Assessment of the EU Countries’ Economic Security based on the

Composite Indicators

OLENA KHADZHYNOVA

Sustainable Innovations Laboratory,

Mykolas Romeris University,

Ateities g. 20, 08303, Vilnius

LITHUANIA

OLEKSIY MINTS

Faculty of Public Governance and Business,

Mykolas Romeris University,

Soborna St, 87, 21050, Vinnytsia

Abstract: - The authors propose an integral indicator of the economic security of a country, based on a study of

economic, social, political and environmental indicators of security of 28 European Union countries. The study

used panel regression methods, correlation analysis, nonlinear approximation, graphical methods. The research

results make it possible to explain up to 58% of the variations in the studied indicators. The calculated values of

the integral indicator of economic security correspond to empirical data. The indicator proposed by authors

comprehensively characterizes the current state of the country’s economic security in the economic, social,

political and environmental spheres. This indicator makes it possible to determine the level and disproportions

Received: May 21, 2021. Revised: January 12, 2022. Accepted: February 13, 2022. Published: February 23, 2022.

1 Introduction

achievement of such a level of production,

efficiency and quality of products that ensure the

competitiveness of the state, allowing it to

participate on an equal footing in the world trade

[1].

2. The stability and sustainability of the national

economy is determined by the degree of protection

of property in all its forms, the creation of reliable

conditions and guarantees for entrepreneurial

activity, and the containment of factors capable of

conditions for the sustainability and self-

preservation of the economy [3].

Taking into account the conflicting research results,

the lack of consensus among scientists regarding the

set of economic security factors and the degree of

their influence on the efficiency of the economy, the

choice of methods and tools for folding individual

indicators into an integral assessment - further

research is needed on this topic.

and qualitative indicators, the use of integral

indicators and indices. Approaches to assessing and

analyzing economic security differ from country to

country, making it difficult to compare countries,

because of this there is still no international index of

the economic security of countries. To assess

economic security, the calculation of composite

indicators of sustainable development of countries is

widely used. The methods for assessing economic

security that are used in international practice have a

basis for the assessment, namely a set of indicators

that take into account all the main threats to the

economic security of the country.

A large number of scientists use complex indices as

indicators of economic security rather than

individual indicators. One of the first scholars to use

a comprehensive assessment of economic security

was J. David Singer. He based his research on The

Composite Index of National Capability (CINC) [6].

It uses six different components to represent

security at the state level and use it in both

developed and developing countries [7].

Mourougane A. and Roma M. study the impact of

the Industrial Confidence Indicator (ICI) and the

Economic Sentiment Indicator (ESI) on GDP

growth in the European Union [8].

In turn, H. Poirson in his work uses the following

components of the indices as indicators of economic

security: political rights, civil liberties, racial, ethnic

and nationality tensions, rule of law, bureaucracy

commissioned by the Research and Documentation

Center (WODC) to study the relationship between

economic performance and national security, as well

as to characterize and assess economic performance

[10].

It should be noted that most of the listed above

studies were carried out quite a long time ago. At

the same time, economic relations are constantly

developing and are supplemented by new factors.

This necessitates updating the set of indicators of

clustering were used.

the state is the degree of compliance of the

economic policy pursued with the chosen strategy

for the development of the national economy, as

well as the level of trust in it both on the part of the

population and international organizations.

This criterion should be characterized by the

integral system of indicators of economic security,

which reflects certain particular aspects of this

problem. In this regard, it is proposed to single out

several groups of indicators of economic security.

statistics for countries), which will make it possible

to obtain both a generalized assessment of economic

security by components (economic, political, etc.),

and by individual indicators that reflect existing

security threats; and will allow comparing countries

in terms of the level of economic security and the

effectiveness of government actions in order to

support it to ensure the sustainable development of

countries. Economic security is considered by the

author in terms of ensuring sustainable development

generalizing study is inappropriate, since in

different countries they can differ significantly. For

example, Malta's GDP in 2019 was € 13.5 billion,

while Germany's GDP was € 3.449 billion. Even

using such an indicator as GDP per capita is not

entirely correct. In 2019, in the EU, it ranged from

6,840 euros (Bulgaria) to 83,640 euros

(Luxembourg). At the same time, the indicators of

relative GDP growth in comparison with the

previous period seem to be more preferable for use,

In addition, as studies show, macroeconomic

processes are rather slow and inertial. Therefore, the

results in the form of changes in GDP growth rates

may appear with some delay [11]. This is why it is

necessary to include in the dataset the output

variables taken with a lag in relation to the input

ones. As part of this study, authors additionally

analyzed the dependent variables taken with a 1-

year delay.

Choosing the right sub-indicator system is the key to

constructed system of indicators, which includes a

compiled indicator formed on the basis of sub-

indicators grouped by components. As described

earlier, the formation of a system of subindicators

for assessing the economic security of a country

should be carried out in accordance with the

principles of representativeness, reliability and

availability of information. In order to form a

system of indicators for assessing the level of

economic security of a country, authors analyzed the

security is given in Table 1.

To ensure the correctness of further statistical

calculations with the raw initial data, the following

actions were performed:

1. Bringing to a single scale.

2. Identification of distortions.

3. Normalization.

As a result of steps 1-3, all input data is reduced to

the range [0; 1], in which it is located according to

the principle "more = better".4.

4.Analysis of cross-correlation in data.

capability) and p2 (Business dynamism) have a

correlation of more than 0.8 with 8 other indicators,

as well as a correlation of 0.9287 with each other.

5. Data aggregation.

Since the input data have a large dimension (29

independent variables) for further research, it is

advisable to aggregate them to reduce the

dimension.

It should be noted that the use of compiled

indicators to study multidimensional phenomena

be based on: a clear theoretical understanding of the

phenomenon under study, a reasonable choice of the

group subindicators and testing them for

multicollinearity, indicator normalization, and

correct aggregation of subindicators [28-32]. The

most widely used aggregation method is additive

[23, 29].

In this study, to aggregate data the authors used

averaging values that have the same direction of

influence on the result, in the context of each group

influence of the panel data structure on the

dependent variables, as well as the nature of such

influence.

To assess the influence of the spatial data structure

on the dependent variables, we will use the between

estimate (Fig. 1). In this case, only one output

variable is evaluated, since the structure of the data

itself is the same for all models.

each country has a more significant impact on each

variable than the temporal fluctuations of these

indicators relative to the average.

Among the panel regression models, there are

models with random effects and fixed effects [33].

Random effects models are simpler, but only work

well if the data that is being analyzed is part of a

larger population.

Fixed-effect models allow to take into account

more complex to implement and use.

Fig. 2: Parameters of random effects panel

regression

Source: Authors` own calculations in STATA

Fig. 3: Parameters of fixed effects panel regression

Source: Authors` own calculations in STATA

Since in all the constructed models with fixed

effects Prob > F = 0.0000, the hypothesis is rejected,

Fig. 4: Haussman test to compare fixed vs random

effects panel regression

Source: Authors` own calculations in STATA

carried out on the basis of the p-level analysis,

which for the models for y1 and y2, respectively, is:

Prob>chi2 = 0.0004

Prob>chi2 = 0.0000

Since in both cases the p-level is <0.01, the null

hypothesis is rejected. Thus, a fixed effects model is

better suited to describe the data of interest.

3.3 Modeling

To build models with fixed effects, we introduce

dummy variables d1..d28, the coefficients of which

will correspond to compensated spatial effects.

Let's consider the process of aggregating variables

model

Source: Authors` own calculations in STATA

Similarly, we are calculating the tables of regression

determine the direction of the connections of input

and output variables, taking into account panel

As you can see from the Table 2, for some input

of the relationship in the current and next year.

Therefore, for further calculations, we will use only

of connection with the output parameters y1, y2,

Economic positive:

• Infrastructure (e2).

• Product market (e3).

• Financial system (e5).

Economic negative:

• Innovation capability (e7).

• Economic decline (e9).

• Economic quality (e12).

Social positive:

• Health (s6).

• Governance (p9).

Political negative:

• Security (p1).

• External intervention (p6).

• Human rights & rule of law (p8).

Environmental positive:

• Environmental performance (ec1).

Table 2. Connection of input and output variables,

taking into account panel effects

Based on the table 2 and indicators listed above, we

can recalculate the aggregation formulas taking into

account panel effects (1).

Calculation of panel regression models using input

variables formed according to formulas (1) made it

possible to significantly improve their ability to

explain dependencies in the data, expressed in terms

of the coefficients of determination, in comparison

indicators.

Based on the results obtained (Fig. 6), it is possible

to write down a general formula for calculating

GDP growth in the next year, which will look like:

GDP per capita in the next year will be as follows:

income level - GDPpC. The last column shows the

average actual growth in per capita income.

Based on the principle of operation of the panel

regression model with fixed effects, the coefficients

for dummy variables d1 ... d28 show how much it is

necessary to correct (increase or decrease) the result

of model calculations for each object under study.

For example, Bulgaria, Slovakia and Malta show

approximately the same average GDPpC growth

rates (3.22, 2.92 and 3.5, respectively). But at the

development than Slovakia and Malta.

coefficient shows the effectiveness of the country's

high growth rates of per capita income. Let's check

this hypothesis.

Let's plot the average GDPpC of the country and its

corresponding value of the adjustment factor (Fig.

7).

Fig. 7: Scatter plot of GDPpC level and country

adjustment factor

Source: Authors` own calculations

As we can see from Fig. 7, despite the presence of

several outliers, in general, there is a fairly strong

relationship between the adjustment factors and the

(which are located in Fig. 1 far from the main array

of points and can be considered as statistical

anomalies) was -0.849.

Such a high value actually makes it possible to

replace dummy variables and a set of coefficients

for them in formula (3) with a logarithmic function

(4), which is graphically shown in Fig. 8.

that is completely based on macroeconomic data

and indicators of economic development.

The logarithmic nature is typical for the description

of many economic patterns associated with the

acceleration of growth rate or vice versa (Hutzler et

al, 2021). Therefore, its application in the proposed

model does not contradict empirical evidence.

Since the logarithmic function is nonlinear, and the

panel regression models (2) and (3) are linear, it can

be concluded that the adjustment coefficients

Fig. 8: Approximation the dependence of country

adjustment factor on the GDPpC level by a

consider the resulting indicator based on model (3),

which is preferable, both in view of the higher value

of the coefficient of determination, and from an

economic point of view, since it provides the

calculation of economic security in the future.

Column 1 of Table 3 corresponds to the average

values of the levels of economic security calculated

by formula (5). As you can see, among the analyzed

countries, Finland, Denmark, and the Netherlands

have the highest level of economic security. And the

lowest is Bulgaria and Romania, which does not

contradict empirical data.

High values of adjustment factors are typical for

countries with low per capita incomes. Therefore, it

can be assumed that the higher the level of GDPpC,

the more difficult it is to maintain sufficiently high

rates of its growth. However, on the other hand, it

may turn out that some of the baseline indicators are

country's high level of economic development,

social, political and environmental spheres. This

indicator makes it possible to determine the level

and disproportions of the country's development and

can become the basis for the formation of directions

for ensuring its economic security.

Authors believe that there are no optimal values for

the components of the proposed indicator of

economic development that would be universal for

all countries. Each country should strive to increase

indicators that have a positive effect on economic

factors, as shown by the study, are key in ensuring

the economic security of the country.

The methodology of the article is based on statistical

research methods, since they can be most fully

documented in terms of assessing the reliability of

the results. Further research can be directed towards

identifying causal relationships between the level of

economic security and individual subindicators of

economic, social, political and environmental

development. These relationships can be

[2] Ziolo, M., Ben Ghoul, M. B., & Aydın, H. İ.

[3] Lekar' S. I. (2012), "Foreign experience