Rima Zitkiene
Mykolas Romeris University, Lithuania
E-mail: rizit3@mruni.eu
Jurij Matyskevic
DXC Technology, Lithuania, Lithuania
E-mail: mediajurijlt@gmail.com
Inna Kremer-Matyskevic
Mykolas Romeris University, Lithuania
E-mail: inna_kremer@hotmail.com
Nataliia Korzhenivska
State Agrarian and Engineering University in Podilya, Ukraine
E-mail: nkorzhenivska@gmail.com
Svitlana Zaika
Kharkiv Petro Vasylenko National Technical University
of Agriculture, Ukraine
E-mail: zaika.svitlana175@gmail.com
Submission: 8/2/2020
Revision: 8/9/2020
Accept: 8/26/2020
ABSTRACT
The article object is to is a relatively new research direction in economic theory - economic security at the macro-level. One of the aims of this article is to reveal the country’s economic security idea and to choose methods for this economic phenomenon evaluation as well as to suggest the method to evaluate the energy sector's impact on this economic phenomenon. Firstly, the authors review different approaches to economic security principles and do some assumptions related to the country's economic security concept. There is shortly described the energy sector. Since the scientific problem is how to evaluate the energy sector and the country's security and what impact the energy sector has on the country's economic security, the authors have selected methods to analyze the links between energy sector activities and economic security. Furthermore, there were presented the results of regression analyzes and concluded what energy sector indicators influence countries' economic security.
Keywords: Energy sector; Economic security; External threats; Internal threats; Management
1.
INTRODUCTION
The phenomenon of the country’s economic security is a relatively new research direction in economic theory, but at the same time, it is an unquestionably integral component of national security which paradigm, as well as a new approach to the perception of national economic security, was formed by economist Keynes in the 1930s. From his point of view, the main threats to the national economy are not competition for foreign goods but unemployment and economic depression (ZUZEVICIUTE et al., 2018). In Western countries, economic security is usually studied at the micro-level, mostly there is an examination of the financial stability of a household or individual. Less research is done at the macro level by analyzing economic security through national security threats identification. One of the aims of this article is to reveal the country’s economic security idea and to choose methods for this economic phenomenon evaluation.
2.
LITERATURE REVIEW
2.1.
Energy sector and economic security
in international context
In the economic globalization
conditions, revealing the essence of economic security and identifying its real
threats as well as providing reliable and effective problem-solving methods is
a pretty important task. Therefore, solving economic security problems becomes
a multifaceted task, which must include not only a security function but also a
comprehensive approach, taking into account the overall country's political and
financial capabilities.
Economic security structure has been
presented by TAMOSIUNIENE and MUNTEANU (2015) in their theoretical research.
According to the offered scheme economic security should be divided into two
approaches: individual and macroeconomic (see Figure 1).
Whereas the individual approach
describes the economic security as an individual subject stable income and
other sources that maintain the living standard in the present and the near
future, i.e.: permanent solvency, predictable cash flow, efficient use of human
capital.
The macroeconomic security approach
is related to a sophisticated history because of the period of this method
rising matches with the times of the two World Wars. Especially, the formation
of this attitude to economic security was supported by a Russian economic school,
which using critical meanings, attempted to quantify economic security, as well
as a model developed by Professor Lino Briguglio, that defined economic
security as the state's economic vulnerability and resistance level.
Figure 1: Economic
security structure
Source: Tamosiuniene, Munteanu
(2015)
Since the object of this research is
the country's economic security, let’s review some insights into the
macroeconomic approach.
Scientists from different countries
have already begun to analyze the principles of economic security, but this
area is still not fully formed on a theoretical basis likewise evaluation
methodology of this phenomenon does not have the general pattern.
In accordance with SIMANAVICIUS
et al. (2019) research, the European Union (EU)
has two standpoints related to the concept of economic security. The first point is connected to the EU
position in the global economic system. There are collected various information
on the economic objectives of the European Union, economic security concept
interpretation, that are presented on the EU official portal.
The European Union
highlights the importance of European integration into the globalization
process of a competitive economy. The second point is related to the largest
official organization dealing with security complex issues in Europe - the
Organization for Security and Co-operation in Europe (OSCE), which develops
measures to reduce military confrontation and increase security in Europe. The
OSCE security concept contains several components: political and military
dimension, economic dimension, and human rights issues.
How to newly describe
the economic security purpose, and to what scope are nowadays applied
quantitative evaluation methods correct has been researched by GIRIUNIENE et
al. (2019). They argue it is worth considering that the state’s
economic security cannot be separated from other factors of the state’s
security. They state, that there is no basis to assert that a state, that
territorial integrity and, meantime, security is facing actual external
threats, with which a state cannot cope efficiently, can be considered
economically secure because the conquerors can make use of the state’s economic
resources.
Economic
security understood as the elimination the internal threats by JOHNSTONE (2013), HIPP (2016), ANGULO-GUERRERO (2017). On the contrary, economic
security has been showed from the prism of external threats, suchlike
countries’ dependency on energy resources, poverty, unemployment, migration,
and corruption by POPESCU (2014) and FRANKI (2015).
Few insights
to this phenomenon as output of modern economic security categories analysis
has been made by SVETLAKOV and GLOTINA (2018):
·
economic security became the spot to the countries and a
significant element of nationality;
·
economic security concept is a rather complex and
controversy category;
·
without economic security providing, a country risks not
solve the problem that faces both internally and internationally;
·
while estimating the economic security of a country, it is
necessary to establish certain conditions that set out the main assumptions for
dealing the category of economic security: differences in national interests,
restricted public resources, increased goods and production competition,
increased individual countries competitiveness, others take into account as a
real threat to national interests of the country;
·
state's economic security is a complex socio-economic
concept that images changing material production conditions as well as external
and internal threats to the country's economy.
Possible general country's economic
security concept, that can be divided into four general fields has been offered
by KREMER-MATYSKEVIC
and CERNIUS (2019) in their previous research:
1)
Economic
development;
2)
Living
standard;
3)
Internal
threats;
4)
External
threats.
The fifth part of the country's
economic security concept which was presented by KREMER-MATYSKEVIC and CERNIUS (2019)
is the principles or foundation of economic security.
Country risk in the context of economic
security and sustainability has been measured by SVIDERSKĖ (2015).
According to this researcher, every government in each country wants to be
economically preserved from any dangers. Economic instruments have long been a
component of the government's strategy, meaning that these measures have an
influence on other countries and their policies. From a traditional point of
view, economic security is safety against other authorities and the
manipulation of other powers.
Referring to REHM et al. (2012), MENDOZA
(2019), STANAWAY et al. (2017) some knowledge about economic security concept
are presented below:
·
economic
security is the main subject in national security, which is one of the
resources to ensure a balance between national security;
·
economic
security is one of the national, regional and global security factors that aim
to economically secure and preserve every individual, community or national
economy;
·
the
fundamental objective of governments, regional and international organizations
is to warrant universal human security;
·
the
state's economic conditions are considered as a source and basis for tackling
poverty, hunger, social and economic inequalities.
Economic security risk has been
treated from the shadow economy side by BURAK and SIMANAVICIENE (2018). Authors
have developed recommendations for minimizing and preventions risk and threats
to the state’s economic security:
·
create
an effective mechanism for interaction and exchange of information on the
issues of counteraction to the laundering of illegally received money, which
allows you to make inquiries and receive the necessary information as soon as
possible;
·
to
improve the system of counteracting money laundering and terrorism financing,
expanding the list of subjects of financial monitoring, as well as establishing
a single information channel between the relevant state institution.
Economic security has been stated as
a key component of the national security system, which is characterized by the
ability of the state's national economy and its regions to ensure stable
continuous development and relative protection for both individual and the
whole country, in reliance on economic methods by KROMALCAS et al. (2019).
Based on DADALKO et al. (2017), KREMER-MATYSKEVIC and CERNIUS (2019) shown collected
definitions by the different approaches in Table 1.
Table 1: Definitions of economic security
Approach |
Description |
References |
By content and concept |
protection individual
vital interests, society, the countries and national economic interests |
DADALKO et al. (2017) |
state of economy, authorities, economic system |
||
economic functioning regime |
||
qualitative characteristics of the economic
system |
||
By subject |
vital interests |
|
national interests |
||
economic interests |
||
By security mechanism assurance |
without mechanism indication |
|
normative - legal, administrative -
organizational, economic, technological, informational, etc. |
||
By depending on the consequences |
dangers and
threats |
|
unfavourable external and internal factors |
Source: KREMER-MATYSKEVIC, CERNIUS (2019)
Generalizing
all authors' minds – economic security is national security goal that idea is
to protect the state from external and internal threats and the same time to
maintain the state’s economic development
2.2.
Energy sector
and economic security in European context
Although in the recent period, the Energy sector in Europa Union
countries is constantly transforming from traditional to climate-neutral, this
economic sector still will play the main role in economic development.
After analyzing the European Commission and 8 countries belonging to the
Baltic sea region approaches to the energy sector, the authors of the article
breakdown energy sector activities into main points and showed it in Figure 2.
The energy sector divides into 5 fields: natural gas, oil and oil
products, electricity, and heat sector (heat economy). Since economics
science seldom defines fields of the energy sector, it was decided to take as
the main definition from the official portals of different energy institutions:
Figure 2: Energy sector
Source: composed by authors
·
according to the AMERICAN PETROLEUM INSTITUTE (2020) natural gas is made up of a mixture
of four naturally occurring gases, all of which have different molecular
structures. This mixture consists primarily of methane, ethane, butane, and
propane. Natural gas has been considered by MELTON et al. (2015) to be the
third-most widely used energy source in the world, accounting for approximately
21 percent of total primary energy demand;
·
explained
oil and oil products as the
mixtures of hydrocarbons that formed from the remains of animals and plants
(diatoms) that lived millions of years ago in a marine environment before the
existence of dinosaurs. Over millions of years, the remains of these animals
and plants were covered by layers of sand, silt, and rock. Heat and pressure
from these layers turned the remains into what we now call crude oil or
petroleum. The word petroleum means rock oil or oil from the earth.
·
the same organization - U.S. ENERGY INFORMATION ADMINISTRATION (2020) presents
explanation about electricity -
is the flow of electrical power or charge. Electricity is both a basic part of
nature and one of the most widely used forms of energy. The electricity that
all use is a secondary energy source because it is produced by converting
primary sources of energy such as coal, natural gas, nuclear energy, solar energy,
and wind energy, into electrical power. Electricity is also referred to as an
energy carrier, which means it can be converted to other forms of energy such
as mechanical energy or heat. Primary energy sources are renewable or
nonrenewable energy, but the electricity we use is neither renewable nor
nonrenewable;
·
heating (heat) sector is a field of energy economy
directly related to heating and hot water generation, transmission, supply and
consumption – this explanation is provided by Ministry of
Energy of the Republic of Lithuania on its official portal (MINISTRY OF ENERGY OF THE REPUBLIC
OF LITHUANIA, 2020). The strategic goal in the heating sector is consistent and
balanced renovation (optimisation) of the centralised district heating supply
systems, which ensures effective heating consumption, reliable,
economically-attractive (competitive) supply and generation, provides a
possibility for installation of state-of-the-art and green technologies, using
local and renewable energy resources, ensures flexibility of the system and
favorable investment climate;
·
renewable energy is energy from sources that are
naturally replenishing but flow-limited; renewable resources are virtually
inexhaustible in duration but limited in the amount of energy that is available
per unit of time (MINISTRY OF ENERGY OF THE REPUBLIC OF LITHUANIA, 2020).
According
to Bhatt and Tao (2020) research efforts on utilizing environmentally friendly
renewable alternative sources have gained weighty interest, because of the
limited supply of conventional fossil raw materials. As it may be seen from Figure 2,
traditional energy has its varieties as renewable energy: natural gas – bio
gas; oil products – bio oil; electricity – wind energy, solar power,
aerothermal sources, hydropower, hydrothermal and ocean (sea) sources; heat
sector – biomass, waste, bio fuels, geothermal sources, and hydrothermal and
ocean (sea) sources.
The research between links of the
country's economic security and various economic sectors' is especially rare.
Although energy is one of the most important components of a country's economy,
the impact of this sector on economic security is a rather complex task due to
the different methods of analysis and the approach of scientists.
The main aim of this article is to reveal the country’s economic
security idea and to choose methods for this economic phenomenon evaluation as
well as to suggest the method to evaluate the energy sector's impact on this
economic phenomenon.
3.
METHODOLOGY
3.1.
Measures
to evaluate energy sector activity
Since the scientific problem is how to
evaluate the energy sector and the country's security and what impact the
energy sector has on the country's economic security, firstly it needs to
select what indicators we have to use to evaluate energy sector activities.
Most of the various scientists use energy balance indicators are presented in
Table 2. The energy balance describes all the physical flows of energy that are
embodied in energy products.
Table 2: Energy balance indicators’ description
Indicator |
Indicator description |
Source to analyse |
Production |
Comprises the production of primary energy, i.e.
hard coal, lignite, peat, crude oil, NGLs, natural gas, biofuels and waste,
nuclear, hydro, geothermal, solar and the heat from heat pumps that is
extracted from the ambient environment. Production is calculated after
removal of impurities (e.g. sulphur from natural gas). |
IEA (2019), World Energy Balances (database) |
Imports |
Comprise amounts having crossed the national
territorial boundaries of the country whether or not customs clearance has
taken place. |
|
Exports |
Comprise amounts having crossed the national
territorial boundaries of the country whether or not customs clearance has
taken place. |
|
Total primary energy supply |
Total primary energy supply (TPES) is made up of
production + imports - exports - international marine bunkers - international
aviation bunkers ± stock changes. Note, exports, bunkers and stock changes
incorporate the algebraic sign directly in the number. |
|
Total final consumption |
Equal to the sum of the consumption in the end-use
sectors. Energy used for transformation processes and for own use of the
energy producing industries is excluded. Final consumption reflects for the
most part deliveries to consumers (see note on stock changes). |
|
Electricity, CHP and heat plants |
Sum of Electricity plants, CHP plants and heat
plants. plant. Main activity producers generate electricity
for sale to third parties, as their primary activity. |
|
Oil refineries, transformation |
Positive figures under 'Oil Products' refer to the
manufacture of finished oil products. Negative figures for 'Crude, NGL and
feedstocks' refer to the refinery inputs. |
|
Transport |
Consumption in transport covers all transport
activity (in mobile engines) regardless of the economic sector to which it is
contributing. |
|
Residential |
Includes consumption by households, excluding fuels
used for transport. Includes households with employed persons. |
|
Commercial and public services |
Consumption by commercial and public services |
|
Other final consumption |
Includes agriculture/forestry, fishing,
non-specified (other) and non-energy use. |
|
Electricity output |
Shows the total number of GWh generated by power
plants. Contrary to the Energy Statistics, electricity production for hydro
pumped storage is excluded within the Energy Balances. |
|
Total CO2 emissions - Fuel Combustion (Mt
of CO2) |
Total CO2 emissions - Fuel Combustion (Mt of CO2)
presents total CO2 emissions from fuel combustion. This includes CO2
emissions from fuel combustion reported in IPCC Source/Sink Category 1 A Fuel
Combustion Activities and those which may be reallocated to IPCC Source/Sink
Category 2 Industrial Processes and Product Use under the 2006 IPCC
Guidelines. |
Source:
composed by authors
Nowadays, in the energy policy
change from traditional to climate neutral, researchers have mostly used an
emission indicator to assess the performance of the energy sector.
However, the authors of this article
would like to provide several examples, how the energy is examined:
- CHU et al. (2020)
in their research used the carbon price volatility to the risk management of
the CO2 emissions trading market;
- FIGAJ et al. (2020)
proposed a hybrid geothermal-solar-wind system that was modelled and simulated
by adopted software. Researchers' designed system is managing adequately the
thermal energy flows in order to match the thermal energy demand of the user;
- in ARUMÄGI and
KALAMEES (2020) analysis detailed energy performance-related costs of the
actual solution components compared with the current practice are included, as
well as the costs due to operational energy use and renewable energy harvesting
are calculated;
- MASIP
MACÍA et al. (2019) stated, that the mining industry is characterized by
high consumption of energy due to the wide diversity of processes involved,
specifically the transportation of ore slurry via pipeline systems;
- An energy usage
indicator was used to establish a metric to rank the buildings of each typology
according to their energy efficiency in BERNARDO and OLIVEIRA (2018) article.
Though one of the authors of this
research has already analyzed the impact of the energy sector on Lithuania's
gross domestic product and suggested to use economic indicators of the energy
sector such as energy sector price change (percent), energy sector value-added,
the amount of energy sector taxes paid to the budget, the net profitability of
the energy sector (MACERINSKIENE; KREMER-MATYSKEVIC, 2017), in this research to
evaluate energy sector impact to state’s economic security, it was suggested to
use energy balance indicators (excluding CO2 emissions) downloaded from World
Energy Balances database (INTERNATIONAL ENERGY AGENCY, 2020).
3.2.
Measures
to evaluate country’s economic security
Given that the representatives of
Western countries' economic Science studying economic security at the macro level
use a model developed by professor BRIGUGLIo
(2015) that reflects economic security, with respect to the vulnerability of
the country’s economy and its capacity, as well as the level of resistance (to
combat the crisis and to prepare for shock absorption), it was decided to use
indicators that may describe this method by a better way.
Economic vulnerability is assessed
by the degree of economic openness, which makes it particularly sensitive to
the economic conditions of other countries; dependence on import restrictions;
isolation, that leads to high transport costs and distance from the major sale
sites, MORKUNAS et al. (2018). As a measures to assess economic vulnerability
such indicators like.
According to ZAVADSKAS et al. (2018)
the resilience of the economy is assessed as crisis preparedness: inflation and
unemployment rates, government balance, external debt, government spending, and
shock absorption level: market efficiency, government efficiency, social and
human development, sustainability.
Figure 3 presents indicators were
chosen to measure economic security based on two-level: economic vulnerability
and the resilience of the economy.
Figure 3: Economic security indicators
Source:
composed by authors
Reflected the plenty range of scientist research of
economic vulnerability authors have made the decision to select the following
indicators:
·
Investment/GDP – LAPINSKAITE et al. (2020) believe this
rate shows the state’s sustainable economic development;
·
Individual consumption/GDP – according to DAGILIUTE (2008)
sustainable production and consumption are one of the main goals for countries
economic development;
·
Tax/GDP - Tax analysis shows the effects of tax policy
changes on different groups of individuals via the effects on prices and
returns to labor and capital (AUERBACH, 2018));
·
Isolation/GDP – the developed logistic system also may
predict the state’s economic development and globalization and integration
level in the global economy;
·
Export/GDP and Import/GDP rate could describe how much the
state’s economy is globalized and not dependent on other countries’ economies.
Government consolidated gross debt.
By
authors of this article opinion resilience level can be described by following
coefficients:
·
Government efficiency – traditionally this indicator can be
shown by Total general government expenditure/GDP rate;
·
Balance of payments – from theoretical background - the
balance of payments, also known as balance of international payments, summarizes
all transactions that a country's individuals, companies, and government bodies
complete with individuals, companies, and government bodies outside the
country;
·
Government consolidated gross debt – as Eurostat (EUROPEAN
COMMISSION, 2020) explains government debt is defined as total gross debt at
nominal value outstanding at the end of the year and consolidated between and
within the sectors of general government;
·
R&D – as GALINDO-RUEDA at el. (2018) state investment
in research and development is a key driver of innovation and economic growth.
Thus,
the above written indicators from 2.1. and 2.2. section downloaded from World
Energy Balance database (INTERNATIONAL ENERGY AGENCY, 2020) and Eurostat
database (EUROPEAN COMMISION, 2020), authors use to evaluate energy sector
activities' impact on Baltic sea region EU countries’ economic security.
For
getting the result there were done a few steps:
1) To describe the Baltic sea region in EU
context;
2) To download the data from databases;
3) To define the period during which the
analysis will be performed;
4) To prepare the data for correlation and
regression analysis using SPSS software package;
5) To present the results of the analysis.
4.
RESULTS
First
of all, it needs to describe what is Baltic sea region EU countries (EUSBSR).
Figure 4 shows the map which presents thus countries.
Accordance
to official portal of Baltic sea region strategy the EU member states involved
in the EUSBSR are Sweden, Denmark, Estonia, Finland, Germany, Latvia, Lithuania
and Poland.
Figure 4:
Baltic sea region EU countries’ map
Source:
EUSBSR
Following
second step described in 2 section for getting the results of research there
were downloaded energy data (13 indicators) from World Energy Balances database
(INTERNATIONAL
ENERGY AGENCY, 2020). This database lets to analyze data set
from 1971 to 2018 years. Data from ten indicators measuring the country’s
economic security took from European commission official statistics portal –
Eurostat (EUROPEAN COMMISION, 2020). The economic security dataset lets to
assess only the 2008-2018 period.
In
this article, the authors evaluate the 2008–2018 years period. There also were
prepared data for correlation and regression analyses by coding all indicators:
Energy
sector indicators are independent (X):
·
ENProd- Production;
·
ENImp – Imports;
·
ENExp – Exports;
·
ENSup - Total primary energy supply;
·
ENTips - Electricity, CHP and heat plants;
·
ENOil - Oil refineries, transformation;
·
ENCon - Total final consumption;
·
ENInd – Industry;
·
ENTr – Transport;
·
ENRes – Residential;
·
ENServ - Commercial and public services;
·
ENOther - Other final consumption;
·
ENOut - Electricity output
Country’s
economic security indicators are dependent (Y):
·
ESGd – Government consolidated gross debt;
·
ESIc - Actual individual consumption;
·
ESExp – Export;
·
ESImp – Import;
·
ESLog – Isolation;
·
ESBp - Balance of payments;
·
ESRd – R&D;
·
ESTax - Tax on GDP;
·
ESInv – Investment;
·
ESGex - Total general government expenditure
Further
the result of research is are presented.
First
of all, the authors are preparing data of each country for correlation analysis
in the SPSS software package. After revealing the significant links between the
Energy sector and Economic security indicators which values are more than 0,7
or less -0,7, this article researcher prepare regression analysis. Firstly, we
take into account R square values that show how much percent of data is
included in the analysis, second step to check P-value, that shows the
significance of links between dependent and independent variables. P-value has
to be less than 0.05.
4.1.
Energy
sector impact on Denmark economic security
Denmark energy sector
and economic security indicators correlations results are presented in Table 3.
Correlation analysis
(Table 3) shows the results between Independent and Dependent indicators.
Links color gray are
significant and using this data there were done regression analysis (see Table
4).
Table
3: Correlation (Denmark)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent (X) |
||||||||||
ENProd |
0.025 |
0.493 |
-0.932 |
-0.947 |
-0.370 |
-0.855 |
-0.622 |
-0.302 |
-0.010 |
0.196 |
ENImp |
0.067 |
-0.535 |
0.638 |
0.592 |
0.718 |
0.648 |
0.251 |
0.477 |
0.025 |
-0.144 |
ENExp |
-0.187 |
-0.390 |
0.833 |
0.880 |
-0.012 |
0.666 |
0.555 |
0.040 |
0.118 |
-0.299 |
ENSup |
-0.055 |
0.520 |
-0.818 |
-0.825 |
-0.471 |
-0.767 |
-0.585 |
-0.510 |
-0.009 |
0.108 |
ENTips |
-0.216 |
-0.702 |
0.924 |
0.938 |
0.298 |
0.735 |
0.607 |
0.187 |
0.189 |
-0.348 |
ENOil |
0.019 |
-0.192 |
0.727 |
0.749 |
0.191 |
0.702 |
0.835 |
0.016 |
-0.113 |
-0.033 |
ENCon |
-0.283 |
0.289 |
-0.694 |
-0.686 |
-0.545 |
-0.729 |
-0.428 |
-0.708 |
0.168 |
-0.115 |
ENInd |
-0.390 |
0.097 |
-0.592 |
-0.592 |
-0.407 |
-0.803 |
-0.627 |
-0.626 |
0.381 |
-0.302 |
ENTr |
-0.433 |
0.114 |
-0.723 |
-0.695 |
-0.540 |
-0.816 |
-0.452 |
-0.611 |
0.394 |
-0.310 |
ENRes |
-0.094 |
0.336 |
-0.426 |
-0.424 |
-0.459 |
-0.295 |
-0.053 |
-0.627 |
-0.137 |
0.098 |
ENServ |
-0.270 |
0.334 |
-0.391 |
-0.385 |
-0.598 |
-0.452 |
-0.151 |
-0.699 |
0.080 |
-0.061 |
ENOther |
0.358 |
0.666 |
-0.830 |
-0.857 |
-0.192 |
-0.650 |
-0.561 |
-0.286 |
-0.356 |
0.474 |
ENOut |
0.209 |
0.699 |
-0.837 |
-0.842 |
-0.276 |
-0.583 |
-0.580 |
-0.202 |
-0.241 |
0.288 |
Source: composed by
authors
Correlation
analysis (Table 3) shows the results between Independent and Dependent
indicators.
Links
color gray are significant and using this data there were done regression
analysis (see Table 4).
Reflecting on Table 4
results, the demonstrated regression model formed correct – R square column
shows above 50 percent of the included data.
However, facts that
correlations (see Table 3) present significant links, regression analysis shows
that in Denmark only 2 economic security indicators – Isolation and Taxes are
dependent on the energy sector’s indicators Imports and Total final
consumption. Import has positive impact on Isolation, Taxes – negative on
Consumption.
4.2.
Energy sector impact on Germany economic security
As in Denmark's case, it was done
correlation analysis using Germany dataset. Germany energy sector and
economic security indicators correlations results are presented in Table 5.
Links color gray are
significant and using this data there were done regression analysis (see Table
6).
To follow the result in Table 6 it
can be stated that Germany’s Government consolidated gross debt depending on
Import in the Energy sector.
Energy production directly
influences Actual individual consumption, Electricity output makes impact on
Export, Energy supply – Economic Isolation, and Industry – Investment.
Table
4: Regression (Denmark)
Dependent variable |
Independent variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESExp |
ENProd |
0.982 |
0.964 |
-1.168 |
0.363 |
P>0.05 |
|
ENExp |
-0.010 |
0.993 |
P>0.05 |
||||
ENSup |
1.068 |
0.397 |
P>0.05 |
||||
ENTips |
0.554 |
0.635 |
P>0.05 |
||||
ENOil |
-1.436 |
0.288 |
P>0.05 |
||||
ENTr |
-0.528 |
0.650 |
P>0.05 |
||||
ENOther |
0.589 |
0.616 |
P>0.05 |
||||
ENOut |
-0.349 |
0.760 |
P>0.05 |
||||
ESImp |
ENProd |
0.983 |
0.966 |
-2.260 |
0.073 |
P>0.05 |
|
ENExp |
2.033 |
0.098 |
P>0.05 |
||||
ENTips |
2.434 |
0.059 |
P>0.05 |
||||
ENOil |
-1.879 |
0.119 |
P>0.05 |
||||
ENOther |
1.877 |
0.119 |
P>0.05 |
||||
ESLog |
ENImp |
0.718 |
0.516 |
3.096 |
0.013 |
P<0.05 |
|
ESBp |
ENProd |
0.919 |
0.845 |
-1.099 |
0.352 |
P>0.05 |
|
ENSup |
-0.177 |
0.871 |
P>0.05 |
||||
ENTips |
-0.169 |
0.877 |
P>0.05 |
||||
ENOil |
-0.840 |
0.462 |
P>0.05 |
||||
ENCon |
0.483 |
0.662 |
P>0.05 |
||||
ENInd |
-0.613 |
0.583 |
P>0.05 |
||||
ENTr |
-0.463 |
0.675 |
P>0.05 |
||||
ESTax |
ENCon |
0.708 |
0.501 |
-3.006 |
0.015 |
P<0.05 |
Source: composed by authors
Table
5: Correlation (Germany)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent (X) |
||||||||||
ENProd |
0.402 |
-0.862 |
-0.951 |
-0.814 |
0.711 |
-0.776 |
-0.968 |
-0.751 |
-0.620 |
0.473 |
ENImp |
-0.717 |
0.209 |
0.666 |
0.500 |
0.022 |
0.565 |
0.572 |
0.668 |
0.531 |
-0.560 |
ENExp |
0.688 |
-0.407 |
-0.848 |
-0.640 |
0.361 |
-0.763 |
-0.791 |
-0.743 |
-0.558 |
0.575 |
ENSup |
0.234 |
-0.727 |
-0.699 |
-0.593 |
0.898 |
-0.595 |
-0.789 |
-0.571 |
-0.424 |
0.259 |
ENTips |
-0.450 |
0.801 |
0.947 |
0.793 |
-0.697 |
0.794 |
0.981 |
0.761 |
0.623 |
-0.466 |
ENOil |
0.363 |
0.720 |
0.435 |
0.313 |
-0.680 |
0.392 |
0.534 |
0.062 |
-0.127 |
0.272 |
ENCon |
-0.322 |
-0.085 |
0.208 |
0.202 |
0.351 |
-0.005 |
0.152 |
0.235 |
0.362 |
-0.105 |
ENInd |
-0.227 |
0.051 |
0.500 |
0.640 |
0.165 |
0.330 |
0.335 |
0.119 |
0.730 |
-0.684 |
ENTr |
-0.697 |
0.575 |
0.915 |
0.707** |
-0.367 |
0.779 |
0.879 |
0.811 |
0.695 |
-0.588 |
ENRes |
0.168 |
-0.481 |
-0.611 |
-0.560 |
0.575 |
-0.661 |
-0.572 |
-0.280 |
-0.379 |
0.575 |
ENServ |
-0.183 |
0.043 |
0.299 |
0.160 |
0.076 |
0.258 |
0.235 |
0.220 |
0.010 |
0.008 |
ENOther |
-0.307 |
-0.062 |
0.152 |
0.276 |
0.174 |
-0.254 |
0.193 |
0.147 |
0.567 |
-0.117 |
ENOut |
-0.508 |
0.212 |
0.708 |
0.636 |
0.012 |
0.640 |
0.558 |
0.506 |
0.605 |
-0.663 |
Source:
composed by authors
Table
6: Regression (Germany)
Dependent variable |
Independent
variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESGd |
ENImp |
0.717 |
0.513 |
-3.082 |
0.013 |
P<0.05 |
|
ESIc |
ENProd |
0.940 |
0.884 |
-2.546 |
0.044 |
P<0.05 |
|
ENSup |
0.392 |
0.708 |
P>0.05 |
||||
ENTips |
-1.496 |
0.185 |
P>0.05 |
||||
ENOil |
2.301 |
0.061 |
P>0.05 |
||||
ESExp |
ENProd |
0.994 |
0.988 |
-2.338 |
0.067 |
P>0.05 |
|
ENExp |
-0.976 |
0.374 |
P>0.05 |
||||
ENTips |
1.450 |
0.207 |
P>0.05 |
||||
ENTr |
-1.913 |
0.114 |
P>0.05 |
||||
ENOut |
3.743 |
0.013 |
P<0.05 |
||||
ESImp |
ENProd |
0.814 |
0.663 |
-0.847 |
0.425 |
P>0.05 |
|
ENTips |
-0.031 |
0.976 |
P>0.05 |
||||
ENTr |
-0.011 |
0.991 |
P>0.05 |
||||
ESLog |
ENProd |
0.899 |
0.808 |
-0.274 |
0.791 |
P>0.05 |
|
ENSup |
3.545 |
0.008 |
P<0.05 |
||||
ESBp |
ENProd |
0.829 |
0.687 |
-0.308 |
0.768 |
P>0.05 |
|
ENExp |
-0.775 |
0.468 |
P>0.05 |
||||
ENTips |
0.188 |
0.857 |
P>0.05 |
||||
ENTr |
-0.201 |
0.847 |
P>0.05 |
||||
ESRd |
ENProd |
0.984 |
0.969 |
-0.891 |
0.414 |
P>0.05 |
|
ENExp |
-0.781 |
0.470 |
P>0.05 |
||||
ENSup |
0.285 |
0.787 |
P>0.05 |
||||
ENTips |
1.621 |
0.166 |
P>0.05 |
||||
ENTr |
-0.569 |
0.594 |
P>0.05 |
||||
ESTax |
ENProd |
0.816 |
0.666 |
-0.147 |
0.888 |
P>0.05 |
|
ENExp |
-0.113 |
0.914 |
P>0.05 |
||||
ENTips |
0.032 |
0.975 |
P>0.05 |
||||
ENTr |
0.651 |
0.539 |
P>0.05 |
||||
ESInv |
ENInd |
0.730 |
0.532 |
3.200 |
0.011 |
P<0.05 |
Source: composed by authors
4.3.
Energy
sector impact on Estonian economic security
Correlation analysis was done also
with the Estonian dataset. The results are presenting in Table 7. Significant
links between Energy sector indicators and country’s economic security
indicators are colored grey. Referring link in Table 7, authors prepared
regression analysis (see Table 8). Eight from ten economic security indicators
are significantly dependent on various indicators describing the energy sector
in Estonia (see Table 8).
Table
7: Correlation (Estonia)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent (X) |
||||||||||
ENProd |
0.712 |
0.768 |
0.855 |
0.845 |
-0.760 |
0.491 |
0.004 |
-0.158 |
-0.150 |
-0.597 |
ENImp |
0.732 |
0.646 |
0.651 |
0.716 |
-0.694 |
-0.044 |
-0.074 |
-0.144 |
0.280 |
-0.279 |
ENExp |
-0.797 |
-0.886 |
-0.792 |
-0.802 |
0.920 |
-0.429 |
0.169 |
-0.060 |
0.157 |
0.378 |
ENSup |
0.450 |
0.462 |
0.656 |
0.649 |
-0.427 |
0.031 |
0.038 |
-0.474 |
0.165 |
-0.772 |
ENTips |
0.100 |
0.245 |
-0.194 |
-0.164 |
-0.329 |
0.083 |
-0.315 |
0.581 |
-0.109 |
0.549 |
ENCon |
-0.530 |
-0.114 |
-0.149 |
-0.088 |
0.257 |
-0.868 |
-0.206 |
-0.522 |
0.673 |
-0.152 |
ENInd |
-0.567 |
-0.603 |
-0.321 |
-0.267 |
0.667 |
-0.806 |
0.254 |
-0.624 |
0.711 |
-0.143 |
ENTr |
-0.055 |
0.710 |
0.473 |
0.487 |
-0.591 |
-0.195 |
-0.362 |
-0.170 |
0.162 |
-0.345 |
ENRes |
-0.511 |
-0.487 |
-0.379 |
-0.455 |
0.608 |
-0.092 |
0.145 |
0.086 |
-0.177 |
0.367 |
ENServ |
0.513 |
0.820 |
0.327 |
0.363 |
-0.888 |
0.245 |
-0.681 |
0.365 |
-0.289 |
-0.107 |
ENOther |
0.035 |
0.470 |
0.143 |
0.240 |
-0.385 |
-0.540 |
-0.556 |
-0.281 |
0.562 |
-0.173 |
ENOut |
0.263 |
0.290 |
0.687 |
0.628 |
-0.213 |
0.195 |
0.323 |
-0.532 |
0.023 |
-0.764 |
Source: composed
by authors
Table
8: Regression (Estonia)
Dependent variable |
Independent variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESGd |
ENProd |
0.824 |
0.679 |
0.631 |
0.548 |
P>0.05 |
|
ENImp |
0.967 |
0.366 |
P>0.05 |
||||
ENExp |
-0.310 |
0.766 |
P>0.05 |
||||
ESIc |
ENProd |
0.954 |
0.911 |
0.638 |
0.552 |
P>0.05 |
|
ENImp |
0.189 |
0.858 |
P>0.05 |
||||
ENExp |
-0.383 |
0.717 |
P>0.05 |
||||
ENTr |
1.731 |
0.144 |
P>0.05 |
||||
ENServ |
1.006 |
0.361 |
P>0.05 |
||||
ESExp |
ENProd |
0.912 |
0.832 |
2.689 |
0.031 |
P<0.05 |
|
ENImp |
2.037 |
0.081 |
P>0.05 |
||||
ENExp |
1.028 |
0.338 |
P>0.05 |
||||
ESImp |
ENProd |
0.971 |
0.942 |
2.689 |
0.031 |
P<0.05 |
|
ENImp |
2.037 |
0.081 |
P>0.05 |
||||
ENExp |
1.028 |
0.338 |
P>0.05 |
||||
ESLog |
ENProd |
0.971 |
0.942 |
-0.631 |
0.548 |
P>0.05 |
|
ENExp |
1.674 |
0.138 |
P>0.05 |
||||
ENServ |
-3.307 |
0.013 |
P<0.05 |
||||
ESBp |
ENCon |
0.902 |
0.813 |
-2.643 |
0.030 |
P<0.05 |
|
ENInd |
-1.585 |
0.152 |
P>0.05 |
||||
ESInv |
ENInd |
0.711 |
0.506 |
3.036 |
0.014 |
P<0.05 |
|
ESGex |
ENSup |
0.772 |
0.595 |
-3.638 |
0.005 |
P<0.05 |
Source: composed by authors
Export
and Import are depending on Energy production, energy sector’s indicator -
Commercial and public services do impact on Isolation, energy Consumption
influences balance of payments, Industry effects on Investment, and Total
primary energy supply directly powers to Total general government expenditure.
4.4.
Energy
sector impact on Latvian economic security
The authors have done correlation analysis with the
Latvian dataset. Correlation results are presenting in Table 9.
Table
9: Correlation (Latvia)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent (X) |
||||||||||
ENProd |
0.277 |
0.765 |
0.643 |
0.515 |
-0.499 |
0.322 |
-0.022 |
0.867 |
-0.435 |
-0.389 |
ENImp |
0.094 |
0.650 |
0.598 |
0.544 |
-0.227 |
0.130 |
-0.048 |
0.659 |
-0.223 |
-0.604 |
ENExp |
-0.334 |
-0.761 |
-0.702 |
-0.577 |
0.485 |
-0.242 |
-0.022 |
-0.917 |
0.521 |
0.549 |
ENSup |
-0.419 |
0.172 |
0.023 |
-0.028 |
-0.235 |
-0.244 |
0.069 |
-0.053 |
0.422 |
0.202 |
ENTips |
-0.150 |
-0.589 |
-0.569 |
-0.493 |
0.396 |
0.028 |
-0.019 |
-0.686 |
0.321 |
0.608 |
ENCon |
-0.470 |
-0.283 |
-0.408 |
-0.361 |
0.000 |
-0.274 |
-0.073 |
-0.464 |
0.561 |
0.408 |
ENInd |
0.544 |
0.415 |
0.803 |
0.781 |
0.017 |
-0.062 |
0.525 |
0.572 |
-0.347 |
-0.389 |
ENTr |
-0.648 |
0.141 |
-0.335 |
-0.455 |
-0.620 |
-0.205 |
-0.364 |
0.041 |
0.328 |
0.137 |
ENRes |
-0.241 |
-0.710 |
-0.683 |
-0.549 |
0.481 |
-0.030 |
-0.085 |
-0.867 |
0.442 |
0.627 |
ENServ |
-0.203 |
0.462 |
0.436 |
0.488 |
-0.287 |
-0.375 |
0.117 |
0.354 |
0.338 |
-0.422 |
ENOther |
-0.051 |
0.894 |
0.762 |
0.626 |
-0.618 |
-0.178 |
0.009 |
0.907 |
-0.157 |
-0.737 |
ENOut |
0.406 |
0.311 |
0.305 |
0.167 |
-0.434 |
0.316 |
-0.230 |
0.555 |
-0.511 |
0.040 |
Source:
composed by authors
Significant links between Latvian
Energy sector indicators and country’s economic security indicators also are
colored grey. In accordance with to correlation results presented in Table 9,
the authors did regression analysis and put it to Table 10.
Table
10: Regression (Latvia)
Dependent variable |
Independent
variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESIc |
ENProd |
0.931 |
0.867 |
0.027 |
0.979 |
P>0.05 |
|
ENExp |
-0.470 |
0.655 |
P>0.05 |
||||
ENRes |
0.835 |
0.436 |
P>0.05 |
||||
ENOther |
2.862 |
0.029 |
P<0.05 |
||||
ESExp |
ENExp |
0.896 |
0.803 |
0.523 |
0.617 |
P>0.05 |
|
ENInd |
2.707 |
0.030 |
P<0.05 |
||||
ENOther |
1.941 |
0.093 |
P>0.05 |
||||
ESImp |
ENInd |
0.781 |
0.609 |
3.746 |
0.005 |
P<0.05 |
|
ESTax |
ENProd |
0.965 |
0.931 |
0.883 |
0.411 |
P>0.05 |
|
ENExp |
-0.016 |
0.988 |
P>0.05 |
||||
ENRes |
-0.295 |
0.778 |
P>0.05 |
||||
ENOther |
1.558 |
0.170 |
P>0.05 |
||||
ESGex |
ENOther |
0.737 |
0.542 |
-3.266 |
0.010 |
P<0.05 |
Source: composed
by authors
Estonian
economic security indicator Actual individual consumption is depending on
Energy other consumption, Export and Import are influenced by energy Industry,
and energy other consumption does impact on Total general government
expenditure, which is the country’s economic security indicator.
4.5.
Energy
sector impact on Lithuanian economic security
Lithuanian energy sector and
economic security indicators correlations results are presented in Table 11.
Table 11: Correlation (Lithuania)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent
(X) |
||||||||||
ENProd |
-0.833 |
-0.256 |
-0.714 |
-0.697 |
-0.540 |
-0.391 |
-0.478 |
0.683 |
0.498 |
0.421 |
ENImp |
0.405 |
0.582 |
0.545 |
0.446 |
0.305 |
-0.118 |
0.121 |
-0.066 |
0.085 |
-0.580 |
ENExp |
-0.380 |
-0.527 |
-0.229 |
-0.105 |
0.139 |
0.006 |
-0.093 |
-0.103 |
-0.056 |
0.504 |
ENSup |
-0.947 |
-0.149 |
-0.520 |
-0.497 |
-0.307 |
-0.625 |
-0.556 |
0.699 |
0.685 |
0.324 |
ENTips |
0.855 |
0.496 |
0.749 |
0.672 |
0.439 |
0.441 |
0.566 |
-0.536 |
-0.402 |
-0.600 |
ENOil |
0.303 |
0.660 |
0.025 |
-0.185 |
-0.134 |
0.112 |
0.352 |
0.503 |
0.121 |
-0.478 |
ENCon |
-0.020 |
0.815 |
0.553 |
0.406 |
0.201 |
-0.320 |
0.171 |
0.285 |
0.553 |
-0.728 |
ENInd |
0.272 |
0.633 |
0.913 |
0.859 |
0.396 |
-0.057 |
0.401 |
-0.328 |
0.192 |
-0.751 |
ENTr |
-0.006 |
0.883 |
0.211 |
-0.006 |
-0.140 |
-0.130 |
0.140 |
0.594 |
0.541 |
-0.726 |
ENRes |
-0.556 |
-0.682 |
-0.482 |
-0.301 |
0.216 |
-0.273 |
-0.819 |
0.052 |
-0.077 |
0.773 |
ENServ |
-0.131 |
0.612 |
0.215 |
0.129 |
0.156 |
0.010 |
-0.282 |
0.375 |
0.216 |
-0.403 |
ENOther |
0.107 |
0.663 |
0.722 |
0.620 |
0.308 |
-0.358 |
0.398 |
-0.015 |
0.455 |
-0.675 |
ENOut |
-0.835 |
-0.504 |
-0.753 |
-0.676 |
-0.469 |
-0.431 |
-0.552 |
0.521 |
0.389 |
0.593 |
Source: composed by authors
Strong correlations between the
Lithuanian energy sector and economic security indicators were colored grey.
Based on these figures the authors prepared regression analysis shown in Table
12.
Table
12: Regression (Lithuania)
Dependent variable |
Independent variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESGd |
ENProd |
0.970 |
0.941 |
1.420 |
0.206 |
P>0.05 |
|
ENSup |
-3.008 |
0.024 |
P<0.05 |
||||
ENTips |
1.014 |
0.350 |
P>0.05 |
||||
ENOut |
0.760 |
0.476 |
P>0.05 |
||||
ESIc |
ENCon |
0.893 |
0.798 |
0.851 |
0.419 |
P>0.05 |
|
ENTr |
2.300 |
0.050 |
P<0.05 |
||||
ESExp |
ENProd |
0.953 |
0.908 |
-1.034 |
0.348 |
P>0.05 |
|
ENTips |
0.461 |
0.664 |
P>0.05 |
||||
ENInd |
2.422 |
0.060 |
P>0.05 |
||||
ENOther |
0.385 |
0.716 |
P>0.05 |
||||
ENOut |
0.572 |
0.592 |
P>0.05 |
||||
ESImp |
ENInd |
0.859 |
0.737 |
5.022 |
0.001 |
P<0.05 |
|
ESRd |
ENRes |
0.819 |
0.671 |
-4.280 |
0.002 |
P<0.05 |
|
ESGex |
ENCon |
0.96 |
0.922 |
1.440 |
0.200 |
P>0.05 |
|
ENInd |
-2.966 |
0.025 |
P<0.05 |
||||
ENTr |
-2.081 |
0.083 |
P>0.05 |
||||
ENRes |
2.022 |
0.090 |
P>0.05 |
Source:
composed by authors
Government consolidated gross debt
in Lithuania is powered by Total primary energy supply, and energy sector
indicator Transport influences on Actual individual consumption.
Economic security indicators Import
and Total general government expenditure are strongly depending on Energy
Industry, Research and development – on Residential.
4.6.
Energy
sector impact on Poland economic security
Table 13 contains correlations
results between Poland energy sector and economic security indicators.
Table
13: Correlation (Poland)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent
(X) |
||||||||||
ENProd |
0.311 |
-0.409 |
-0.459 |
-0.370 |
-0.151 |
-0.492 |
-0.646 |
-0.498 |
0.555 |
0.364 |
ENImp |
-0.168 |
0.794 |
0.829 |
0.775 |
0.452 |
0.584 |
0.842 |
0.753 |
-0.704 |
-0.640 |
ENExp |
-0.410 |
-0.314 |
-0.590 |
-0.572 |
-0.628 |
-0.755 |
-0.589 |
-0.109 |
0.603 |
0.730 |
ENSup |
-0.017 |
0.709 |
0.573 |
0.542 |
0.426 |
0.176 |
0.448 |
0.637 |
-0.505 |
-0.249 |
ENTips |
-0.362 |
0.326 |
0.507 |
0.418 |
0.247 |
0.774 |
0.730 |
0.579 |
-0.630 |
-0.686 |
ENOil |
-0.469 |
-0.155 |
-0.061 |
-0.184 |
-0.041 |
0.337 |
0.160 |
0.316 |
-0.069 |
-0.187 |
ENCon |
-0.049 |
0.688 |
0.671 |
0.614 |
0.473 |
0.445 |
0.643 |
0.676 |
-0.701 |
-0.447 |
ENInd |
-0.181 |
0.874 |
0.879 |
0.841 |
0.680 |
0.651 |
0.805 |
0.841 |
-0.721 |
-0.771 |
ENTr |
-0.186 |
0.647 |
0.681 |
0.613 |
0.431 |
0.529 |
0.702 |
0.722 |
-0.688 |
-0.544 |
ENRes |
0.428 |
-0.104 |
-0.265 |
-0.242 |
-0.132 |
-0.414 |
-0.319 |
-0.314 |
0.001 |
0.596 |
ENServ |
0.553 |
-0.155 |
-0.207 |
-0.212 |
-0.105 |
-0.355 |
-0.273 |
-0.269 |
-0.070 |
0.438 |
ENOther |
-0.275 |
0.773 |
0.794 |
0.725 |
0.548 |
0.605 |
0.770 |
0.845 |
-0.655 |
-0.686 |
ENOut |
0.250 |
0.787 |
0.941 |
0.910 |
0.787 |
0.746 |
0.848 |
0.585 |
-0.842 |
-0.811 |
Source: composed by authors
Following
the same examination structure that was done with other countries, the authors
supplied regression analysis results in Table 14.
Although Table 13 shows
a lot of significant correlations, regression analysis presents several
significant dependencies between the Energy sector and economic security
indicators in Poland.
So, Import, Export,
Isolation, R&D are influenced by Electricity output, Balance of payments
are depending on energy Export and Electricity, CHP and heat plants.
Electricity, CHP and
heat plants also make an impact on R&D, as well as energy Export makes the
force on Total general government expenditure.
Table 14: Regression (Poland)
Dependent variable |
Independent
variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESIc |
ENImp |
0.906 |
0.820 |
0.297 |
0.779 |
P>0.05 |
|
ENSup |
0.562 |
0.599 |
P>0.05 |
||||
ENInd |
1.873 |
0.120 |
P>0.05 |
||||
ENOther |
-1.087 |
0.327 |
P>0.05 |
||||
ENOut |
0.115 |
0.913 |
P>0.05 |
||||
ESExp |
ENImp |
0.959 |
0.919 |
0.673 |
0.526 |
P>0.05 |
|
ENInd |
1.385 |
0.215 |
P>0.05 |
||||
ENOther |
-1.186 |
0.280 |
P>0.05 |
||||
ENOut |
2.753 |
0.033 |
P<0.05 |
||||
ESImp |
ENImp |
0.917 |
0.841 |
-0.373 |
0.720 |
P>0.05 |
|
ENInd |
0.741 |
0.483 |
P>0.05 |
||||
ENOut |
2.422 |
0.046 |
P<0.05 |
||||
ESLog |
ENOut |
0.787 |
0.619 |
3.821 |
0.004 |
P<0.05 |
|
ESBp |
ENExp |
0.943 |
0.889 |
-2.596 |
0.036 |
P<0.05 |
|
ENTips |
3.285 |
0.013 |
P<0.05 |
||||
ENOut |
1.754 |
0.123 |
P>0.05 |
||||
ESRd |
ENImp |
0.986 |
0.973 |
3.766 |
0.020 |
P<0.05 |
|
ENTips |
4.464 |
0.011 |
P<0.05 |
||||
ENInd |
-0.283 |
0.791 |
P>0.05 |
||||
ENTr |
-2.524 |
0.065 |
P>0.05 |
||||
ENOther |
-1.252 |
0.279 |
P>0.05 |
||||
ENOut |
3.333 |
0.029 |
P<0.05 |
||||
ESTax |
ENImp |
0.873 |
0.762 |
-0.336 |
0.749 |
P>0.05 |
|
ENInd |
0.547 |
0.604 |
P>0.05 |
||||
ENTr |
-0.476 |
0.651 |
P>0.05 |
||||
ENOther |
1.152 |
0.293 |
P>0.05 |
||||
ESInv |
ENImp |
0.779 |
0.607 |
-0.191 |
0.855 |
P>0.05 |
|
ENInd |
-1.252 |
0.257 |
P>0.05 |
||||
ENTr |
-0.760 |
0.476 |
P>0.05 |
||||
ENOther |
1.036 |
0.340 |
P>0.05 |
||||
ESGex |
ENExp |
0.911 |
0.829 |
2.515 |
0.040 |
P<0.05 |
|
ENInd |
-1.644 |
0.144 |
P>0.05 |
||||
ENOut |
-0.111 |
0.914 |
P>0.05 |
Source: composed by authors
4.7.
Energy sector impact on Finland economic security
This article’s author
present Finland energy sector and economic security indicators correlations
results in Table 15.
Finland dataset
correlations results in Table 15 presented not a lot of significant links, even
so, authors have done regression analysis which results are shown in Table 16.
Table
15: Correlation (Finland)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent (X) |
||||||||||
ENProd |
0.756 |
0.602 |
0.757 |
0.633 |
-0.221 |
-0.637 |
-0.723 |
0.551 |
-0.147 |
0.431 |
ENImp |
-0.578 |
-0.157 |
-0.249 |
-0.088 |
0.184 |
0.293 |
0.543 |
-0.319 |
0.183 |
-0.343 |
ENExp |
-0.707 |
-0.744 |
-0.574 |
-0.514 |
0.303 |
0.704 |
0.681 |
-0.752 |
0.146 |
-0.484 |
ENSup |
-0.598 |
-0.424 |
-0.192 |
-0.081 |
0.518 |
0.443 |
0.597 |
-0.680 |
0.311 |
-0.518 |
ENTips |
0.659 |
0.270 |
0.450 |
0.276 |
-0.073 |
-0.472 |
-0.901 |
0.609 |
0.147 |
0.150 |
ENOil |
0.589 |
0.427 |
0.743 |
0.670 |
-0.468 |
-0.537 |
-0.638 |
0.647 |
-0.159 |
0.291 |
ENCon |
-0.082 |
-0.168 |
0.186 |
0.176 |
0.529 |
0.101 |
-0.058 |
-0.204 |
0.368 |
-0.379 |
ENInd |
-0.125 |
-0.263 |
0.311 |
0.282 |
0.460 |
0.061 |
-0.185 |
-0.063 |
0.475 |
-0.589 |
ENTr |
-0.623 |
-0.346 |
-0.091 |
0.029 |
0.523 |
0.338 |
0.584 |
-0.673 |
0.469 |
-0.614 |
ENRes |
-0.107 |
-0.035 |
-0.147 |
-0.099 |
0.317 |
0.148 |
0.311 |
-0.437 |
0.066 |
0.042 |
ENServ |
0.192 |
0.383 |
0.206 |
0.260 |
-0.004 |
-0.217 |
0.142 |
-0.168 |
-0.110 |
0.359 |
ENOther |
0.346 |
0.036 |
-0.043 |
-0.164 |
0.021 |
-0.009 |
-0.534 |
0.476 |
-0.159 |
0.166 |
ENOut |
-0.778 |
-0.647 |
-0.462 |
-0.355 |
0.550 |
0.698 |
0.752 |
-0.822 |
0.278 |
-0.587 |
Source: composed by authors
Finland dataset
correlations results in Table 15 presented not a lot of significant links, even
so, authors have done regression analysis which results are shown in Table 16.
Table 16: Regression (Finland)
Dependent variable |
Independent variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESGd |
ENProd |
0.887 |
0.786 |
1.776 |
0.119 |
P>0.05 |
|
ENExp |
-0.224 |
0.829 |
P>0.05 |
||||
ENOut |
-2.303 |
0.055 |
P>0.05 |
||||
ESIc |
ENExp |
0.744 |
0.554 |
-3.344 |
0.009 |
P<0.05 |
|
ESExp |
ENProd |
0.837 |
0.700 |
1.985 |
0.082 |
P>0.05 |
|
ENOil |
1.847 |
0.102 |
P>0.05 |
||||
ESRd |
ENProd |
0.941 |
0.885 |
-2.056 |
0.079 |
P>0.05 |
|
ENTips |
-3.109 |
0.017 |
P<0.05 |
||||
ENOut |
0.176 |
0.865 |
P>0.05 |
||||
ESTax |
ENExp |
0.88 |
0.775 |
-1.872 |
0.098 |
P>0.05 |
|
ENOut |
-2.726 |
0.026 |
P<0.05 |
Source: composed by authors
Finland energy Export indicator
impacts on Actual individual consumption, CHP and heat plants. Electricity
directly links with R&D, and Tax indicator is depending on Electricity
output.
4.8.
Energy
sector impact on Sweden economic security
As in other 7 countries’ case in
this reaserch, it was done correlation analysis using Sweden dataset.
Sweden energy sector and economic
security indicators correlations results are presented in Table 17.
Table
17: Correlation (Sweden)
Dependent (Y) |
ESGd |
ESIc |
ESExp |
ESImp |
ESLog |
ESBp |
ESRd |
ESTax |
ESInv |
ESGex |
Independent (X) |
||||||||||
ENProd |
0.083 |
0.678 |
0.877 |
0.895 |
-0.441 |
-0.583 |
-0.208 |
-0.033 |
0.446 |
-0.479 |
ENImp |
-0.050 |
-0.193 |
0.197 |
0.243 |
0.230 |
-0.530 |
0.113 |
0.566 |
0.753 |
-0.781 |
ENExp |
-0.265 |
-0.084 |
-0.506 |
-0.577 |
0.214 |
0.837 |
-0.042 |
-0.435 |
-0.754 |
0.687 |
ENSup |
-0.591 |
0.370 |
0.289 |
0.232 |
0.038 |
0.222 |
-0.168 |
-0.144 |
-0.046 |
-0.141 |
ENTips |
0.076 |
-0.513 |
-0.697 |
-0.730 |
0.185 |
0.384 |
0.038 |
-0.083 |
-0.452 |
0.221 |
ENOil |
0.349 |
-0.100 |
-0.064 |
-0.047 |
-0.179 |
-0.336 |
-0.370 |
-0.227 |
-0.128 |
-0.022 |
ENCon |
-0.569 |
-0.118 |
0.105 |
0.077 |
0.171 |
-0.092 |
0.042 |
0.287 |
0.304 |
-0.478 |
ENInd |
-0.700 |
-0.046 |
-0.065 |
-0.158 |
0.405 |
0.559 |
0.021 |
-0.173 |
-0.090 |
-0.273 |
ENTr |
0.088 |
-0.233 |
0.221 |
0.309 |
0.138 |
-0.694 |
0.254 |
0.697 |
0.869 |
-0.692 |
ENRes |
-0.341 |
0.496 |
0.511 |
0.445 |
-0.622 |
-0.318 |
-0.508 |
-0.341 |
-0.219 |
-0.163 |
ENServ |
-0.206 |
-0.393 |
-0.492 |
-0.527 |
0.289 |
0.203 |
-0.056 |
0.260 |
-0.193 |
0.032 |
ENOther |
-0.493 |
-0.542 |
-0.275 |
-0.238 |
0.643 |
0.169 |
0.596 |
0.674 |
0.536 |
-0.211 |
ENOut |
0.079 |
0.607 |
0.843 |
0.844 |
-0.455 |
-0.537 |
-0.201 |
-0.122 |
0.413 |
-0.584 |
Source: composed by authors
It may seem that the energy
sector indicators make a lack of impact on the country’s economic security
factors.
Having a little amount
of significance, the authors of this article still decided to prepare a regression
analysis declared in Table 18.
Table
18: Regression (Sweden)
Dependent variable |
Independent variable |
R |
R Square |
t |
Sig. |
Comment |
|
ESExp |
ENProd |
0.883 |
0.780 |
1.587 |
0.151 |
P>0.05 |
|
ENOut |
0.632 |
0.545 |
P>0.05 |
||||
ESImp |
ENProd |
0.898 |
0.806 |
0.449 |
0.667 |
P>0.05 |
|
ENTips |
-0.166 |
0.873 |
P>0.05 |
||||
ENOut |
0.345 |
0.740 |
P>0.05 |
||||
ESBp |
ENExp |
0.837 |
0.701 |
4.590 |
0.001 |
P<0.05 |
|
ESInv |
ENTr |
0.869 |
0.754 |
5.259 |
0.001 |
P<0.05 |
Source: composed by authors
From Table 18 it is
understood that the Balances of payments in Sweden is depending on the energy
sector Export indicator, and Investment is powered by Transport.
Table
19: Energy sector impact on Baltic
sea region EU countries’ economic security
Independent variable |
Dependent variable |
t |
Sig. |
Comment |
Country |
|
ENCon |
ESBp |
-2.643 |
0.030 |
P<0.05 |
Estonia |
|
ESTax |
-3.006 |
0.015 |
P<0.05 |
Denmark |
||
ENExp |
ESBp |
-2.596 |
0.036 |
P<0.05 |
Poland |
|
ESBp |
4.590 |
0.001 |
P<0.05 |
Sweden |
||
ESGex |
2.515 |
0.040 |
P<0.05 |
Poland |
||
ESIc |
-3.344 |
0.009 |
P<0.05 |
Finland |
||
ENImp |
ESGd |
-3.082 |
0.013 |
P<0.05 |
Germany |
|
ESLog |
3.096 |
0.013 |
P<0.05 |
Denmark |
||
ESRd |
3.766 |
0.020 |
P<0.05 |
Poland |
||
ENInd |
ESExp |
2.707 |
0.030 |
P<0.05 |
Latvia |
|
ESGex |
-2.966 |
0.025 |
P<0.05 |
Lithuania |
||
ESImp |
3.746 |
0.005 |
P<0.05 |
Latvia |
||
ESImp |
5.022 |
0.001 |
P<0.05 |
Lithuania |
||
ESInv |
3.200 |
0.011 |
P<0.05 |
Germany |
||
ESInv |
3.036 |
0.014 |
P<0.05 |
Estonia |
||
ENOther |
ESGex |
-3.266 |
0.010 |
P<0.05 |
Latvia |
|
ESIc |
2.862 |
0.029 |
P<0.05 |
Latvia |
||
ENOut |
ESExp |
3.743 |
0.013 |
P<0.05 |
Germany |
|
ESExp |
2.753 |
0.033 |
P<0.05 |
Poland |
||
ESImp |
2.422 |
0.046 |
P<0.05 |
Poland |
||
ESLog |
3.821 |
0.004 |
P<0.05 |
Poland |
||
ESRd |
3.333 |
0.029 |
P<0.05 |
Poland |
||
ESTax |
-2.726 |
0.026 |
P<0.05 |
Finland |
||
ENProd |
ESExp |
2.689 |
0.031 |
P<0.05 |
Estonia |
|
ESIc |
-2.546 |
0.044 |
P<0.05 |
Germany |
||
ESImp |
2.689 |
0.031 |
P<0.05 |
Estonia |
||
ENRes |
ESRd |
-4.280 |
0.002 |
P<0.05 |
Lithuania |
|
ENServ |
ESLog |
-3.307 |
0.013 |
P<0.05 |
Estonia |
|
ENSup |
ESGd |
-3.008 |
0.024 |
P<0.05 |
Lithuania |
|
ESGex |
-3.638 |
0.005 |
P<0.05 |
Estonia |
||
ESLog |
3.545 |
0.008 |
P<0.05 |
Germany |
||
ENTips |
ESBp |
3.285 |
0.013 |
P<0.05 |
Poland |
|
ESRd |
4.464 |
0.011 |
P<0.05 |
Poland |
||
ESRd |
-3.109 |
0.017 |
P<0.05 |
Finland |
||
ENTr |
ESIc |
2.300 |
0.050 |
P<0.05 |
Lithuania |
|
ESInv |
5.259 |
0.001 |
P<0.05 |
Sweden |
Source: composed by authors
Table 19 shows energy
sector indicators that influence economic security indicators in the Baltic sea
region EU states. To conclude the results in this table it can be stated that
most often countries' economic security factors are depended on Energy Export,
Industry, Electricity output. Energy Import and Production have a pretty
significant role in forming economic security.
Following eight
countries' analysis results, the authors suggest not limited Lino Briguglio
developed system indicators but to broaden research including indexes from the
other economic schools.
5. CONCLUSIONS
The authors have done
reviewing economic security literature. Different approaches to economic
security principles let to do some assumptions related to the country's
economic security concept. Firstly, the country's economic security cannot be
separated from other factors of the state’s security dimensions such as
political and military, economic, and human rights issues. Second, economic
security at the macroeconomic level can be shown from the prism of external
threats, suchlike countries’ dependency on energy resources, poverty,
unemployment, migration, and corruption.
Also, the authors have
described the energy sector creating the general structure to reveal this
sector's main activities as well as selected indicators that analyze energy
sector.
To analyze the economic
security at the macro level this article authors use BRIGULIO proposed method
into two-level: economic vulnerability and resilience level. The authors have
decided to use indicators that may describe this method in a better way.
Using the Baltic sea
region EU states' datasets that include the indicators measuring the energy
sector and the country's economic security, the authors have prepared
correlation and regression analysis. The research has covered a period of 11
years (from 2008 - 2018 years) and applied for each EU country of the Baltic
sea region. The results of the research were presented in Tables 3-19, as well
as briefly declared in third article part. The main conclusion of research
results is that most often countries' economic security factors are dependent
on Energy Export, Industry, Electricity output. Energy Import and Production
have a pretty significant role in forming economic security, too.
This research could
serve as a basis for further SWOT and PEST analysis.
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