the comparison of european countries on the base human development index
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The Comparison of European Countries on the Base Human Development Index. Zlata Sojková, Zlata Kropková Slovak University of Agriculture, Nitra, Slovak Republic. - PowerPoint PPT PresentationTRANSCRIPT
The Comparison of European Countries on the Base Human Development Index
The Comparison of European Countries on the Base Human Development IndexZlata Sojková, Zlata KropkováSlovak University of Agriculture, Nitra, Slovak RepublicZlata Sojková, Zlata KropkováSlovak University of Agriculture, Nitra, Slovak Republic
The human development index is one of the important indicators of country development level, including another aspect concerning the quality of life unlike gross domestic product.
The countries are categorized to three categories by The United Nations Organization Development Program (UNDP) according to the Human development index: low level of human development to 0.499, middle level from 0.500 to 0.799, and high level from 0.8 to 1.
This classification serves as a comparison of the countries of the world with evident marked disproportions between developed and developing countries.
European countries are classified on the basis of this classification into two groups: the countries with high level of Human Development Index and those of middle level.
The human development index is one of the important indicators of country development level, including another aspect concerning the quality of life unlike gross domestic product.
The countries are categorized to three categories by The United Nations Organization Development Program (UNDP) according to the Human development index: low level of human development to 0.499, middle level from 0.500 to 0.799, and high level from 0.8 to 1.
This classification serves as a comparison of the countries of the world with evident marked disproportions between developed and developing countries.
European countries are classified on the basis of this classification into two groups: the countries with high level of Human Development Index and those of middle level.
The aims of the analyses are:The aims of the analyses are:
to realize detailed classification of European countries to the groups on the basis of Education Index, Gross Domestic Product Index, and Life Expectancy Index;
to characterize and compare groups of the countries from the point of view of partial indicators creating the Human Development Index;
to specify disparities between countries from the point of view of the partial components of the Human Development Index;
to compare the results of the grouping according to the multidimensional classification with the results of the ranking based on the Human Development Index.
to realize detailed classification of European countries to the groups on the basis of Education Index, Gross Domestic Product Index, and Life Expectancy Index;
to characterize and compare groups of the countries from the point of view of partial indicators creating the Human Development Index;
to specify disparities between countries from the point of view of the partial components of the Human Development Index;
to compare the results of the grouping according to the multidimensional classification with the results of the ranking based on the Human Development Index.
The comparative analysis is realized on the basis of the data from the World Bank in 2002. The following information of 37 European countries was excerpted from these data:
Human Development Index (HDi)Life Expectancy Index (iLE)Education Index (iED)Gross Domestic Product Index(iGDP)
The applied methodological means of multidimensional classification of such countries from the point of view of three components of the HDI is the cluster analysis and the discriminant analysis.
The comparative analysis is realized on the basis of the data from the World Bank in 2002. The following information of 37 European countries was excerpted from these data:
Human Development Index (HDi)Life Expectancy Index (iLE)Education Index (iED)Gross Domestic Product Index(iGDP)
The applied methodological means of multidimensional classification of such countries from the point of view of three components of the HDI is the cluster analysis and the discriminant analysis.
The multidimensional classification of 37 European countries is realized according to the three above mentioned components of the Human Development Index simultaneously:
Gross Domestic Product Index (x1), Life Expectancy Index (x2) and Education Index (x3).
The multidimensional classification of 37 European countries is realized according to the three above mentioned components of the Human Development Index simultaneously:
Gross Domestic Product Index (x1), Life Expectancy Index (x2) and Education Index (x3).
Comparison of the European countries from the point of view of the Human Development
Index in 2002
Comparison of the European countries from the point of view of the Human Development
Index in 2002Country Abb. Rank Live Educ HDP iLE iED iHDP HDI Klast. Dif
2002 Exp 2002Ran
k *
Norway NOR 1 78.9 98 36600 0.9 0.99 0.99 0.956 1 1
Sweden SWE 2 80 114 26050 0.92 0.99 0.93 0.946 1 19Belgium BEL 6 78.7 111 27570 0.9 0.99 0.94 0.942 1 7Netherlands NLD 5 78.3 99 29100 0.89 0.99 0.95 0.942 1 6Island IS 7 79.7 90 29750 0.91 0.96 0.95 0.941 1 1Switzerland CH 11 79.1 88 30010 0.9 0.95 0.95 0.936 1 -4Ireland IRL 10 76.9 90 36360 0.86 0.96 0.98 0.936 1 -7United Kingdom UK 12 78.1 113 26150 0.88 0.99 0.93 0.936 1 8Finland FIN 13 77.9 106 26190 0.88 0.99 0.93 0.935 1 6Austria AU 14 78.5 91 29220 0.89 0.96 0.95 0.934 1 -4Luxemburg LUX 15 78.3 75 61190 0.89 0.91 1 0.933 2 -14Germany DEU 17 76.6 96 30940 0.86 0.98 0.96 0.932 1 -12France FR 16 78.9 91 26920 0.9 0.96 0.93 0.932 1 0Denmark DK 19 78.2 88 27100 0.89 0.95 0.94 0.925 1 -5Spain ESP 20 79.2 92 21460 0.9 0.97 0.9 0.922 1 5Italy ITA 21 78.7 82 26430 0.89 0.93 0.93 0.92 2 -3Greece GRE 24 78.2 86 18720 0.89 0.95 0.87 0.902 1 5Portugal PRT 26 76.1 93 18280 0.85 0.97 0.87 0.897 1 6Slovenia SVN 27 76.2 90 18540 0.85 0.96 0.87 0.895 1 3Cyprus CY 30 78.2 74 18360 0.89 0.89 0.87 0.883 2 1Malta MAL 31 78.3 77 17640 0.89 0.87 0.86 0.875 2 3Czech Republic CZ 32 75.3 78 15780 0.84 0.92 0.84 0.868 3 7Estonia EST 36 71.6 96 12260 0.78 0.98 0.8 0.853 4 10Poland POL 37 73.8 90 10560 0.81 0.96 0.78 0.85 4 13Hungary HUN 38 71.7 86 13400 0.78 0.95 0.82 0.848 4 3Lithuania LIT 41 72.5 90 10320 0.79 0.96 0.77 0.842 4 10Slovak Republic SK 42 73.6 74 12840 0.81 0.91 0.81 0.842 3 1Croatia HR 48 74.1 73 10240 0.82 0.9 0.77 0.83 3 4Latvia LVA 50 70.9 87 9210 0.76 0.95 0.75 0.823 4 6Bulgaria BUL 56 70.9 76 7130 0.77 0.91 0.71 0.796 5 10Russia RUS 56 66.7 88 8230 0.69 0.95 0.74 0.795 6 3Macedonia MK 60 73.5 70 6470 0.81 0.87 0.7 0.793 5 15Belarus BY 62 69.9 88 5520 0.75 0.95 0.67 0.79 6 24Albania AL 65 73.6 69 4830 0.81 0.89 0.65 0.781 5 31Bosnia a Herzegovina BiH 66 74 64 5970 0.82 0.84 0.68 0.781 5 15Romania RO 69 70.5 68 6560 0.76 0.88 0.7 0.778 5 5Ukraine UA 70 69.5 84 4870 0.74 0.94 0.65 0.777 6 25
2002
Source: HDR 2004 and authors’ calculations*)
Multidimensional classification of European countries in 2002
Multidimensional classification of European countries in 2002
The multidimensional classification of countries is realized on the basis of three partial indices (iLE, iED, iGDP). The countries are grouped to mutual similar six cluster from according to the three indices mentioned above, so that the classified countries were the most similar and there were the significant differences between the clusters. The Further Neighbour Method is applied in the procedure of agglomeration. The procedure of classification is presented in dendogram Graph 1. The results of the grouping of European countries are six clusters - groups. The efficiency of the classification was verified by discriminant analysis and it was confirmed. The rearrangement within the clusters was not necessary.
The multidimensional classification of countries is realized on the basis of three partial indices (iLE, iED, iGDP). The countries are grouped to mutual similar six cluster from according to the three indices mentioned above, so that the classified countries were the most similar and there were the significant differences between the clusters. The Further Neighbour Method is applied in the procedure of agglomeration. The procedure of classification is presented in dendogram Graph 1. The results of the grouping of European countries are six clusters - groups. The efficiency of the classification was verified by discriminant analysis and it was confirmed. The rearrangement within the clusters was not necessary.
Dendrogram
Furthest Neighbor Method,Squared Euclidean
Dis
tan
ce
0
0,5
1
1,5
2
2,5
3
3,5
4
NO
R
SW
E
NL
DB
EL IS
IRL
CH
UK
FIN AU
LU
X
FR
A
DK
DE
U
ES
P
ITA
GR
E
PR
TS
VN
CY
MA
LC
Z
ES
TP
OL
HU
NL
ITSK
HR
LVA
BU
L
RU
S
MK
BY
AL
BB
iH
RO
UA
Source: HDR 2004 and authors’ calculations*)
Graph 1 Clustering of countries on the basis of partial indices – dendogram
Graph 1 Clustering of countries on the basis of partial indices – dendogram
Cluster 1 (17): Norway, Sweden, Netherlands, Belgium, Island, Ireland, Switzerland, United Kingdom, Finland, Austria, France, Denmark, Germany, Spain, Greece, Portugal, Slovenia
Cluster 2 (4): Luxemburg, Italy, Cyprus, MaltaCluster 3 (3): Czech Republic, Slovak Republic, CroatiaCluster 4 (5): Estonia, Poland, Hungary, Latvia,
LithuaniaCluster 5 (5): Bulgaria, Albania, Macedonia, Romania,
Bosnia and HerzegovinaCluster 6 (3): Russia, Belarus, Ukraine
Cluster 1 (17): Norway, Sweden, Netherlands, Belgium, Island, Ireland, Switzerland, United Kingdom, Finland, Austria, France, Denmark, Germany, Spain, Greece, Portugal, Slovenia
Cluster 2 (4): Luxemburg, Italy, Cyprus, MaltaCluster 3 (3): Czech Republic, Slovak Republic, CroatiaCluster 4 (5): Estonia, Poland, Hungary, Latvia,
LithuaniaCluster 5 (5): Bulgaria, Albania, Macedonia, Romania,
Bosnia and HerzegovinaCluster 6 (3): Russia, Belarus, Ukraine
The following clusters of European countries were created by
multidimensional classification:
The following clusters of European countries were created by
multidimensional classification:
Geographical clustering of multidimensional classification of
European countries in 2002
Geographical clustering of multidimensional classification of
European countries in 2002
Source: HDR 2004 and authors’ calculations*)
Comparison of the first and the second cluster
on the basis of partial indices Comparison of the first and the second cluster
on the basis of partial indices
0,6
0,8
1iEDU
iLEiGDP
1: NOR NLD BEL UK FIN SWE IS FRA CH DEU AU ESP GRE IRL DK PRT SVN2: LUX ITA CY MAL
0,6
0,8
1iEDU
iLEiGDP
2: LUX ITA CY MAL 3: CZ SK HR
Comparison of the second and the third cluster on the basis of partial indices
Comparison of the third and the fourth cluster
on the basis of partial indices Comparison of the third and the fourth cluster
on the basis of partial indices
0,6
0,8
1iEDU
iLEiGDP
3: CZ SK HR 4: EST POL LIT HUN LVA
Comparison of partial indices of Human Development Index in the selected countries in
2002
Comparison of partial indices of Human Development Index in the selected countries in
2002
0,6
0,8
1
iLE
iED iHDP
SK EST SVN
Relationship between GDP index and Life Expectancy index and GDP index and
Education index in 2002
Relationship between GDP index and Life Expectancy index and GDP index and
Education index in 2002
Cluster Scatterplot
Furthest Neighbor Method,Squared Euclidean
IHDP
ILE
Cluster123456Centroids
0,65 0,75 0,85 0,95 1,050,69
0,73
0,77
0,81
0,85
0,89
0,93
0,97
Cluster ScatterplotFurthest Neighbor Method,Squared Euclidean
i HDP
iED
U
Cluster123456Centroids
0,6 0,7 0,8 0,9 10,8
0,84
0,88
0,92
0,96
1
It is evident in the graphic picture that the real Gross Domestic Product level expressed in GDP Index is impacted on Life expectancy Index (clusters are charted on the diagonal). On the other hand the education level expressed in the Education Index almost does not correspond with GDP Index. The clusters of the European countries are separated and are not concentrated on the diagonal.
It is evident in the graphic picture that the real Gross Domestic Product level expressed in GDP Index is impacted on Life expectancy Index (clusters are charted on the diagonal). On the other hand the education level expressed in the Education Index almost does not correspond with GDP Index. The clusters of the European countries are separated and are not concentrated on the diagonal.
Source: HDR 2004 and authors’ calculations*) Source: HDR 2004 and authors’ calculations*)
It could be submitted, that a real Gross Domestic Product is not significantly determinate for Education level.
This fact is typical for Estonia, Latvia, Lithuania, and the other countries, too. The relatively higher Education Index is attained in spite of low real Gross Domestic
Product.
It could be submitted, that a real Gross Domestic Product is not significantly determinate for Education level.
This fact is typical for Estonia, Latvia, Lithuania, and the other countries, too. The relatively higher Education Index is attained in spite of low real Gross Domestic
Product.
CONCLUSIONCONCLUSION
The reason of the application of the multidimensional classification is the fact, that the disparities in partial indices of three indicators composing HDI are averaged by the Human Development Index.
To simplify: Two countries close or identical from the point of view of the total HDI can be less or more evidently different from the point of view of partial indices. From the point of view of the components, the disproportions between countries are covered by the Human Development Index.
Regional disparities within European countries are and will be the next problem of globalization. They might be observed not only in the original European Union, but also particularly in the new Member States.
The reason of the application of the multidimensional classification is the fact, that the disparities in partial indices of three indicators composing HDI are averaged by the Human Development Index.
To simplify: Two countries close or identical from the point of view of the total HDI can be less or more evidently different from the point of view of partial indices. From the point of view of the components, the disproportions between countries are covered by the Human Development Index.
Regional disparities within European countries are and will be the next problem of globalization. They might be observed not only in the original European Union, but also particularly in the new Member States.
The investigation of convergence and divergence tendencies and the disparities on the NUTS2 and NUT3 level is just the topic high on the list of our scientific research.
The investigation of convergence and divergence tendencies and the disparities on the NUTS2 and NUT3 level is just the topic high on the list of our scientific research.