous centuries, to mainly creative labor. These
transformation processes gave rise to a change in the
place and role of education in the economy. Education
has long become a sphere of social production, in
which the main resource and potential for human
creativity development have been formed.
The basis of the decree of the President of the Republic
of Uzbekistan dated October 8, 2019 "On approval of
the concept of the development of the higher
education system of the Republic of Uzbekistan until
2030" - number PF 5847 [1], the concept of the
development of the higher education system of the
Republic of Uzbekistan until 2030 was adopted. The
concept is aimed at improving the quality of education,
training competitive personnel, and effective
organization of scientific and innovative activities
based on the needs of the social sphere and economic
sectors, ensuring the solid integration of science,
education and production.
This is the aspect which President of the Republic
Uzbekistan Sh.M. Mirziyoev specifically mentioned
with the following points: 65 academic lyceums will be
transferred to higher education institutions in order to
strengthen the cohesion between universities and
lower levels of the educational system. Also, 187
technical schools will be attached to related
universities and network enterprises in their field [2]. A
distinctive feature of this strategy is the development
of public-private partnership in the field of higher
education, the establishment of branches of state and
non-state HEIs in the regions, including the branches of
prestigious foreign HEIs.
The educational service budget is the demand for
educational services of the main economic entity
(individual, household, household and organization,
state) and the provision of this service by the general
educational organization is considered as a basic
requirement, and these higher education services
contribute to the national economy and its
determining and assessing the impact on the gross
services sector is of urgent importance.
REVIEW OF LITERATURE
The scientific-theoretical basis of increasing the
volume and quality of higher education services,
training competitive personnel, effective organization
of scientific and innovative activities on the basis of
ensuring a solid integration of education and
production,
foreign
scientists
B.A.Lundvall,
J.K.Galbraith, R.Nelson, G.B. Klyder, D. Mandel, K.
Freeman and other scientific research works can be
cited.
Among the Russian scientists are A. A. Porokhovsky,
Yu. P. Anisimov, S. Yu. Glazev, O. G. Golichenko, A. A.
Dinkin, Beketovn. V., Yu. V. Erigin, B. N. Kuzik, N. I.
Ivanov, V. M. Polterovich, I. V. Shevchenko, Yu. V.
Yakoves and others have conducted research on this
topic.
Scientific-theoretical aspects of improving the volume
and quality of higher education services, training
Volume 04 Issue 08-2024
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International Journal Of Management And Economics Fundamental
(ISSN
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2771-2257)
VOLUME
04
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08
P
AGES
:
52-70
OCLC
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1121105677
Publisher:
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competitive personnel, effective organization of
scientific and innovative activities on the basis of
ensuring a solid integration of education and
production in the Republic of Uzbekistan. Toychieva
O.M., Usmonov B.Sh., Shukurullaev U.U., Azizov S.R.,
Khudaynazarova D.Kh., Khojaev A.S., Djumaniyazov
U.I., Nabiev D.A., Vakhobov A.V. and others can be
distinguished in this field.
The concept of "network structure" in the higher
education system was coined by B.A. Lundvall[3]. The
interconnectedness of this concept determines the
diversity of approaches to defining the nature of the
network structure. A networked structure is governed
by long-term single goals related to certain integration
relations for the most efficient use of its resource
potential. Network structures differ from traditional
structures in almost all the basic principles of
operation. The most important features that
distinguish network structures from hierarchical and
market structures in the higher education system and
the first classification of the network structure,
considered classical, were proposed by P. Miles and Ch.
Snow [4].
According to Russian scientists S.L. Parfenov,
considering higher education institutions, the
structure of the educational network, formed by a set
of organizations that implement educational projects
together, is also aimed at building mutual cooperation
with large scientific centers and the real sector of the
economy. Such a network structure revealed that the
main form of interaction is a consortium of business
communities and a cluster of higher education
institutions, academic institutions and associations [5].
As reported by Professor Makoveev V.V. in higher
education institutions, "integrative network structures
are of special importance for establishing integrative
relations among science, education and production,
and the activities of its participants: fundamental
research
–
REDW (research and experimental design
work) - experimental production - mass production -
sales" scientifically justified that it is aimed at covering
the innovation cycle" [6].
Zufarova N.G., an economist from Uzbekistan. In
higher education institutions, "universities are at the
central link of mutual cooperation, and they are the
main stems of innovations[7]. Among the young
economists in our country, A.Sultanov, U.Djumaniozov
and K.Khalmuratov paid special attention to public-
private partnership as a form of branch structures in
higher education institutions, and in their scientific
work, bearing in mind public-private partnership based
on the long-term strategic tasks and goals of the state,
public-private partnership is a long-term strategic task
of the state, and based on their goals, on the basis of
various possible economic, political, social, cultural and
considering other risks, dangers, risk distribution, with
the private sector, extremely important socio-
economic for the population, if necessary, projects and
relations with the private sector are mutually beneficial
Volume 04 Issue 08-2024
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International Journal Of Management And Economics Fundamental
(ISSN
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2771-2257)
VOLUME
04
ISSUE
08
P
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:
52-70
OCLC
–
1121105677
Publisher:
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to build politically important objects, introduce
innovations in the fields, and provide services" [8].
RESEARCH METHODOLOGY
The article includes dialectical, systematic, integral and
synergetic approaches, economic, logical, scientific
abstraction, analysis and synthesis, modeling of
economic processes and systems, induction and
deduction, comparison, generalization, grouping,
graphical
econometric
modeling,
exponential
smoothing method, regression equation methods
were used.
ANALYSIS AND DISCUSSION OF RESULTS
The higher education system is an important pillar that
increases the country's national wealth and
competitiveness. In accord with experience of
developed societies, in order to ensure sustainable
economic growth, 40-50 percent of the population
should possess at least higher education, and in the
knowledge economy, the percentage of highly
educated people reaches 60 percent. In this regard,
the President emphasized the following: improving the
quality of education is the only correct way of
development of the new Uzbekistan [9]. Particularly, in
the concept of development of the higher education
system of the Republic of Uzbekistan until 2030, raising
the process of training independent-thinking, highly
qualified personnel with modern knowledge and high
moral and ethical qualities to a new level in terms of
quality, modernization of higher education the task of
developing the social sphere and economic sectors
based on advanced educational technologies.
The development of stable market relations in our
country is inextricably linked with the emergence and
development of the educational services market.
Formation of the educational services market is a
complex process. Understanding education as a
service and its entry into the market includes financial
relations between the subjects of the market of
educational services. Education will become a separate
service sector of the market, and the tax-paying citizen
will receive the right of a customer, demanding the
improvement of the quality of the services provided,
taking into account the needs of consumers and their
legal representatives.
As competitive factors in the market of educational
services, the standard of living, the structure of
employment, the rate of development of socially
important fields and practices, etc. can be cited.
Educational services are exchanged in the market as a
type of market service, which is understood as a set of
existing and potential buyers and sellers of goods. The
educational services market is the demand for
educational services of the main economic entities
(individuals,
households,
enterprises
and
organizations, the state) and their delivery by various
educational
organizations,
considered
as
an
interacting market.
In modern market conditions, the nature of the
relationship between the citizen and the state is
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(ISSN
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VOLUME
04
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08
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52-70
OCLC
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1121105677
Publisher:
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changing. Education becomes a service sector, and the
tax-paying citizen takes the right of the customer and
demands the improvement of the quality of the
services provided, taking into account the needs of
consumers and their legal representatives.
Currently, higher education institutions in the Republic,
which have been granted financial freedom, are
competing with each other in the rival for students,
because the choice of legal representatives can
provide educational conditions that meet the new
state educational standards and provide various
quality educational services, aimed at educational
organizations that can provide
The number of higher education institutions in the
republic was 154 in 2021, and by 2022 there will be a
total of 186, including 34 universities, 48 institutes, 3
academies, 27 branches, 1 conservatory, foreign 31
branches of the national higher education institution
and 42 non-state higher education institutions are
operating[10].
Picture 1. Dynamics of the number of higher education institutions in the Republic of Uzbekistan (2010-2021).
The number of republican higher education institutions
increased from 65 in 2010 to 154 by 2021, and the
number of students studying in them increased by
almost 3 times to 808,000. In 2012, the number of
higher education institutions in Tashkent decreased by
1.
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Picture 2. Dynamics of the number of higher education institutions in the regions of the Republic of
Uzbekistan
It can be seen that the increase in the number of higher
education institutions operating in the republic has
increased from year to year, which corresponds to the
general market trend, and the leader in the ranking of
the number of higher education institutions by region
is the city of Tashkent, in 2021 there are 51 higher
education institutions in it, which is 40.2% . In the
Samarkand region - 12 (9.4%), in the Fergana region - 10
(7.9%), in the Republic of Karakalpakstan - 9 (7.1%), and
in the Syrdarya and Navoi regions - 2 higher education
institutions. is 1.6% compared to the total number.
When looking at a number of important aspects in the
field of education, it has become the foundation for
human development and technological changes of the
economy, it provides the regions with labor force, on
the other hand, it helps to develop the
competitiveness of the subjects of the Republic.
Econometric models were used to analyze the position
of higher education services in the service sector.
Modeling and forecasting of socio-economic processes
in the conditions of the market economy is the
scientific knowledge of the past, the future based on
the development laws and trends of the present time,
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and the determination of future development goals
and objectives. Forecasting is of great importance in
the theory and practice of managing the country's
economy. This science serves as a basis for choosing
management
solutions,
determines
ways
of
influencing economic processes in the present to
achieve future goals.
"Forecasting" has been chosen as another stage of the
process of regulating the economy or part of the
development of the economic and social development
program of the country. At the same time, it is a
relatively independent science, distinguished by
several characteristics: firstly, forecasts are not
directive in nature, their quantitative estimates are
mainly probabilistic in nature, they are aimed at
identifying development problems that have occurred
on a large scale and looking for ways to solve them.
In our research, we used the exponential smoothing
method to determine the future share of higher
education services in the service sector and in the GDP
of the Republic. According to Allen L. Webster, the use
of moving average series, exponential smoothing, and
linear trend equations in time series smoothing shows
the necessity of using linear regression trend equations
in time series forecasting [11].
There are various methods of time series smoothing
and time based forecasting, the most commonly used
are:
1.
Method of extending the indicator period;
2.
Average sliding method;
3.
Exponential smoothing method;
4.
Trend equations.
The method of extending the period of the indicator is
carried out by calculating the weighted average within
recent years for long periods and forecasting that
average for the next period.
The exponential smoothing method is a method of
smoothing time series based on the quantities of
recent periods and the exponential parameter, and it is
more convenient for developing predictions for the
near future.
The formula for the exponential smoothing method is
as follows:
𝒚
𝒏+𝟏
= 𝒚
𝒏
∗ 𝜶 + (𝟏 − 𝜶) ∗ 𝒚
𝒏−𝟏
(1)
Where:
𝑦
𝑛+1
–
smoothed or projected period
information;
𝑦
𝑛
–
current period information;
𝑦
𝑛−1
–
basis (past) period observations.
𝛼
–
exponential leveling parameter.
Exponential leveling parameter the following
formula with is:
𝛼 =
2
𝑚+1
(2)
As can be seen, depending on the size of
𝛼
, the
severity of the previous observation decreases
rapidly. The larger
𝛼
is, the smaller the effect of
previous years. If
𝛼
is close to number one, only the
influence of the last observations can be taken into
account in this forecasting, and if it is close to zero,
the weight measured at the time series levels will be
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very slow. All previous periods and observations are
taken into account in forecasting.
At this point, it should be said that in some literature,
the data of the current and past periods are
presented directly in absolute amounts, while in some
literature, the current and past periods are
arithmetically represented instead of the current
data. The average amount, instead of the information
of the previous period, the arithmetic average of the
amounts of the previous and previous year is taken.
The average relative error (e) in the data
obtained as a result of exponential smoothing is
determined by the following formula:
ε =
1
𝑛
∗ ∑
|𝑌
𝑝𝑟
− 𝑌|
𝑌
𝑛
𝑖=1
∗ 100
(3)
In the interpretation of the values to evaluate the
forecast accuracy of the mean relative error, if
ε
is less
than 10, the forecast accuracy is high, in the range of
10-20, the accuracy is good, in the range of 20-50, the
accuracy is satisfactory, and when it is greater than 50
accuracy is considered unsatisfactory.
The trend method of forecasting is one of the
most widespread methods, which is a linear trend
equation in its simplest form, but in our research we
used a regression equation in the form of a second
order parabola. Because in the following years, due to
the increase in the number of higher education
institutions and the increase in the demand for higher
education services, there was a sharp increase in the
service sector (Fig. 1).
𝑌 = 𝑎 + 𝑏 ∙ 𝑡 + 𝑐 ∙ 𝑡
3
(4)
Here: Y - result;
a , b , c - regression equation parameter;
t - time series
The values of a, b and c are found by using the
least squares method to represent the system of
equations.
{
∑ 𝑦 = 𝑛 ∙ 𝑎 + 𝑏 ∙ ∑ 𝑡 + 𝑐 ∙ ∑ 𝑡
2
∑ 𝑦 ∙ 𝑡 = 𝑎 ∙ ∑ 𝑡 + 𝑏 ∙ ∑ 𝑡
2
+ 𝑐 ∙ ∑ 𝑡
3
∑ 𝑦 ∙ 𝑡
2
= 𝑎 ∙ ∑ 𝑡
2
+ 𝑏 ∙ ∑ 𝑡
3
+ 𝑐 ∙ ∑ 𝑡
4
(5)
The created equation (model) is evaluated
according to the following criteria:
a) Determination coefficient;
b) Fisher criterion;
c) Student standard;
g) Darbin-Watson criterion;
d) Approximation error.
Trend
of models
quality
determination
coefficient the following formula defined by :
𝐷 = 𝑅
2
=
𝐸𝑆𝑆
𝑇𝑆𝑆
(6)
The value of the coefficient of determination is
determined according to the Chedok scale, and
according to it, it is between 0 and 1, and the result
close to 0 means that the connection between the
events is weak, 0 means that there is no connection
at all, and 1 Close to .0 means that the association is
very strong.
This where:
𝐷 = 𝑅
2
-determination coefficient;
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𝐸𝑆𝑆
- value of random variation (
explained amount
of squares);
𝑇𝑆𝑆
- total variation value (
total sum of squares
).
The statistical significance of the model is
determined by Fisher's F-criterion (F):
𝐹 =
𝐸𝑆𝑆∗(𝑛−𝑚−1)
𝑅𝑆𝑆∗𝑚
(7)
This where: n- number of observations;
m - factor number of variables ;
RSS - trend variation value (
residual sum of squares
).
The statistical significance of the regression
coefficients is tested by Student's
𝑡
test.
𝑡
𝑎
=
|𝑎|
𝑆
𝑎
(8)
𝑆
𝑎
2
=
𝑆
𝜀
2
∑
(𝑡
𝜀
−𝑡)
2
𝑛
𝑖=1
(9)
The accuracy of the model is calculated using the
average relative error (A) of the approximation:
𝐴 =
1
𝑛
∗ ∑
|
𝜀
𝑖
𝑌
𝑖
|
𝑛
𝑖=1
∗ 100
(10)
There should be no autocorrelation between the
time series values, which is checked using the Darbin-
Watson criterion:
𝑑 =
∑
(𝜀
𝑖
−𝜀
𝑖−1
)
2
𝑛
𝑖=1
∑
𝜀
𝑖
2
𝑛
𝑖=1
(11)
The Darbin-Watson scale allows for a range of 0-4.
It oscillates around 2.0 if there is no autocorrelation
between the row values.
When the found value is checked by the table
value, it has autocorrelation
𝑑
𝑟𝑒𝑎𝑙
< 𝑑
𝑙𝑜𝑤
, if it has
autocorrelation,
𝑑
𝑟𝑒𝑎𝑙
> 𝑑
ℎ𝑖𝑔ℎ
if
there
is
no
autocorrelation,
𝑑
𝑙𝑜𝑤
< 𝑑
𝑟𝑒𝑎𝑙
< 𝑑
ℎ𝑖𝑔ℎ
then the check is
continued.
Based on the developed model, a forecast for the
coming years is prepared. In this case, the forecast
indicators are required to be located in the upper and
lower range of the forecast developed for the next
period.
𝑌
(𝑡
0
)
− 𝑡
𝑛𝑎𝑧
∙ 𝑆
𝑦𝑥
≤ 𝑓𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝑖𝑛𝑑𝑖𝑐𝑎𝑡𝑜𝑟 ≤
𝑌
(𝑡
0
)
+ 𝑡
𝑛𝑎𝑧
∙ 𝑆
𝑦𝑥
(12)
Here:
𝑌
(𝑡
0
)
−
current period information;
𝑡
𝑛𝑎𝑧
−
Theoretical value according to the Student
criterion;
𝑆
𝑦𝑥
= 𝑆
𝜀
2
(
1
𝑛
+
(𝑡
𝑛+1
+𝑡)
2
∑
(𝑡
𝑖
+𝑡)
2
𝑛
𝑖=1
)
(13)
Table 1
Changes in country's GDP, volume of services and gross educational services in 2010-2021
The year _
Vol. of country's
GDP, bln soums
Total services,
bln soums
Higher education
services, bln soums
2010
78936.6
31463.8
1412.9
2011
103232.6
40529.1
1682.1
2012
127590.2
50254.7
2070.0
2013
153311.3
62099.2
2459.7
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2014
186829.5
73600.9
2917.3
2015
221350.9
86674.5
3435.4
2016
255421.9
99665.5
4034.9
2017
317476.4
116901.5
6057.8
2018
424728.7
147587.2
8292.6
2019
529391.4
204874.5
10616.6
2020
602193.0
233048.7
12043.9
2021
734587.7
283550.0
16020.1
The change is 2021
compared to 2010
9.3
9 , 1
11.3
Between 2010 and 2021, the country's GDP increased by
9.3 times, total services by 8.3 times, and higher
education services by 11.3 times. Over the past 12 years,
total services have increased more than higher
education services, indicating that services in higher
education have increased more than other types of
services.
In our study, the number of observations is equal to the
studied period, i.e. 12, and the exponential smoothing
parameter is equal to
𝛼 =
2
12+1
= 0,15
.
We will calculate in two options to develop
forecast data for 2022-2026.
In the first option, the forecast amount is
calculated as follows:
𝑦
𝑛+1
= 𝑦
𝑛
∗ 0,15 + (1 − 0,15) ∗ 𝑦
𝑛−1
(14)
In the second option, the amount of the forecast
is calculated as follows:
𝑦
𝑛+1
=
𝑦
𝑛
+𝑦
𝑛−1
2
∗ 0,15 + (1 − 0,15) ∗
𝑦
𝑛−1
+𝑦
𝑛−2
2
(18)
In our study, a forecast for the next nine years was
made, (see table 2)
Table 2
Forecast of higher education services of the country based on exponential texting, billion soums
years
higher
education
services,
Forecast amount based on
absolute amount of current and past
periods, option 1
Forecast amount based on average
amount of current and past periods,
option 2
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billion soums,
Y
𝑌
𝑝𝑟
Average
relative error,
𝜀, %
𝑌
𝑝𝑟
Average
relative error,
𝜀, %
2010
1412.9
2011
1682.1
2012
2070
2013
2459.7
1740.3
29.2
1596.8
35.1
2014
2917.3
2128.5
27.0
1934.4
33.7
2015
3435.4
2528.3
26.4
2328.4
32.2
2016
4034.9
2995.0
25.8
2761.7
31.6
2017
6057.8
3525.3
41.8
3260.2
46.2
2018
8292.6
4338.3
47.7
3931.8
52.6
2019
10616.6
6393.0
39.8
5365.7
49.5
2020
12043.9
8641.2
28.3
7517.1
37.6
2021
16020.1
10830.7
32.4
9735.9
39.2
2022
12640.3
11735.5
2023
15513.1
14008.9
2024
13071.3
13727.0
2025
15146.9
13021.6
2026
13382.6
13793.9
2027
14882.2
13379.3
2028
13607,5 _
13434.5
2029
14691.0
13559.6
2030
13770.1
13420.4
Medium _ _
5920.3
8062, 5
33.2
7479.9
39.7
Due to the presence of "convex" amounts in the time
series in option 1, the amounts of the next period of the
forecasted time series are the same, and due to the
sliding time series in option 2, the amounts in the last
forecast time series are the same.
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International Journal Of Management And Economics Fundamental
(ISSN
–
2771-2257)
VOLUME
04
ISSUE
08
P
AGES
:
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OCLC
–
1121105677
Publisher:
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Servi
Based on the above information, we have the
following regression equations for forecasting
economic processes with stable inertial dynamics:
By volume of higher education services:
𝑌
𝑥
̂ = 308,35 ∙ 𝑡
2
− 3018,3 ∙ 𝑡 + 8184,7
Based on the developed regression equation, the
quality, content and accuracy of the model were
analyzed.
When the coefficients of determination are calculated
based on the formula (6),
𝑅
2
= 0,89
the value means
that the time dependence is very strong and the time
model is reasonable.
Using the formula (7), Fisher's F-criterion was
calculated based on the data in Table 1. According to
him,
𝐹 = 386.9
it was equal to A Fisher's F-test greater
than 4.75 indicates that the model is statistically
significant.
The average relative error of the approximation of the
model accuracy is found by the formula (10)
𝐴 =
1
12
∗
64.5 = 5.38
and is less than 10 percent, which indicates
high model accuracy.
When analyzed by Darbin-Watson criterion (d) by
formula (11), the number of observations is
𝑑
𝑟𝑒𝑎𝑙
=
1.41
equal to 12, the factor is 1, and taking into account
the Jalwal data, it
𝑑
𝑙𝑜𝑤
= 0.97
can
𝑑
ℎ𝑖𝑔ℎ
= 1.33
be said
that there is no autocorrelation in the time series value.
From the basic forecast indicators of higher education
services, we can see that the volume of employees in
higher education will increase by 106.9 percent in 2030
compared to 2021 (see Table 3).
Table 3
Dynamics of change of basic forecast indicators of higher education services
Y
ea
rs
GD
P, bil
lio
n
s
o
u
m
Absolute
increase (decrease)
in s /
The rate of
increase (decrease) is in
%
The rate of
additional growth
(decrease) is in %
Significance
of
100
баз
А
1%
additional
growth
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OCLC
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1121105677
Publisher:
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Servi
Bas
ic
m
etho
d
(
Y
1
- Y
0
)
The
chain is a
similar
method
( Y
i
-
Y
i -1
)
Basic
method
100
0
1
Y
Y
The
chain is a
similar
method
100
1
−
i
i
Y
Y
Basi
c method
P
b
-
100%
Th
e chain
is
a
similar
method
P
Z
-
100%
1
2
3
4
5
6
7
(5-100%)
8
(6-
100%)
100
2
2021
16020
-
-
-
-
-
-
-
2022
10663.
6
-
5356.4
-
5356.4
66.6
66.6
-33.4 -33.4
160.2
2023
11474.1
-
4545.9
810.5
71.6
107.6
-28.4
7.6
106,63
6
202
4
12283.8
-
3736.2
809.
7
76.7
107.1
-23.3
7.1
114,741
2025
13092.9
-
2927.1
809.1
81.7
106.6
-18.3
6.6
122,838
202
6
13901.4
-
2118.6
808.
5
86.8
106.2
-13.2
6.2
130,929
2027
14709.
4
-
1310.6
808
91.8
105.8
-8.2
5.8
139,014
202
8
15516.8
-
503.2
807.
4
96.9
105.5
-3.1
5.5
147,09
4
202
9
16323.8
303.
8
807
101.9
105.2
1.9
5.2
155,168
203
0
17130.3
1110.
3
806.
5
106.9
104.9
6.9
4.9
163,238
Volume 04 Issue 08-2024
65
International Journal Of Management And Economics Fundamental
(ISSN
–
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VOLUME
04
ISSUE
08
P
AGES
:
52-70
OCLC
–
1121105677
Publisher:
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Servi
In our study, when determining the forecast of the
volume of higher education services in the mobilization
option, the amount allocated for higher education
from the state budget, income from payment-
contracts, and the amount of funds appropriated at
the expense of republican grants and economic
contracts are taken into account. we analyzed the
effect of the effect on educational services in the form
of a rank function. In this case, the general regression
equation took the following form:
Values of regression equation parameters
1
𝐿𝑛𝑌
𝑌𝑇𝑋
= 5,92 + 0,41𝐿𝑛𝑋
𝑠𝑡𝑎𝑡𝑒 𝑓𝑢𝑛𝑑
+
0.52𝑋
𝑝𝑒𝑟𝑠.𝑓𝑢𝑛𝑑
+ 0.11𝑋
𝑠𝑐ℎ𝑜𝑙𝑎𝑟𝑠ℎ𝑖𝑝𝑠
It can be seen that, according to the data of the
regression equation, if other factors remain
unchanged, increasing the amount allocated from the
state budget by one percent will increase the volume
of gross higher education services by an average of
0.41 percent, coming from the payment-contract
account. an increase in the amount of income by one
percent increases the volume of gross higher
education services by 0.52 percent on average, and a
one percent increase in the amount of funds allocated
1
Gretl based on statistics author development in the program
to foreign grants and economic contracts at the
Republic level increases the volume of gross higher
education services leads to an average increase of 0.11
percent.
It can be seen that the amount allocated from the state
budget to the volume of gross higher education
services and the income from the payment contract
have a significant impact on the increase in the volume
of services in the field of gross education.
We determined the forecast values for the volume of
higher education services until 2030 according to the
developed model.
Volume 04 Issue 08-2024
66
International Journal Of Management And Economics Fundamental
(ISSN
–
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VOLUME
04
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AGES
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1121105677
Publisher:
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3 . GDP of the country, volume of total services and
volume of higher education services forecasted in
2022-2030
From the graph in Figure 2, it can be seen that the
growth of higher education services is faster than the
country's GDP. This, in turn, is explained by the fact
that the price and quality of higher education services
are in line with the wishes of consumers in the increase
in the demand for educational services.
In our study, basic, inertial and mobilization
forecasts of the volume of higher education services
until 2022-2030 were developed.
Table 4
Forecast indicators of higher education services, billion soums
Years
Basic
Inertia
Mobilization
2022
10663.6
13942.0
18776.1
2023i
11474.1
15176.1
24729.3
2024
12283.8
16410.2
27277.3
2025
13092.9
17644.3
34542.2
2026
13901.4
18878.4
44662.9
2027
14709.4
20112.5
53824.7
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AGES
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OCLC
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2028
15516.8
21346.6
65321.9
2029
16323.8
22580.7
72407.3
2030
17130.3
23814.8
82994.0
Figure 4. Forecast indicators of basic, inertial and mobilization options of the volume of higher education
services in 2022-2030
Table 5
The forecast value of higher education services is the share of the country's GDP and total services
Th
e yea
r _
The size
of
the
country's
GDP, billion
soums
Of this, the share of
higher education services ,
%
Total
services,
billion
soums
Of this, the share of
higher education services , %
Bas
ic
Iner
tia
M
o
bil
izatio
n
Bas
ic
Iner
tia
M
o
bil
izatio
n
2022
782335.9
1.4
1.8
2.4
304328.7
3.5
4.6
6.2
2023
883187.7
1.3
1.7
2.8
347092.8
3.3
4.4
7.1
2024
940594.9
1.3
1.7
2.9
377178.6
3.3
4.4
7.2
2025
1046733.6
1.3
1.7
3.3
427067.3
3.1
4.1
8.1
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2026
1175340.3
1.2
1.6
3.8
481889.5
2.9
3.9
9.3
2027
1251737.4
1.2
1.6
4.3
520722.8
2.8
3.9
10.3
2028
1333100.3
1.2
1.6
4.9
561235.2
2.8
3.8
11.6
2029
1419751.8
1.1
1.6
5.1
607653.8
2.7
3.7
11.9
2030
1482035.6
1.2
1.6
5.6
650613.6
2.6
3.7
12.8
By ensuring stable high growth rates in economic
sectors, in the next five years, the gross domestic
product per capita will be increased by -1.6 times (from
$1,750 to $2,800), and by 2030, the per capita income
will increase from 4,000 US dollars, and "countries with
higher than average income" "creating the ground for
entering the line is indicated in the Decree of the
President of the Republic of Uzbekistan dated January
28, 2022 No. PF-60 "On the Development Strategy of
New Uzbekistan for 2022-2026". As a result, it was
determined that the share of higher education services
in GDP will reach 5.6% and the share of total services in
GDP will reach 43.9% according to the optimal option,
that is, the mobilization forecast indicator .
CONCLUSIONS
The number of republican higher education institutions
was 65 in 2010, and by 2021 it has doubled to well
over154.
The increase in the number of higher education
institutions operating in the republic has increased
year by year, the leader in the ranking of the number of
higher education institutions is the city of Tashkent. In
2021, there are 51 higher education institutions in it,
which is 40.2% , in the Samarkand region - 12 (9.4%), in
the Fergana region - 10 (7.9%), in the Republic of
Karakalpakstan - 9 (7.1%), in the Syrdarya and Navoi
regions - 2 It is 1.6% of the total number of higher
education institutions.
Between 2010 and 2021, the country's GDP increased by
9.3 times, total services by 8.3 times, and higher
education services by 11.3 times. Over the past 12 years,
higher education services have grown more than other
types of services as part of total services.
According to the determined regression equation, if
other factors remain unchanged, an increase in the
amount allocated from the state budget by one
percent increases the volume of gross higher
education services by 0.41 percent on average, and the
volume of revenue from payment-contracts by one
percent. an increase in the volume of gross higher
education services by 0.52% on average and an increase
in the volume of funds allocated to foreign grants and
economic contracts at the Republic level by one
percent, the volume of gross higher education services
by 0.11% on average leads to a percentage increase.
Volume 04 Issue 08-2024
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International Journal Of Management And Economics Fundamental
(ISSN
–
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VOLUME
04
ISSUE
08
P
AGES
:
52-70
OCLC
–
1121105677
Publisher:
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Servi
The volume of higher education services in the republic
was analyzed using the exponential leveling method of
the absolute amount and the average amount of the
current and past periods, and the indicators of the
future period were forecasted using the regression
equation for forecasting economic processes with
stable inertial dynamics. The forecast value in the
inertial option showed that 2030 will increase by 148.7
percent compared to 2021. Based on the forecast
indicators of higher education services, the dynamics
of change will lead to a 106.9 percent increase in the
number of employees in higher education in 2030
compared to 2021. According to the forecast indicator
in the mobilization option, the volume of higher
education services will reach 518.1 percent in 2030
compared to 2021.
As a result, it was determined that the share of higher
education services in GDP will reach 5.6% and the share
of total services in GDP will reach 43.9% according to
the optimal option, that is, the mobilization forecast
indicator.
The fact that the growth of higher education services
is faster than the country's GDP is explained by the fact
that the price and quality of higher education services
are in line with the consumer's desires in increasing the
demand for educational services.
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Decree No. PF 5847 of the President of the
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2.
Address of the President of the Republic of
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“Halq so’zi”
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National Systems of Innovation: Towards a Theory
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AGES
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International Conference on Future Networks and
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