This document analyzes and compares European countries based on their Human Development Index (HDI) scores in 2002. It groups the 37 European countries studied into six clusters based on multivariate analysis of three HDI components: Gross Domestic Product Index, Life Expectancy Index, and Education Index. The clusters show some geographical patterns. Comparisons of clusters reveal differences in levels of the three indices. Overall HDI scores can obscure differences between countries revealed by examining individual index components.
This document analyzes and compares European countries based on their Human Development Index (HDI) scores in 2002. It groups the 37 European countries studied into six clusters based on multivariate analysis of three HDI components: Gross Domestic Product Index, Life Expectancy Index, and Education Index. The clusters show some geographical clustering. Comparisons of clusters based on these three indices reveal disparities between countries in terms of economic development and quality of life.
The education system in Sweden is decentralized and provides equal access to education for all students. The national government sets educational goals and frameworks, while municipalities organize schools and allocate resources. Schools have autonomy in how they achieve national standards. Recent reforms have focused on increasing accountability, evaluations, and improving teacher quality.
Full report best european countries for business 2018mResearcher
The European Chamber ranks European countries based on their business environment. The EuCham score, used for the
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Social Progress Index 2014 Executive Summarysocprog
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The document compares various metrics between countries including Olympic medals, GDP, GNI per capita, income inequality, levels of democracy, and military spending. It provides data on these metrics for countries like the US, Germany, and others. It also lists sources for international development, economic, and democracy indicators.
This document analyzes and compares European countries based on their Human Development Index (HDI) scores in 2002. It groups the 37 European countries studied into six clusters based on multivariate analysis of three HDI components: Gross Domestic Product Index, Life Expectancy Index, and Education Index. The clusters show some geographical patterns. Comparisons of clusters reveal differences in levels of the three indices. Overall HDI scores can obscure differences between countries revealed by examining individual index components.
This document analyzes and compares European countries based on their Human Development Index (HDI) scores in 2002. It groups the 37 European countries studied into six clusters based on multivariate analysis of three HDI components: Gross Domestic Product Index, Life Expectancy Index, and Education Index. The clusters show some geographical clustering. Comparisons of clusters based on these three indices reveal disparities between countries in terms of economic development and quality of life.
The education system in Sweden is decentralized and provides equal access to education for all students. The national government sets educational goals and frameworks, while municipalities organize schools and allocate resources. Schools have autonomy in how they achieve national standards. Recent reforms have focused on increasing accountability, evaluations, and improving teacher quality.
Full report best european countries for business 2018mResearcher
The European Chamber ranks European countries based on their business environment. The EuCham score, used for the
ranking, originates from the average of the World Bank’s Distance To Frontier score (DTF) and Transparency International’s Corruption Perception Index (CPI).
Social Progress Index 2014 Executive Summarysocprog
The document provides an executive summary of the Social Progress Index 2014. It discusses the need to measure social progress beyond just economic metrics like GDP. The Social Progress Index aims to fill this need by measuring social and environmental performance across three dimensions - basic human needs, foundations of wellbeing, and opportunity. The top scoring countries are New Zealand, Switzerland, and Iceland. While higher GDP countries generally score higher, GDP alone does not guarantee social progress. Social progress improves rapidly with economic growth at low incomes but the relationship levels off at higher incomes.
The document compares various metrics between countries including Olympic medals, GDP, GNI per capita, income inequality, levels of democracy, and military spending. It provides data on these metrics for countries like the US, Germany, and others. It also lists sources for international development, economic, and democracy indicators.
The document summarizes unemployment rates across regions in the EU in 2013. It finds that unemployment varied widely, from a low of 2.6% in Oberbayern, Germany to a high of 36.3% in Andalucía, Spain. Youth unemployment was even more varied, ranging from 4.4% in Oberbayern and Tübingen, Germany to 72.7% in Ceuta, Spain. Long-term unemployment, defined as being out of work for over a year, was lowest in Swedish regions at 12.4-17.5% and highest in French overseas territories at 71.0-79.5%.
The survey found that global awareness of professional coaching has increased since 2010, especially in Europe and the Big Four countries of the US, Canada, UK, and Australia. 58% of respondents across 25 countries were aware of coaching. Awareness was higher among younger age groups and in the Big Four countries. While awareness has increased, participation in coaching has not increased at the same rate. 17% of respondents had participated in coaching. The main reasons people did not consider coaching were that they did not need it or could not afford it. Younger people were more open to participating in coaching than older age groups.
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- Countries have different priorities for their welfare systems such as employment, equality, poverty reduction, health, education, or old age.
- Performance is measured based on the capacity to fulfill five basic welfare state missions: poverty alleviation, inequality reduction, health, employment, and education.
- Countries' performances were evaluated using two techniques, with results showing some countries performed better than others on composite indicators.
- Major challenges threatening welfare state viability include demographic aging, globalization, and financial/budget crises. Reforms have moved
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Authors:
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Anne Annink, Public Administration
Fabian Dekker, Sociology
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The document summarizes unemployment rates across regions in the EU in 2013. It finds that unemployment varied widely, from a low of 2.6% in Oberbayern, Germany to a high of 36.3% in Andalucía, Spain. Youth unemployment was even more varied, ranging from 4.4% in Oberbayern and Tübingen, Germany to 72.7% in Ceuta, Spain. Long-term unemployment, defined as being out of work for over a year, was lowest in Swedish regions at 12.4-17.5% and highest in French overseas territories at 71.0-79.5%.
The survey found that global awareness of professional coaching has increased since 2010, especially in Europe and the Big Four countries of the US, Canada, UK, and Australia. 58% of respondents across 25 countries were aware of coaching. Awareness was higher among younger age groups and in the Big Four countries. While awareness has increased, participation in coaching has not increased at the same rate. 17% of respondents had participated in coaching. The main reasons people did not consider coaching were that they did not need it or could not afford it. Younger people were more open to participating in coaching than older age groups.
This document discusses the performance and challenges facing the European welfare state. It provides an overview of recent studies that evaluate welfare state performance across 28 EU countries. Key findings include:
- Countries have different priorities for their welfare systems such as employment, equality, poverty reduction, health, education, or old age.
- Performance is measured based on the capacity to fulfill five basic welfare state missions: poverty alleviation, inequality reduction, health, employment, and education.
- Countries' performances were evaluated using two techniques, with results showing some countries performed better than others on composite indicators.
- Major challenges threatening welfare state viability include demographic aging, globalization, and financial/budget crises. Reforms have moved
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This document discusses a framework for linking policies to living standards through inclusive growth. It proposes that the framework should provide a clear link between dimensions of welfare (like income, health, education) and policies, identify transmission channels, and make policy tradeoffs explicit while being adaptable. The framework models welfare as outcomes of a production function influenced by policies. The document then examines how specific policies influence key outcomes like income generation, health, and income distribution for different countries.
This document provides an introduction to a publication summarizing the results of a survey of practices for estimating non-observed economic activities (NOE) in national accounts across 43 countries. The survey aimed to update previous inventories, increase country coverage, and allow for comparison of estimation methods and difficulties. Countries provided estimates of NOE's size in GDP and details on estimation methods. The goals were to present practices at different development stages, enable comparison of approaches, and serve as a reference for comprehensive GDP estimates.
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1. The Comparison of European
Countries on the Base Human
Development Index
Zlata Sojková, Zlata Kropková
Slovak University of Agriculture, Nitra, Slovak Republic
2. 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.
3. 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.
4. 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.
5. 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).
6. Comparison of the European countries from
the point of view of the Human Development Index
in 2002
Country Abb. Rank Live Educ HDP iLE iED iHDP HDI Klast. Dif
2002 Exp 2002
Ran
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 19
Belgium BEL 6 78.7 111 27570 0.9 0.99 0.94 0.942 1 7
Netherlands NLD 5 78.3 99 29100 0.89 0.99 0.95 0.942 1 6
Island IS 7 79.7 90 29750 0.91 0.96 0.95 0.941 1 1
Switzerland CH 11 79.1 88 30010 0.9 0.95 0.95 0.936 1 -4
Ireland IRL 10 76.9 90 36360 0.86 0.96 0.98 0.936 1 -7
United Kingdom UK 12 78.1 113 26150 0.88 0.99 0.93 0.936 1 8
Finland FIN 13 77.9 106 26190 0.88 0.99 0.93 0.935 1 6
Austria AU 14 78.5 91 29220 0.89 0.96 0.95 0.934 1 -4
Luxemburg LUX 15 78.3 75 61190 0.89 0.91 1 0.933 2 -14
Germany DEU 17 76.6 96 30940 0.86 0.98 0.96 0.932 1 -12
France FR 16 78.9 91 26920 0.9 0.96 0.93 0.932 1 0
Denmark DK 19 78.2 88 27100 0.89 0.95 0.94 0.925 1 -5
Spain ESP 20 79.2 92 21460 0.9 0.97 0.9 0.922 1 5
Italy ITA 21 78.7 82 26430 0.89 0.93 0.93 0.92 2 -3
Greece GRE 24 78.2 86 18720 0.89 0.95 0.87 0.902 1 5
Portugal PRT 26 76.1 93 18280 0.85 0.97 0.87 0.897 1 6
Slovenia SVN 27 76.2 90 18540 0.85 0.96 0.87 0.895 1 3
Cyprus CY 30 78.2 74 18360 0.89 0.89 0.87 0.883 2 1
Malta MAL 31 78.3 77 17640 0.89 0.87 0.86 0.875 2 3
Czech Republic CZ 32 75.3 78 15780 0.84 0.92 0.84 0.868 3 7
Estonia EST 36 71.6 96 12260 0.78 0.98 0.8 0.853 4 10
Poland POL 37 73.8 90 10560 0.81 0.96 0.78 0.85 4 13
Hungary HUN 38 71.7 86 13400 0.78 0.95 0.82 0.848 4 3
Lithuania LIT 41 72.5 90 10320 0.79 0.96 0.77 0.842 4 10
Slovak Republic SK 42 73.6 74 12840 0.81 0.91 0.81 0.842 3 1
Croatia HR 48 74.1 73 10240 0.82 0.9 0.77 0.83 3 4
Latvia LVA 50 70.9 87 9210 0.76 0.95 0.75 0.823 4 6
Bulgaria BUL 56 70.9 76 7130 0.77 0.91 0.71 0.796 5 10
Russia RUS 56 66.7 88 8230 0.69 0.95 0.74 0.795 6 3
Macedonia MK 60 73.5 70 6470 0.81 0.87 0.7 0.793 5 15
Belarus BY 62 69.9 88 5520 0.75 0.95 0.67 0.79 6 24
Albania AL 65 73.6 69 4830 0.81 0.89 0.65 0.781 5 31
Bosnia a Herzegovina BiH 66 74 64 5970 0.82 0.84 0.68 0.781 5 15
Romania RO 69 70.5 68 6560 0.76 0.88 0.7 0.778 5 5
Ukraine UA 70 69.5 84 4870 0.74 0.94 0.65 0.777 6 25
2002
Source: HDR 2004 and authors’ calculations*)
7. 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.
9. 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, Malta
Cluster 3 (3): Czech Republic, Slovak Republic, Croatia
Cluster 4 (5): Estonia, Poland, Hungary, Latvia, Lithuania
Cluster 5 (5): Bulgaria, Albania, Macedonia, Romania,
Bosnia and Herzegovina
Cluster 6 (3): Russia, Belarus, Ukraine
The following clusters of European countries
were created by multidimensional
classification:
10. Geographical clustering of multidimensional
classification of European countries in 2002
Source: HDR 2004 and authors’ calculations*)
11.
12. Comparison of the first and the second cluster
on the basis of partial indices
0,6
0,8
1
iEDU
iLEiGDP
1: NOR NLD BEL UK FIN SWE IS FRA CH DEU AU ESP GREIRL DK PRT SVN
2: LUX ITA CY MAL
14. Comparison of the third and the fourth cluster on
the basis of partial indices
0,6
0,8
1
iEDU
iLEiGDP
3: CZ SK HR 4: EST POL LIT HUN LVA
15. Comparison of partial indices of Human
Development Index in the selected countries in
2002
0,6
0,8
1
iLE
iEDiHDP
SK EST SVN
16. 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
Cluster
1
2
3
4
5
6
Centroids
0,65 0,75 0,85 0,95 1,05
0,69
0,73
0,77
0,81
0,85
0,89
0,93
0,97
Cluster Scatterplot
Furthest Neighbor Method,Squared Euclidean
i HDP
iEDU
Cluster
1
2
3
4
5
6
Centroids
0,6 0,7 0,8 0,9 1
0,8
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.
Source: HDR 2004 and authors’ calculations*) Source: HDR 2004 and authors’ calculations*)
17. 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.
18. CONCLUSION
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.
19. 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.