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2211
Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
t. LXXIII
nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
Mjr dr Bartosz Kozicki
Wojskowa Akademia Techniczna
ORCID: 0000-0001-6089-952X
e-mail: bartosz.kozicki@wat.edu.pl
Por. mgr Paweł Jaśkiewicz
IWojskowa Akademia Techniczna
ORCID: 0000-0002-8863-6948
e-mail: pawel.jaskiewicz@wat.edu.pl
Multidimensional comparative analysis
of populations and deaths
of people in European countries
in terms of economic security
Wielowymiarowa analiza porównawcza populacji i zgonów ludzi
w państwach Europy w aspekcie bezpieczeństwa ekonomicznego
Streszczenie
Celem artykułu jest przeprowadzenie wielowymiarowej analizy
porównawczej populacji i zgonów ludzi w państwach Europy
w aspekcie bezpieczeństwa ekonomicznego. Do badań zastoso-
wano wielowymiarowe analizy porównawcze. Dane poddawano
grupowaniu i rozplataniu. Następnie zestawiano je na wykre-
sach i oceniono. Podmiotem badań są 32 państwa Europy, zaś
przedmiotem populacja i zgony ludzi w latach 2005–2018. Sfor-
mułowano pytanie badawcze, które brzmi: „Czy zastosowanie
wielowymiarowej analizy porównawczej populacji i zgonów lu-
dzi w 32 poszczególnych państwach Europy pozwoli wykryć
prawidłowości rządzące rozpatrywanym zjawiskiem?”.
Artykuł zawiera wielowymiarowe analizy porównawcze
zmiennych zależnych (32 państwa Europy, lata) i zmiennych
je objaśniających (populacja i zgony ludzi) w aspekcie wpływu
na bezpieczeństwo ekonomiczne. Rezultatem przeprowadzo-
nych badań są zależności powtarzające się w jednoimiennych
przedziałach czasowych — latach.
Wykrycie prawidłowości utrzymujących się w populacji i zgo-
nach ludzi w 32 poszczególnych państwach Europy poprzez za-
stosowanie wielowymiarowych analiz porównawczych może
pozwolić na ich prognozowanie na przyszłość. Wyliczono in-
deksy zgonów w populacjach w punktach procentowych w każ-
dym z 32 rozpatrywanych państw Europy w latach 2005–2018.
Pozwoliły one na zaobserwowanie podobieństw w analizowa-
nych szeregach czasowych.
Keywords:
population, deaths, multidimensional comparative
analyses, economic security
JEL: C51, E31, E37, E64
Słowa kluczowe:
populacja, zgony, wielowymiarowe analizy porównawcze,
bezpieczeństwo ekonomiczne
Abstract
The objective of the article is to carry out a multidimensional
comparative analysis of populations and human deaths in
European countries in terms of economic security. The
research applies tools of comparative analysis, first by
grouping and unraveling the data and then by their charting
and evaluation. The study covers 32 European countries
focusing on populations and deaths of people in 2005–2018.
The research question has been formulated as: "Will the
application of multidimensional comparative analysis of
populations and deaths of people in 32 European countries
allow to detect any regularities occurring in the phenomenon?"
The article provides multidimensional comparative analyses of
dependent variables (32 European countries, years) and
explanatory variables (population and human deaths) in terms
of the impact on economic security. The results of the studies
carried out are repetitive relationships in mononomial
intervals — years.
Detecting regularities persistent in populations and human
deaths in 32 European countries using multidimensional
comparative analyses may allow their predicting in the
future. Death rates expressed in percentage points in
populations of 32 European countries in 2005–2018 were
calculated and enabled observation of similarities in the
time series analyzed.
Introduction and literature review
In 32 European countries, the population and the
number of deaths of people in 2005–2018 are
increasing steadily. The total of 506,947,964 people
were recorded in 32 European countries in 2005 and
by 2018 this number increased to 529,108,246. In
2005, there were 4,975,928 deaths in 32 European
countries, increasing to 5,418,241 in 2018. According
to literature, Europe owes the increase of its
population to migration because the difference
between birth and death rates is negative (Tracz-
-Dral, 2018, p. 6).
1
In terms of population, number of deaths, and
economic power, among 32 European countries
Germany is the leader,
2
followed by France and the
United Kingdom.
Undoubtedly, the number of people in the
European countries is and will be affected in the
future by the COVID-19 pandemic. COVID-19 is an
infectious disease that first appeared in the world in
Wuhan, China in December 2019 (Zhu et al., 2020).
It tended to spread rapidly and it was declared
a pandemic on 11 March 2020 (Satomi et al., 2020).
COVID-19 has contributed to an increase in the
number of human deaths worldwide. Countries have
taken measures to overcome the disease: closure of
borders, limitation of movement and other
restrictions that citizens have had and still have to
comply with (Manurung, 2020).
As yet, no complete and detailed data on global
human deaths between 2019–2020 are available in
online databases so the study intends to examine
trends seen before the COVID-19 pandemic
(2005–2018) for the sake of future studies on this
issue in terms of economic security. It was
observed that in the preliminary stage of the
COVID-19 pandemic — i.e. March 2020 — the
number of deaths in European countries
collectively hovered around a statistical error of
around 0.005 percentage point (Kozicki, Mitkov,
2020).
According to T. Szubrycht, security is a condition
that gives a sense of confidence, a belief this is going
to last, and an opportunity of improvement
(Szubrycht, 2006, p. 87). This paper considers one
type of security, focusing on the issue of economic
security.
In literature, economic security is seen as the
provision of economic conditions essential for
survival, prosperity and sustainable development of
a society, for smooth operation of the state with its
institutions. It is also seen as a condition achieved
through effective overcoming of external or internal
destructive factors that could entail developmental
disorders (Kitler, 2011, p. 49). When assessing this
interpretation of the meaning of economic security
in the context of this paper, it should be observed
that it addresses the issue of preserving, in European
countries taken into account, of regularities
concerning lasting trends in the level of populations
and deaths. These are studied in dynamic terms as
they occur over time.
Multidimensional comparative analyses were
applied for the research. These belong to a group of
statistical methods where at least two variables
describing each object (phenomenon) in question
(Łuniewska, 2006, p. 9) are analyzed simultaneously.
Within multidimensional comparative analyses, the
linear ordering methods were applied, ranked from
largest to smallest. Tools including grouping and
unraveling were used in examining the data. The
study consists of the summary where research
methods are described, two key research sections,
and the conclusion.
Multidimensional comparative
analysis of populations
and deaths in European countries
The study began with preparation of a line chart
showing the human population in 32 European
countries between 2005 and 2020.
Data presented in Figure 1 reveal that
Germany is the largest human population in
Europe. The arithmetic mean of the population in
this country between 2005 and 2020 is 81,874,408.
France ranks second (65,351,430), followed by the
United Kingdom (63,674,803), Italy (59,585,742),
Spain (46,097,154), Poland (38,049,443), Romania
(20,183,813), Netherlands (16 768 194), Belgium
(11 031 317), Greece (10 938 206), the Czech
Republic (10 472 088), Portugal (10 446 754), etc.
For the remaining 20 countries the arithmetic
mean of populations is less than 10,000,000,
Liechtenstein ranking lowest with an arithmetic
mean of population at 36,634 in 2005–2020.
Then, for illustrative purposes, Figure 2 outlines
data on the number of deaths in 32 European
countries between 2005 and 2018.
Figure 2 shows that the highest arithmetic mean of
the number of deaths in 32 European countries
between 2005 and 2018 is 874 579 in Germany. This
is followed by Italy (600,133), the United Kingdom
(579,492), France (563,377), Spain (395,046), Poland
(384,433). In the remaining 26 European countries,
the arithmetic mean of the number of deaths is less
than 260 000.
The same rankings (Figure 1–2) of the arithmetic
means of populations and deaths in 32 European
countries were recorded in the half of the countries
2222Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
t. LXXIII
nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
under consideration (Germany, the United
Kingdom, Spain, Poland, Romania, the Netherlands,
Greece, Denmark, Slovakia, Slovenia, Estonia,
Cyprus, Luxembourg, Malta, Iceland and
Liechtenstein).
This observation has become a prerequisite for
further research on this issue. For illustrative
purposes the location of raw data, outliers and
extreme values, ranges of non-outliers of analyzed
dependent variables in terms of populations and
deaths in 32 European countries in 2018 were
compared.
Figure 3 shows that four positions of extreme
values are visible in the populations of people in 32
different European countries in 2018. The highest is
Germany with 82,792,351, followed by France
(66,918,941), the United Kingdom (66,273,576) and
Italy (60,483,973). It should be emphasized that the
2233
Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
t. LXXIII
nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
Figure 1
Line chart of the population in 32 European countries between 2005 and 2020
Note: X2 axis — ranking of the human population from highest to lowest arithmetic mean between 2005–2020 in each of 32 European countries.
Source: own study based on data obtained from the website: https://ec.europa.eu/ (10.01.2020)
Figure 2
Line chart of human deaths in 32 European countries between 2005 and 2018
Note: X2 axis — ranking of human deaths from highest to lowest arithmetic mean in 2005–2018 in respective 32 European countries.
Source: see Figure 1.
positions of France and the United Kingdom are
similar in terms of values (distance). The outliers in
32 populations included two positions: Spain
(46,658,447) and Poland (37,976,687), differing
between them in terms of the values recorded. The
distribution of 32 populations due to observed
outliers and extreme values is not normal and our
experience allows us to observe a slight right-
slanted tendency in Figure 3.
Figure 4 shows four identical extremes (taking the
nationality into account) as in the case of the data
compiled in Figure 3. The position of the three
extreme points (Italy — 633,133, the United
Kingdom — 614,313 and France — 609,747), taking
their distances into account, differs between Figures
3 and 4. In Figure 4, they are accumulated, while in
Figure 3, Italy deviates from the others. Germany
has the highest and most distant extreme value with
954,874 deaths. Also, as with outliers, it was observed
that the points: Spain (425,153) and Poland
(414,200) for the number of deaths are close to each
other, whereas in Figure 3 they are distant. The
distribution of the data analyzed (Figure 4) is not
normal and shows a right-slanted tendency greater
than in Figure 3.
Figures 1–4 show the probability of hypotheses that
mortality in each country hovers around the index at
about 1 percentage point described by the function:
Y = Z/P ×100%,
Y — death rate in populations in percentage points;
Z — number of deaths of people;
P — population.
In order to respond to this hypothesis, it was
decided to analyze and evaluate the Y models
described above. The study began by outlining, in
Figure 5, indices of deaths in percentage points in 32
European countries between 2005 and 2018, and
ranking the results from highest to lowest, with 2018
taken as the reference.
Figures compiled in Figure 5 show that the
arithmetic mean of the index is 0.98 out of 448 deaths
in 32 European countries between 2005 and 2018.
Thus, the hypothesis is confirmed. The regularity
2244Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
t. LXXIII
nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
Figure 3
Box plot of populations in 32 different European countries in 2018
Source: see Figure 1.
observed allows us to conclude that in 32 European
countries, each year between 2005 and 2018, around
1 percentage point of the human population dies.
In addition, it was found that the median of the
index concerned is lower than the arithmetic mean
and equals 0.96 percentage points. The minimum
index is 0.58 percentage points in Liechtenstein in
2008 and the maximum, in Bulgaria, is 4.55
percentage points in 2017. The standard deviation
from the arithmetic mean is 0.23 percentage point.
In half of 32 European countries, the index exceeds
1 percentage point, and in the second half it
remains below this value. This means that the half
of the European countries concerned have higher
human mortality per population, whereas in the
second half the situation is the opposite, so it can be
presumed that in that other half of the countries
either people live longer or their societies are
younger.
The final stage of the study was an analysis of the
distribution of calculated death indices in 32
populations between 2005 and 2018. The results are
outlined in Figure 6.
Considering the histogram itself (Figure 5), the
distribution of the data resembles normality. The
Shapiro-Wilk test, on the other hand, clearly
indicates that the data in question are not normal. In
addition, it has been observed that the best-suited
distributor is the one of an extreme nature. The
largest N group of 159 elements includes variables
between 0.77 and 0.97 percentage point. Next, there
are 121 variables between 0.97 and 1.16 percentage
point. Third in the ranking is N equal to 73 variables
between 0.58 and 0.77. The fourth group represents
57 N elements between 1,16 and 1.35 percentage
point. On the other hand, the last ranked group
consists of 38 N elements from 1.35 to 1.55
percentage point.
Summary and conclusions
Studies have shown that in 32 European countries
in question there is a group of six countries which, in
terms of population numbers, have outperformed
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Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
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nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
Figure 4
Box plot of the number of deaths in 32 respective European countries in 2018
Source: see Figure 1.
the other between 2005 and 2020 (Figure 1). These
leaders include Germany (81,874,408), France
(65,351,430), the United Kingdom (63,674,803), Italy
(59,585 742), Spain (46,097,154), and Poland
(38,049,443).
When considering the number of deaths, the same
ranking positions (Figure 1–2) of arithmetic means
of two dependent variables, i.e. populations and
deaths in 32 European countries, were recorded in
half of the countries concerned, namely in Germany,
the United Kingdom, Spain, Poland, Romania, the
Netherlands, Greece, Denmark, Slovakia, Slovenia,
Estonia, Cyprus, Luxembourg, Malta, Iceland and
Liechtenstein.
The arithmetic mean of the death index (Figure 5) in
populations in 32 European countries is 0.98
percentage point. This means that around 1 percentage
point of each population of countries in Europe
under consideration accounts for human deaths
every year.
The distribution of the total number of deaths in
32 European countries between 2005 and 2018
(Figure 6) is not normal and the best suited
distributor is the one of an extreme nature.
The resulting evaluations, revealing persistent
regularities related to the number of deaths in 32
European countries between 2005 and 2020, are
useful for selection of method and for future
forecasting. The forecasts received may be relevant
in terms of planning for future budget revenue and
expenditure, education and other aspects related to
economic security.
The observed regularity related to the persistent
level of the death index in 32 European countries
(Figure 5) between 2005–2018 may prompt one to
conclude that, witnessing the mortality increase
caused by the COVID-19 pandemic in 2020, in
subsequent years the number of deaths will decline,
in proportion to the increases caused by a random
factor which is a persistent infectious disease.
2266Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
t. LXXIII
nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
Figure 5
Linear chart of death indices by percentage points in 32 countries in Europe between 2005 and 2018
Note: axis X2 — ranking death in populations from highest to lowest in 2018)
Source: see Figure 1
The increase in human deaths in 2020 led to
a situation where the broadly understood funeral
industry recorded higher revenues in the analyzed
period than in previous years. The crisis caused by
the infectious disease COVID-19 has generally led to
a decline in consumption which has hit industries
such as tourism, transport and catering the most. The
continuing restrictions and the absence of employees
at workplaces led to a slowdown in the functioning of
the global supply chains. This, in turn, affected the
global stock market and declines in exchange rates,
especially in emerging countries. In Europe, an
increase in financial outlays for health care has been
observed which has directly contributed and will
cause a decline in other entities of budgetary
expenditure.
2277
Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
t. LXXIII
nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
Figure 6
Histogram of the Shapiro-Wilk test of death indexes in percentage points in 32 respective countries in Europe
between 2005 and 2018
Source: see Figure1.
Przypisy/Notes
1
See also: https://forsal.pl/artykuly/1187464,populacja-panstw-ue-dane-demograficzne-eurostat-2018.html (19.01.2021).
2
https://www.pb.pl/25-najpotezniejszych-krajow-na-swiecie-980397, as of 19.01.2021
Bibliografia/References
Literatura/Literature
Kitler, W. (2011). Bezpieczeństwo narodowe RP: podstawowe kategorie, uwarunkowania, system. Warszawa: Akademia Obrony Narodowej.
Kozicki, B., Mitkow, Sz. (2020). Analysis of Human Deaths in Regard to Covid-19 Pandemic in European Countries. European Research
Studies Journal, XXIII (Special Issue 3), 213–227.
Łuniewska, M., Tarczyński, W. (2006). Metody wielowymiarowej analizy porównawczej na rynku kapitałowym. Warszawa: Wydawnictwo
Nukowe PWN.
Manurung, H. (2020). Russia-ASEAN relations during COVID-19 pandemic. https://www.researchgate.net/publication/342499986.
https://doi.org/10.13140/RG.2.2.35835.34087
Satomi, E. et al. (2020). Alocaçao justa de recuros de saúde escassos diante da pandemia de COVID-19 Consideraçoes éticas. Einstein,
Sao Paulo, 18(2), 1–5, https://doi.org/10.31744/einstein_journal/2020AE5775.
Szubrycht, T. (2006). Współczesne aspekty bezpieczeństwa państwa. Zeszyty Naukowe Akademii Marynarki Wojennej, XLVII(4), 167.
Tracz-Dral, J. (2018). Starzenie się ludności w Unii Europejskiej — stan obecny i prognoza. Warszawa: Biuro Analiz, Dokumentacji
i Korespondencji Kancelarii Senatu.
Zhu N., Zhang D., Wang W., Li X., Yang B., Song J. et al. (2020). A Novel Coronavirus from Patients with Pneumonia in China. New
England Journal of Medicine (24.01.2020). https://doi.org/10.1056/NEJMoa2001017
2288Gospodarka Materiałowa i Logistyka
Material Economy and Logistics Journal ISSN 1231-2037
t. LXXIII
nr 2/2021
DOI 10.33226/1231-2037.2021.2.4
Źródła internetowe/Internet sources
https://ec.europa.eu/ (10.01.2020)
https://forsal.pl/artykuly/1187464,populacja-panstw-ue-dane-demograficzne-eurostat-2018.html (19.01.2021)
https://www.pb.pl/25-najpotezniejszych-krajow-na-swiecie-980397 (19.01.2021)
Mjr dr Bartosz Kozicki
Doktor w dziedzinie nauk ekonomicznych, w dyscyplinie na-
uk o zarządzaniu. Pracuje na stanowisku adiunkta na Wy-
dziale Bezpieczeństwa, Logistyki i Zarządzania Wojskowej
Akademii Technicznej. Jego zainteresowania naukowo ba-
dawcze koncentrują się wokół zagadnień ekonomiczno-finan-
sowych przedsiębiorstwa z uwzględnieniem dyscypliny na-
ukowej zarządzanie.
Por. mgr Paweł Jaśkiewicz
Magister filologii angielskiej. Pracuje w Dziale Współpracy
Międzynarodowej w Wojskowej Akademii Technicznej. Jego
zainteresowania naukowe i badawcze koncentrują się wokół
zagadnień związanych z nauczaniem języka angielskiego
i analizą danych.
Mjr dr Bartosz Kozicki
Ph.D. in economic sciences in the field of management. He
has been holding the position of an assistant professor at the
Faculty of Logistics at Military University of Technology.
His research interests include mainly the economic and
financial issues of the enterprise determined by the field of
management.
Por. mgr Paweł Jaśkiewicz
M.A. in English language philology. He works in
International Cooperation Department at Military
University of Technology. His scientific and research
interests include English language teaching and data
analysis.
ZNAJDZIESZ NAS
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