QUANTITATIVE ANALYSIS OF THE INTERACTION OF THE LABOUR MARKET AND THE HIGHER EDUCATION MARKET (ON THE EXAMPLE OF KAZAKHSTAN)

Abstract

The importance of the interaction of the labour market and the higher education market is beyond doubt. The analysis of scientific articles has shown that this type of interaction is considered by scientists depending on the direction of research. Only a few works are devoted to the quantitative analysis of the interaction of these domestic markets. The task is complicated by the fact that today there is no clear methodology for quantitative analysis of the interaction of subjects of different markets. The authors made an attempt to adapt the analysis methodology proposed by Russian scientists. The methodology used is based on an economic and statistical analysis of the interaction of the labour market and the higher education market, with the determination of the type of interaction under the influence of individual factor indicators of these markets and the use of systematic and structural group data. As a result of quantitative analysis, the lack of elasticity between the supply of universities and the needs of the labour market was revealed. The imbalance has led to the fact that in the sectors of the economy of Kazakhstan, there is a shortage in one industry and a surplus of personnel with higher education in another. The results of this study are important for stakeholders, such as politicians, universities, to solve the problems of unemployment among recent graduates.

Full text

137
Oxana Bezler1
Teodor Sedlarski2 Volume 31 (2), 2022
QUANTITATIVE ANALYSIS OF THE INTERACTION OF THE
LABOUR MARKET AND THE HIGHER EDUCATION MARKET
(ON THE EXAMPLE OF KAZAKHSTAN)3
The importance of the interaction of the labour market and the higher education market
is beyond doubt. The analysis of scientific articles has shown that this type of
interaction is considered by scientists depending on the direction of research. Only a
few works are devoted to the quantitative analysis of the interaction of these domestic
markets. The task is complicated by the fact that today there is no clear methodology
for quantitative analysis of the interaction of subjects of different markets. The authors
made an attempt to adapt the analysis methodology proposed by Russian scientists. The
methodology used is based on an economic and statistical analysis of the interaction of
the labour market and the higher education market, with the determination of the type
of interaction under the influence of individual factor indicators of these markets and
the use of systematic and structural group data. As a result of quantitative analysis, the
lack of elasticity between the supply of universities and the needs of the labour market
was revealed. The imbalance has led to the fact that in the sectors of the economy of
Kazakhstan, there is a shortage in one industry and a surplus of personnel with higher
education in another. The results of this study are important for stakeholders, such as
politicians, universities, to solve the problems of unemployment among recent
graduates.
Keywords: labour market; demand of labour market, higher education market;
proposals from university graduates; interaction; types of interaction of different
markets
JEL: A10; I2; J6
Introduction
The labour market and the higher education market are characterized by internal factors and
socio-economic indicators. The employment of the population is one of the key indicators of
the development of the socio-economic policy of the state. The mandatory employment rate
of university graduates in the first year of its completion in Kazakhstan should be 80%. An
important role in the growth of employment and recruitment is played by the quantitative
1 Oxana Bezler, Karaganda University of Kazpotrebsoyuz, e-mail: bezleroxana@mail.ru.
2 Teodor Sedlarski, Sofia University “St. Kliment Ohridski”, e-mail: sedlarski@feb.uni-sofia.bg.
3 This paper should be cited as: Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction
of the Labor Market and the Higher Education Market (on the Example of Kazakhstan). – Economic
Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
138
interaction of the subjects of the labour market and the subjects of the higher education
market. A university graduate is a participant in this interaction. Entering the university, a
student decides to master certain competencies, at best, in accordance with their inclinations,
ideas about the expected level of wages, income and demand in the labour market. The
university strives to sell educational services of already open educational programs to as
many potential applicants as possible. The more students enter the university, the higher the
level of financial condition of the university. The state order for training specialists for most
universities is minimal. The largest share of students in Kazakhstan receives higher education
on a fee-based basis. According to official data4 for the 2020-2021 academic year, the number
of students studying at universities amounted to 576.6 thousand students. And only 29.8%
(171.8 thousand students) study at the expense of state educational grants. The state does not
regulate the quantitative influx of specialists of the highest category. In Kazakhstan, neither
the university nor the state studies the quantitative sectoral needs of the labour market. The
analysis of personnel needs is carried out only according to the documents of statistical
reporting. This situation leads to a violation of the balance between the quantitative demand
of the labour market for young professionals with higher education and the quantitative
supply of the higher education market. In this case, it is not necessary to talk about the
equilibrium price. The economic opportunities of the employer and the desires of the
university graduate do not coincide. If the labour market is not able to offer enough jobs that
graduates expect, then many graduates will receive limited profits from their education
(Lauder, Mayhew, 2020).
The work on making projections, in developed countries, enjoys state support; however, not
everywhere state institutions are producers of forecast works. Only in the USA and Canada,
government agencies are responsible for this direction. In European countries, professional
structure projection is carried out by non-profit organizations, for example, the English
Institute for Employment Research at Warwick University or the German Institute for
Employment and Occupational Research at the Federal Institute of Labour in Nuremberg.
Many researchers explain the non-participation of the state in forecasting activities by the
fact that the authorities are afraid to take responsibility for the quality of forecast estimates.
In addition to forecasts that are developed by specialists of individual countries, there are
forecasts for groups of countries of the European Union. This work is performed by
CEDEFOP (Vishnevskaya, Zudina, 2017).
This imbalance, in our opinion, arises as a result of the lack of a clear organizational and
economic mechanism between the interaction of the labour market and the higher education
market. And also, as a result of the lack of a methodology for analyzing this interaction, the
results of which can be considered in the system of planning, forecasting and state regulation.
4 Official website of the Bureau of National Statistics Agencies for Strategic Planning and Reforms of
the Republic of Kazakhstan - https://stat.gov.kz/for_users/dynamic.

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
139
Literature Review
In the international practice, a sufficient number of modern scientific works is devoted to the
interaction of the higher educational market and the labour market. The absence of effective
modern interaction is recognized by all authors without any exception. The authors reveal
and investigate this problem from their own scientific point of view.
Kostina and Orlova (2016) conducted an empirical study of the interaction of the labour
market and educational services. The authors came to the conclusion that the optimal
employment structure can be achieved as a result of the employers’ participation in the
development of requirements for future graduates and the development of educational
material.
With the objective interaction of the labour market and educational services, according to
Borisenko (2017), a labour market emerges. The labour market provides a qualitative
assessment of the professional competencies of its participants. The quantitative regulation
is imposed on the state. Only with such a model of interaction, in his opinion, it is possible
to maintain a balance of labour resources.
In the works of Perevozchikova and Vasilenko (2018), the conceptual foundations of the
labour market and the higher education market services at the current stage of their interaction
are defined.
Digital technologies are intensively included in all spheres of human economic activity. Their
influence transforms employment, increases the mobility and innovation of the labour force.
In general, this causes a change in the employer’s requirements not only for the digital
competencies of university graduates but also for their quantity.
In the scientific discussion, there are works devoted to the changes in the content of the labour
market, its organization, and the skills of personnel under the influence of computer
technology, such as Handel M. J. (2008), Green F. (2012), Seo H. J., Lee Y. S., Hur J.J., Kim
J.K. (2012), Frey C. B., Osborne M. A. (2013), Azmuk N. (2015). A number of scientific
works is devoted to determining the influence of information technologies on the formation
of students’ competencies, which in general form a qualitative component (Youssef,
Dahmani, 2008; Sampath Kumar, Manjunath, 2013; Castillo-Merino, Serradell- Lopez,
2014). The state, society, and family also have a direct impact on the choice of a future
speciality (Barham et al., 2009; Rodriguez – Planas, Benus, 2010; Bacher et al. 2017;
Spencer-Oatey et al., 2017). The role of companies and organizations in the development of
competencies of their employees with the highlighting of successful strategies and views on
performance is of considerable importance in the issue under consideration (Eilström, Kock,
2008; Ronald, 2009; Lai, Teng, 2011; Velasco, 2014; Delaney et al., 2020).
In the research, the authors also focus on the significant role of competition factors in the
formation of professional competencies of graduates to meet the needs of the labour market
(Ma’dan Marfunizah, Muhamad Takiyuddin Ismail, 2020).
Competition in the higher education market does not lead to an increase in the quality of
educational services, but to an oversupply of specialists in certain areas and a shortage in
others. In order to maintain a balance, the markets should be provided with data on the

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
140
economic and personnel development of the country in the form of macroeconomic forecasts.
The data should be partially corrected by employers’ expectations in the short and long term.
The guarantee of employment after receiving higher education should be an important
competitive advantage of the university in the higher education market, the problems of
which we considered in previous studies. (Borbasova, Sedlarski, Bezler, 2019).
Having studied the scientific works of domestic and foreign scientists, we can conclude that
the interaction of the labour market and higher education is largely investigated through
qualitative assessments. Within the framework of this study, the authors tried to give a
quantitative analysis of the interaction of the labour market and the higher education market.
Analysis Methodology
The qualitative analysis of university graduates consists of studies of professional
competencies. A university graduate must meet the employer’s requirements for the
professional and qualification composition of staff. The elasticity of the qualitative
interaction of markets should be achieved due to the coincidence of the qualitative demand
of the labour market with the qualitative supply of the higher education market.
A quantitative analysis of the interaction consists in the balance of the demand for labour
resources with higher education (the number of vacancies) in a particular industry and the
supply of the higher education market of graduates for certain educational programs. The
elasticity of the interaction of quantitative and qualitative characteristics of the markets under
research will provide a high level of employment. At the same time, the planning and
forecasting system plays an important role in this process.
The process of interaction between the labour market and higher education market reflects
the possible balance between labour demand and supply. A market in which demand matches
supply reaches equilibrium, but this ideal model is not always supported. The divergence of
interests creates an imbalance that requires the participation of all actors in this interaction
process.
In this article, we will conduct a quantitative analysis of the interaction of the labour market
and the higher education market according to available data from Kazakhstan. For
quantitative analysis of interaction, the authors tried to adapt the methodology proposed by
Russian scientists Khamalinsky and Zavgorodnya (2010).
The purpose of the methodology used is to identify the type and trends of interaction between
the labour market and the higher education market at the current stage of socio-economic
development under the influence of various factors with the possibility of planning and
forecasting based on the results obtained.
Quantitative analysis of the interaction of labour market demand for personnel in certain
industries and the supply of university graduates in certain areas of training is carried out
using secondary data analysis. The data of the Ministry of National Economy of the Republic
of Kazakhstan Committee on Statistics and the data request of the National Chamber of

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
141
Entrepreneurs (NCE) of the Republic of Kazakhstan “Atameken”5(analyzes the employment
of graduates of universities of Kazakhstan according to official data of the State Pension
Payment Center and determines whether the graduate has mandatory pension contributions
from wages, which confirms the official employment of graduates) were used as sources.
The methodology of quantitative analysis of the interaction of the labour market and the
higher education market is implemented using a comprehensive analysis procedure (Table
1).
Table 1
Procedure for analyzing the interaction of the labour market and the higher education
market
Analysis and assessment Indicators
The dynamics of the labour market The number of economically active people employed,
unemployed, including by level of education, by
vocational-qualification structure, in industry and
regional contexts, allocation of the employable youth
level, youth unemployment, and labour replacement
rate.
Analysis of the educational services market The number of universities, the number of
universities’ graduates, the employment percentage of
graduates according their educational programs, the
ratio of budget and extra-budgetary financing of
universities.
Analysis of factors that determine the formation and
functioning of the labour market with the
identification of factors that have the greatest impact
on the interaction of the studied markets
The total population, graduates gender structure, the
number of job opportunities, the number of specialists
admitted with higher education during the graduation
year, the average annual salary, the cost of educational
services
Analysis of the quantitative correspondence of the
professional and qualification composition of the
labour force to the needs of the labour market (the
ratio of supply and demand in the labour market as a
whole and by groups of educational programs)
The coefficient of the interaction:
i
i
iD
S
С=.
Si– graduates supply with a certain of the educational
programs;
Di – demand for graduates of the same educational
programs.
Demand elasticity coefficient (supply) from i (factor).
Evaluating interactions based on type and trend
identification
Types of interaction with tendencies to increase or
decrease the coefficient of interaction:
T= C
 / C
Source: Khamalinsky, Zavgorodnaya, 2010.
In our opinion, the choice of a certain speciality for higher education depends on a number
of factors:
The supply of graduates of a particular speciality depends on a number of factors:
S= F(P,P
,N,
K
), (1)
5 https://atameken.kz.

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
142
P – educational service price;
PT – average salary;
N – average number of universities;
K – number of working-age population.
The demand for specialists in a particular educational program depends on factors:
D= F(P
,E,G), (2)
PT – average salary;
E – workplaces number;
G – number of state orders for specialists in the given educational program (number of
allocated grants).
The degree of influence of one or another factor on the resulting indicator can be estimated
using the elasticity coefficient. The coefficient of elasticity of demand (supply) from the i-
factor allows you to determine the percentage change in the effective feature (supply,
demand) with an increase in the factor feature by 1%:
E=
y
,(x /
y
) (3)
Ei – elasticity coefficient from the i factorial feature;
y’ – first derived function;
xi – i-factorial feature;
yx – aligned value of effective feature.
A multivariate model can be constructed using a linear function:
𝑦x1,x2…xn =𝑎+𝑏1 ∗𝑥
1+𝑏2 ∗𝑥
2+ …𝑏n ∗𝑥
n (4)
b1,b2…bn – regression coefficients are showing the intensity of factors influence on the
effective feature, that is, for how many units will be increased the accepted Y value, if the
variable X changes by one (Khamalinsky, Zavgorodnaya, 2010).
The interaction of the higher education market takes place with a different state of demand
for specialists and their supply. In the methodology used, the authors propose to determine 4
types of interaction depending on the ratio of specialists trained by the higher education
market and the need for specialists with higher education in the labour market (Table 2).

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
143
Table 2
Combined matrix of types and trends of interaction between the labour market and the
higher education market
Trends of market interaction Types of market interaction
I II III IV
The strengthening of interaction Ci=1, T
p
Ci>0 Ci<1,T
p
Ci>0 Ci>1, T
p
Ci≤0 Ci=1, T
p
Ci≥0
The weakening of the interaction Ci>1, TpCi≥0 Ci<1,TpCi≤0 Ci>1,TpCi>0 Ci=1, TpCi<0
Ci>1, T
p
Ci>0
Source: Khamalinsky, Zavgorodnaya, 2010.
To assess trends in the interaction of the studied markets, the indicator of the growth rate of
the interaction coefficient is used:
T= C
 / C , (5)
Т – growth rate of the coefficient of the interaction of market;
С – coefficient of the interaction of markets.
The I type is a weak level of market interaction, characterized by a low degree of job creation
and training to meet the requirements.
The II type – the analyzed interaction is weakened by universities. In this situation, the labour
market is able to move towards a new employment structure, under the influence of changed
institutional conditions. Changing demand in the labour market is the impetus for changes in
universities. The offer of universities hinders the development of the labour market, not
satisfying its quantitative needs.
The III type of interaction, shown by a low intensity of job creation and relocation. In this
case, the supply of labour for a particular educational program exceeds the demand for it.
The IV type is high interaction intensity (Khamalinsky, Zavgorodnaya, 2010).
Results
In the quantitative analysis, the factors influencing the supply and demand for graduates were
determined. The primary data of the state statistics bodies, the employment service and the
legal system of regulatory acts of the Republic of Kazakhstan “Adilet” and the data of NCE
“Atameken” were used to conduct a secondary analysis for 2011-2019 and forecasting on
2020-2024.
Initially, with the help of correlation analysis, the influence of various factors on the
graduates’ supply in all educational programs was determined. The following factors were
used:
S – graduates supply (persons);

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
144
P – educational services price (EUR);
PT – cost of studying at a Universities (EUR);
N – average number of Universities (units);
K – population over the age of 15 and above (thousand people).
The results show that the average monthly salary has the greatest impact on the supply of
graduates, where the relationship between this factor and the supply is opposite. This can be
explained by the fact that with an increase in wages, parents have more opportunities to
provide their children with the opportunity to study abroad. This has been a trend in recent
years. The average number of universities has the least impact on the supply of graduates.
Based on the available data, we will create a regression model of the dependence of the
graduates’ supply on these factors. The multiple regression equation in general looks like
this:
S= a+b
P+ b
P
+b
 N+ b

K
, (6)
We will evaluate the multiple regression equation parameters using the “Regression” tool.
As a result of data approximation, we’ve got a protocol for performing regression analysis
(Table 3).
Table 3
The regression analysis protocol (graduates supply)
Regression statistics
Multiple R 0,933955
R-square 0,872272
Standard R- square 0,616816
Standard error 12012,46
Observations 7
Variance analysis
df SS MS F
Regression 4 1970876023 4,93E+08 19,34566
Balance 2 288598304 1,44E+08
Total 6 2259474327
Coefficients Standard error t-statistic
a 500972,143 234274,905 2,138394
b1 -0,10953 0,25605646 -4,42777
b2 -1,31017 0,55907076 -5,34348
b3 -1680,38 1050,24062 -1,59999
b4 6,034636 9,2121187 5,655076
Source: compiled by authors
As a result, we have the following equation of multiple linear regression:
S = 500972,14 −0,11P −1,31P
−1680,38N + 6,03
K
(7)
The multiple correlation coefficient is equal to 93,0R =, which indicates a close
relationship of the resulting feature with four factorial features simultaneously. The

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
145
determination coefficient is equal to 87,0R2=, i.e. 87% of the dependent variable variation
is explained by the regression obtained. Check the statistical significance and reliability of
the obtained regression equation and its coefficients. The data of regression analysis
execution protocol provide that the observed value of the F-test is equal to 35,19=
obser
F.
The critical value of the F-test at the level 05,0=
α
and the degrees of freedom number
21,4 21 =−−=== mnkmk (where n – number of observations, m – factors
number) is equal to
()
25,192;4;05,0
.=
crit
F.
As .. critobser FF > ( 25,1919,35 >), then we can conclude concerning the statistical
significance and reliability of the obtained regression equation. The statistical significance of
the equation certain coefficients shall be determined using a t-student statistic. The observed
values of this statistic for the certain coefficients are respectively equal to:
.7,5,6,1,34,5,42,4,14,2 4321 ===== bbbba ttttt
The critical value of the student criteria at the significance level 05,0=
α
and the number of
degrees of freedom 21 =−−= mnk is equal to
()
3,42;05,0
.=
crit
t.
Comparing the observed values of t-statistics with critical ones, we can conclude about the
statistical significance and reliability of only coefficients that take into account such variables
as university tuition fees, the average monthly nominal salary and the population aged 15
years and older.
Let’s analyze statistically significant coefficients of the obtained regression equation: with
an increase in the cost of training by 10 euros, the graduates supply decreases by 110 people;
with an increase in the average monthly nominal salary of 10 euros, the graduates supply
decreases by 1,310 people; with an increase in the population aged 15 years and older by
1,000 people, the number of graduates increases by 6 people. Let’s determine the average
value of the elasticity coefficients:
.%468,0
156485
121147
04,6
,%005,1
156485
120005
31,1
,%281,0
156485
402018
11,0
4
2
1
=⋅=⋅=
−=⋅−=⋅=
−=⋅−=⋅=
S
K
bE
S
P
bE
S
P
bE
SK
T
SP
SP
T
Elasticity coefficients indicate the following: with an increase in the cost of studying by 1%
of the average level, the graduates supply decreases by 0.281% of its average level with the
unchanged values of the remaining factors; with an increase in the average monthly nominal
wage by 1% from the average level, the graduates supply decreases by 1.005% from its
average level with the unchanged values of the remaining factors; with population growth
aged 15 and older by 1% of the average level, the graduates supply increases by 0.468% of
its average level with the unchanged values of the remaining factors.

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
146
Thus, we can conclude the average monthly nominal wage has the greatest impact on
graduates’ supply, and this effect is the opposite, and the possible reasons for this were
indicated therein. Further, using the correlation analysis, the influence of various factors on
the graduates’ demand in all educational programs was determined.
The following indications were used:
D – graduates’ demand (persons);
PT – average monthly nominal wage (EUR);
E – workplaces number (units);
G – state order size for specialists (number of grants allocated, units).
The obtained results show the average monthly wage has the greatest impact on graduates’
demand. The least impact on graduates’ demand has a number of state orders. Based on the
available data, we will create a regression model of the graduates’ supply dependence from
these factors. The multiple regression equation in a general way is the following:
D= a+ b
P
+b
 E+ b
 G, (8)
As a result of data approximation, we’ve got a protocol for performing regression analysis
(Table 4).
Table 4
The regression analysis protocol (graduates’ demand)
Regression statistics
Multiple R 0,933955
R-square 0,872272
Standard R- square 0,616816
Standard error 12012,46
Observations 7
Variance analysis
df SS MS F
Regression 4 1970876023 4,93E+08 19,34566
Balance 2 288598304 1,44E+08
Total 6 2259474327
Coefficients Standard error t-statistic
a 500972,143 234274,905 2,138394
b1 -0,10953 0,25605646 -4,42777
b2 -1,31017 0,55907076 -5,34348
b3 -1680,38 1050,24062 -1,59999
b4 6,034636 9,2121187 5,655076
As a result, we have the following equation of multiple linear regression:
y
= −23683,91 + 0,43P
−0.04E + 1,45G, (9)

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
147
The multiple correlation coefficient is equal to 94,0R =, which indicates a close
relationship of the resulting feature with four factorial features simultaneously. The
determination coefficient is equal to 88,0R2=, i.e. 88% of the dependent variable variation
is explained by the regression obtained. Let us check the statistical significance and reliability
of the obtained regression equation and its coefficients. The data of regression analysis
execution protocol provide that the observed value of the F-test is equal to 61,9=
obser
F.
The critical value of the F-test at the level 05,0=
α
and the degrees of freedom number
31,3 21 =−−=== mnkmk (where n – number of observations, m – factors
number) is equal to
()
28,92;4;05,0
.=
crit
F.
As .. critobser FF >(28,99,61 >), then we can conclude concerning the statistical
significance and reliability of the obtained regression equation.
The statistical significance of the equation certain coefficients shall be determined using a t-
student statistic. The observed values of these statistics for the certain coefficients are
respectively equal to: .41,3,75,4,55,5,43,0 321 ==== bbba tttt
The critical value of the student criteria at the significance level 05,0=
α
and the number
of degrees of freedom 31 =−−= mnk is equal to
()
18,33;05,0
.=
crit
t.
Comparing the observed values of the t-statistic with a critical one, we can conclude the
statistical significance and reliability of only coefficients proceeding all variables, except for
an intercept term.
Let us analyze the statistically significant coefficients of the obtained regression equation:
with an increase in the average monthly nominal wage by 1000 EUR, the graduates demand
decreases by 430 people; with an increase in the number of workplaces by 100 units, the
graduates demand decreases by 4 persons, it can be explained by the fact that employers
prefer to hire specialists with work experience; with the increase in the size of state order for
specialists by 100 units, the graduates demand increases by 145 people, i.e. the state order
does not completely cover the need for specialists.
Let us define the grand mean of elasticity coefficients:
.%630,1
71,23923
26971
45,1
,%787,1
71,23923
1043091
04,0
,%146,2
71,23923
120005
43,0
3
2
1
=⋅=⋅=
−=⋅−=⋅=
=⋅=⋅=
D
G
bE
D
E
bE
D
P
bE
DG
DE
T
DT T
Elasticity coefficients indicate the following: with an increase in the average monthly
nominal wage by 1% of the average level, the graduates demand increases by 2.146% of its
average level with the unchanged values of the remaining factors; with an increase in the

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
148
number of workplaces by 1% from the average level, the graduates demand decreases by
1.787% from its average level with the unchanged values of the remaining factors; with an
increase in the size of state orders for specialists by 1% of the average level, the graduates’
demand increases by 1.630% of its average level with the unchanged values of the remaining
factors. Thus, we can conclude the graduates’ demand is most affected by the average
monthly nominal wage.
Further quantitative analysis of the interaction between the labour market demand for
specialists and the supply of university graduates was as follows:
1) all educational programs were combined into 8 enlarged groups of educational programs:
education; law; art; agriculture sciences; services; technical sciences and technologies;
social sciences, economics, and business; healthcare and social security (medicine) using
the Classifier for higher and postgraduate education educational programs of the Republic
of Kazakhstan. Such groups of educational programs as the natural sciences and
humanities, military affairs, and security were not included in this assessment since it is
not possible to define the exact type of professional activity for these groups of
educational programs;
2) building of similar regression dependence models of graduates supply and demand for
each group of educational programs;
3) defining of projected values of graduates supply and demand for 2020-2024, both in
general for all educational programs and for selected groups of educational programs;
4) defining the coefficient of the interaction of the higher education market and the labour
market. The coefficient was calculated both according to the available data from 2011 to
2019 and according to the projected values of 2020-2024 (the 2020 data was included in
the analysis as a forecast indicator, due to the lack of data during the study);
5) calculation of the coefficient of the interaction growth rate coefficient of the interaction.
Figure 1
Dynamics and forecast of the coefficient of interaction (according to the considered groups
of educational programs), 2011-2024, units
Source: Compiled by authors
9.6
14.9
8.5
6.3
4.7 4.6 4.3 3.6 3.1
2.7 2.4 2.1 1.8 1.6
0
2
4
6
8
10
12
14
16
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
149
Over the period being evaluated, the interaction coefficient has an annual positive trend from
14.9 in 2012 to 3.1 in 2019. While maintaining annual economic conditions, the interaction
coefficient may approach the best value of 1 (in 2024, it will be 1.6).
According to the group of educational programs “Education”, the worst value of the
interaction coefficient was observed in 2012, for this period, supply exceeded demand by
225.2 times, which is significantly higher than the same indicator for all educational
programs (14.9).
Since 2017, the coefficient has shown a positive trend, which indicates a decrease in the
imbalance between the supply and demand of graduates. The forecast values do not indicate
a decrease in this gap (Figure 2).
Figure 2
Dynamics and forecast of the coefficient of the interaction for the “Education” group of
educational programs, 2011-2024, units
Source: Compiled by authors
In general, the results obtained reflect the existing problems in the interaction of supply and
demand for graduates in the group of educational programs “Education”. There is a shortage
of teachers in the republic. At a time when the state annually increases the volume of the state
order for the training of pedagogical personnel at the expense of the republican budget.
Educational grants are being mastered, but work in a school or college among Kazakh youth
is not in demand.
For the group of the “Law” educational programs, the coefficient of the interaction has an
irregular change (С>1). The greatest oversaturation of the labour market by lawyers with
higher education was observed from 2011 to 2016. Over the same period, there is a significant
difference with the same indicator for all educational programs (9.6 and 14.9, respectively).
In 2017, the disparity between the supply and demand of law graduates is the smallest. The
forecast values for the next four years show that the interaction coefficient will be in the range
from 47.2 to 39.1 and is far from an optimistic value (Figure 3).
115.5
225.2
70.6
44.9 42.1 45.1 44.6 39.3 37.6 36.2 35.1 34.1 33.3 32.6
9.6 14.9 8.5 6.3 4.7 4.6 4.3 3.6 3.1 2.7 2.4 2.1 1.8 1.6
0
50
100
150
200
250
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Education All groups of educational programs

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
150
Figure 3
Dynamics and forecast of the coefficient of the interaction for the “Law” group of
educational programs, 2011-2024, units
Source: Compiled by authors
For the group of educational programs “Art”, the coefficient of interaction has the greatest
negative effect in 2012 by 169.7 times. In general, a moderate irregular change is observed
in the group of educational programs “Art” (Figure 4).
Figure 4
Dynamics and forecast of the coefficient of the interaction for the “Art” group of
educational programs, 2011-2024, units
Source: Compiled by authors
For the group of educational programs “Social Sciences, Economics and Business”, the worst
value of the interaction coefficient was observed in 2012, during this period, supply exceeded
demand by 209.5 times, which is significantly higher than the same indicator for all
educational programs (14.9) (Figure 5).
653.0
588.0
89.0 98.8 137.2 113.1
35.4 54.5 50.4 47.2 44.5 42.4 40.6 39.1
9.6 14.9 8.5 6.3 4.7 4.6 4.3 3.6 3.1 2.7 2.4 2.1 1.8 1.6
0
100
200
300
400
500
600
700
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Law All groups of educational programs
159.3 169.7
41.3 33.1
13.7 15.6 23.0 15.4 14.2 13.2 12.4 11.8 11.2 10.7
9.6 14.9 8.5 6.3 4.7 4.6 4.3 3.6 3.1 2.7 2.4 2.1 1.8 1.6
0
20
40
60
80
100
120
140
160
180
200
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Art All groups of educational programs

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
151
Figure 5
Dynamics and forecast of the integration coefficient for the “Social Sciences, Economics
and Business” group of educational programs, 2011-2024, units
Source: Compiled by authors
However, after reaching a peak in 2012, since 2013, the interaction coefficient follows a
downward trend, the imbalance between supply and demand in the studied markets decreases.
In 2019, the imbalance decreased by 17.6 times (11.9) compared to 2012 (209.5). In the
forecast by 2024, this tendency to reduce the imbalance between the supply and demand of
graduates will continue and will strive for an ideal value.
The coefficient of interaction for the group of educational programs “Technical Sciences and
Technologies” has the largest gap between the supply and demand of graduates in 2012 and
exceeded it by 67.6 times, i.e. almost 68 graduates applied for 1 vacant place in this group of
educational programs (Figure 6).
Figure 6
Dynamics and forecast of the integration coefficient for the “Technical Sciences and
Technologies” group of educational programs, 2011-2024, units
Source: Compiled by authors
79.9
209.5
51.227.2 27.1 20.5 12.2 14.0 11.9 10.2 8.8 7.7 6.7 5.8
9.6 14.9 8.5 6.3 4.7 4.6 4.3 3.6 3.1 2.7 2.4 2.1 1.8 1.6
0
50
100
150
200
250
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Social Sciences, Economics and Business
29.1
67.6
23.6 22.619.8 22.0
15.1 16.2 15.2 14.4 13.7 13.1 12.6 12.1
9.6 14.9
8.5 6.3 4.7 4.6 4.3 3.6 3.1 2.7 2.4 2.1 1.8 1.6
0
10
20
30
40
50
60
70
80
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Technical Sciences and Technologies

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
152
Further, we can see a wavy value of the coefficient of interaction for this group of educational
programs. The smallest imbalance was observed in 2017 (15.1), in our opinion, this was due
to the active phase of the implementation of state programs to support technical education.
However, if the current situation persists, the indicators will not be close to the optimal value.
Significant fluctuations in the coefficient of interaction are observed for the group of
educational programs “Agricultural Sciences”. During the study period, the smallest
disproportion in the supply and demand of graduates for this group of educational programs
was observed in 2011 (13.5), followed by intensive growth in 2012 and 2013 – 213.3 and
362.8, respectively. The largest oversupply in the agricultural sector was observed in 2019
by 1286.1 times. However, at the moment, the agricultural sector of Kazakhstan is
experiencing an acute “personnel shortage”, including personnel shortage with higher
education. This problem requires a systematic state approach and serious strategic decisions
of large agricultural holdings (Figure 7).
Figure 7
Dynamics and forecast of the integration coefficient for the “Agricultural Science” group of
educational programs, 2011-2024, units
Source: Compiled by authors
In the group of educational programs “Services”, the worst value of the coefficient of
interaction was observed in 2012, during this period, supply exceeded demand by 34.9 times,
which is significantly higher than the same indicator for all educational programs (14.9). In
the service sector, the best closeness of the relationship with the general values in the country
is observed (Figure 8).
Significant ups and downs are observed in the close relationship in the group of educational
programs “Health and social security” (“Medicine”) (Figure 9). In 2012, the World Health
Organization indicated that there is an acute shortage of medical personnel in the world. The
effective provision of the country with medical workers is determined by the ratio of the
number of medical workers to the population. Kazakhstan is urgently considering new
mechanisms for regulating the personnel issue in the field of medical services.
13.5
213.3
362.8
210.7
30.4
192.9 196.6
489.3
1,286.1
-162.1 -113.4 -89.0 -74.3 -64.5
9.6 14.9 8.5 6.3 4.7 4.6 4.3 3.6 3.1 2.7 2.4 2.1 1.8 1.6
-400
-200
0
200
400
600
800
1000
1200
1400
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Agricultural Science All groups of educational programs

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
153
Figure 8
Dynamics and forecast of the integration coefficient for the “Services” group of educational
programs, 2011-2024, units
Source: Compiled by authors
Figure 9
Dynamics and forecast of the integration coefficient for the “Medicine” group of
educational programs, 2011-2021, units
Source: Compiled by authors
12.1
34.9
8.6
5.1 3.2
5.8
3.8
3.6 3.4 3.2 3.1 3.0 2.8 2.7
9.6
14.9
8.5 6.3 4.7
4.6
4.3
3.6 3.1 2.7 2.4 2.1 1.8 1.6
0
5
10
15
20
25
30
35
40
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Services All groups of educational programs
6.1
18.6
8.1
2.7
6.4
5.3
4.3 4.4 4.2 4.1 4.0 4.0 3.9 3.8
9.6
14.9
8.5
6.3
4.7 4.6
4.3
3.6 3.1 2.7 2.4 2.1 1.8 1.6
0
2
4
6
8
10
12
14
16
18
20
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Medicine All groups of educational programs

Bezler, O., Sedlarski, T. (2022). Quantitative Analysis of the Interaction of the Labor Market and the
Higher Education Market (on the Example of Kazakhstan).
154
According to the research methodology used, it is now necessary to calculate and analyze the
growth rates of the interaction coefficient for groups of educational programs. The type of
dynamic and predictive interaction between the labour market and the higher education
market is determined (Table 5).
Table 5
Type and trends of quantitative interaction between the labour market and the higher
education market
Group of educational
programs
The current interaction The expected interaction
Сi0 Сi1 T
pCi
indicator
values
type of
interaction
Сi0 Сi1 T
pCi
indicator
values
type of
interaction
All groups of educational
programs 9.6 3.1 0.32
C i1>1
T
p
Ci>0 III 2.7 1.6 0.59
C i1>1
T
p
Ci>0 III
Education 115.5 37.6 0.33
C i1>1
T
p
Ci>0 III 36.2 32.6 0.9 Ci1>1
T
p
Ci>0 III
Law 653.0 50.4 0.08
C i1>1
T
p
Ci>0 III 47.2 39.1 0.83 Ci1>1
T
p
Ci>0 III
Art 159.3 14.2 0.09
C i1>1
T
p
Ci>0 III 13.2 10.7 0.81 Ci1>1
T
p
Ci>0 III
Social Sciences,
Economics and Business 79.9 11.9 0.15
C i1>1
T
p
Ci>0 III 10.2 5.8 0.57 C i1>1
T
p
Ci>0 III
Engineering Science and
Technology 29.1 15.2 0.52
C i1>1
T
p
Ci>0 III 14.4 12.1 0.84 C i1>1
T
p
Ci>0 III
Agricultural sciences 13.5 1286.1 95.2 C i1>1
T
p
Ci>0 III -162.1 -6.45 -226.6 C i1>1
T
p
Ci>0
II
Services 12.1 3.4 0.28
C i1>1
T
p
Ci>0 III 3.2 2.7 0.84
C i1>1
T
p
Ci>0 III
Medicine 6.1 4.2 0.69
C i1>1
T
p
Ci>0 III 4.1 3.8 0.93
C i1>1
T
p
Ci>0 III
Source: compiled by authors
The dynamics of the coefficient of interaction between the higher education market and the
labour market in combination with the third type of interaction shows a tendency to weaken
interaction. This weakening is associated with a reduction in jobs by type of economic
activity and an increase in the number of graduates.
Conclusions
Applying the methodology of quantitative analysis of interaction, the republican features of
the interaction of the higher education market and the labour market were identified, in the
context of groups of educational programs - “Education”, “Law”, “Art”, “Social Sciences,
Economics and Business”, “Engineering Science and Technology”, “Agricultural Sciences”,
“Services”, “Medicine”, which revealed that the interaction of the studied markets belongs

– Economic Studies (Ikonomicheski Izsledvania), 31 (2), pp. 137-156.
155
to the 3rd type. The labour market is weakened due to the low intensity of job creation and
relocation, while the supply of graduates exceeds its demand.
The Kazakhstan Government is taking certain steps to stimulate employment and education
among the population, and this cannot be denied. The labour market and the higher education
market are in the process of constant development, but as we can see, the measures taken are
insufficient. Perhaps the Kazakhstan Government should pay attention to the European
experience of organizing a professional structure forecasting, using the services of research
institutes, non-profit scientific organizations.
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