Transcript Income inequality in EU member countries

Improving the Quality of Public Services
A Multinational Conference on Public Management
June 28-29, 2011, Moscow
The study of income and living conditions of
the Slovakia’s households and its
macroeconomic aspects
Ladislav Kabat
professor
Faculty of Economics and Business
The Pan European university
Bratislava, Slovakia
The study of income and living conditions of the
Slovakia’s households and its macroeconomic
aspects
• This paper follows two key goals
– To present the core results of the EU SILC project
2005-2009 with orientation on the socially
vulnerable groups of population
– To show the core macroeconomic indicators (GDP
pc, GDP annual growth) within V4 countries in
relation to level and size of the at-risk-of-poverty
population
Some frequently presented data (in 1996)
• 800 million
• 1 852 kcal pc per day
• 1,2 billion
• 1$ pc a day
GOALS
for 2015
50% less
Some frequently presented data (in 2010)
Where the undernourished people live?
Ranking
Country
1
2
3
4
5
6
7
8
9
Congo Dem Rep
Eritrea
Burundi
Haiti
Sierra Leone
Zambia
Angola
Ethiopia
Central African Rep
10
Rwanda
% of population
undernourished
75
66
63
58
46
45
44
44
41
40
Poverty and social exclusion is not only
the developing countries phenomena
Poverty across EU27 in 2007
Data for Romania and
Bulgaria estimated
according EU SILC
methodology
The alarming data on EU poverty and
social exclusion continue with
economic recession
• 2008 - 17 % citizens were at-risk-of-poverty
– Over 80 million
– 2% more than in 2007
– Problematic situation in Latvia, Romania,
Lithuania – low income + high income inequality
• 2010 – expected results even worse
Terminology, data, indicators of the
EU SILC project
•
•
•
•
Household as a unit of study
Household income – sum of partial incomes
Household size – all members of household
EU SILC methodology approach
– Equivalized size of household
– Equivalized income per member of household
– New indicators on the at-risk-of-poverty
– List of mandatory compiled data (variables)
• Also material deprivation is studied
Calculation of the equivalized income
per person /family member/
Step 1
Step 2
Step 3
Step 4
Number of all
members of
household
Calculation of the
equivalized size of
household (ESH)
Disposable
household income
(DHI)
Calculation of the
equivalized
household income
EI per person
A=number of adults
B=number of
children
ESH=1+(A-1)*0,5
+B*0,3
DHI=Sum of all
incomes
EI=DHI/ESH
Example for family of 2 adults and 3 children with total income of 1200 euro
A=2
B=3
Income pp 240 euro
ESH=1 + 0,5 + 3*0,3
DHI=1200
= 2,4
EI=1200/2,4 = 500
Cumulative growth in GDP over
2005-2009
Economic growth in EU and V4
GDP growth - cumul
35
30
25
20
15
EU
10
Czech r.
5
Hungary
Poland
0
2005
2006
2007
Year
2008
2009
Slovakia
Slovenia
Estimation of the at-risk-of-poverty
population
The core parameters are
studied:
Median and 0,6*Median
at-risk-of
poverty
population
To analyze the role of social net
Three subgroups of the surveyed households
for Slovakia studied:
1. At-risk-of-poverty population before all social
transfers
2. At-risk-of-poverty population before social
transfers except the pension payments
(survivors and old-age benefits)
3. At-risk-of-poverty population, when the
disposable income of households is
considered
EU SILC project results for 2005-2009
with regional breakdown
EU SILC project results for 2005-2009
Bratislava vs regions
The core statistical findings on income
• Permanent growth in average income for
Slovakia
• Permanent growth in income differentiation
between capital city and rest of Slovakia
– Median value 30% higher than country's level
– Median value 45% higher than some regional levels
• Growing inequality between top and bottom
income deciles
Results with social consequences
• 11% of Slovak citizens - more than 595,000 people,
were in 2009 at-risk-of-poverty after social transfers
• In terms of gender - women are relatively more at-riskof poverty status (11.8%) than men (10.1%)
• The most vulnerable groups are children and
youngsters till 17 years of age with 16,8 % of them atrisk-of-poverty, followed by women over 65
• The long term unemployment
The unemployed population is highly
vulnerable
Material deprivation rate
Is proportion of population with enforced lack of at
least three (or four) out of following items, which
the household cannot afford:
 to face unexpected expenses,
 to go on one week annual holiday away from home,
 to pay for arrears (mortgage or rent, utility bills or hire
purchase installments),
 to eat meal with meat, chicken or fish every second
day,
 to keep home adequately warm, or could not afford
(even if household wanted to): a washing machine, a
color TV, a telephone and a personal car.
Material deprivation data
Table 4 Material deprivation rate
Number of missing
items
3
4
2005 2006 2007 2008 2009
Proportion of households in %
43.2 35.7 30.2 27.8 24.5
22.5 18.3 13.7 11.8 11.1
The special findings on social situation
• Mostly disadvantaged social groups are
influenced
• Gypsy population
• Low education labor force
• Handicapped citizens
• The material deprivation is felt much stronger,
than the income poverty indicators show.
To solve the trap of poverty
• requires the long-term successful economic
progress
• active involvement and support from
government and regional authorities,
• solution of the long lasting unemployment,
• attention to the low educated labor force
Support to social net over period of
economic boom
% of GDP used fo social net
GDP and social net allocations in EU and V4 countries
28
27
26
25
24
23
22
21
20
19
18
17
16
15
EU(27)
Czech Republic
Hungary
Poland
Slovenia
Slovakia
2000
2001 2002
2003 2004 2005
Year
2006 2007
2008
Slovakia achieved the highest economic
growth among the EU27 over 2005 and 2009
Graph 4
GDP dynamics and selected social indicators
40
% change
35
GDP Grow th cumul
30
Under PL - w ith all transfers
25
Under PL(excl pensions)
20
Under PL BST (of all)
15
10
2005
2006
2007
2008
Year
2009
2010
At-risk-of population in Visegrad
countries over 2005-2009
Table 7 At risk of poverty population in Visegrad
countries
2005 2006 2007 2008 2009
EU
16,4
16,5
16,4
16,4
16,3
Czech rep
10,4
9,9
9,6
9
8,6
Hungary
13,5
15,9
12,2
12,4
12,4
Poland
20,5
19,1
17,3
16,9
17,1
Slovakia
13,3
11,6
10,5
10,9
11
Slovenia
12,2
11,6
11,5
12,3
11,3
Statistics does not solve the problem
The calculation of the social income deficit is needed
The presented statistical findings are
not the final solution
To improve:
• definition of poverty should be formulated as a
multidimensional – income and material deprivation
should be covered comprehensively
• methodology of estimation the share of the under
poverty line population should be checked against the
other information sources
• Calculation of the minimum social deficit needed to
upgrade the socially excluded citizens should be
presented to public (government, NGOs, universities)
Final conclusions
 The high share of socially vulnerable population has not
changed significantly during the period of strong economic
growth in Slovakia
 Similar development has been found also in other Visegrad
countries
 We did not prove the expected significant impact of economic
growth on social position of population in these countries as
declared by government and leading political parties
 These findings should be studied in more details, taking into
account longer time series on relevant statistical data as well as
the broader set of explanatory variables.