Income Inequality in Greece:EU SILC Evidence

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Income inequality in Greece: EU-SILC evidence

K. Chrissis and A. Livada

Athens University of Economics and Business

Technical Report No 271

ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS

DEPARTMENT OF STATISTICS

DECEMBER 2013



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Abstract

The purpose of this paper is to examine income inequality in Greece from EU-SILC

(European Union Survey on Income and Living Conditions) micro data. The time

period of the analysis is from the year 2002 to the year 2010.

The empirical findings indicate that aggregate income inequality in Greece is in

higher level than the average of both European Union and Euro area.

The inequality indices are decomposed by population sub-groups and by income

sources. The empirical results indicate that the main contribution to total income

inequality is the ‘within’ inequality. The pattern is different only for the categorical

variable of education. The education level attained imposes effect on the distribution

of income. The decomposition by income components allows having a clear idea on

how each component contributes to the total inequality. The empirical findings

indicate that the main contribution to the total income inequality stems from salaries

and wages, income from the self employed, and to a lesser extent from pensions and

property income.

The analysis for the examination of the redistributive effects of social transfers andtaxes constitutes of the typical comparison of the main inequality measures (axiomatic

approach) and of second order stochastic dominance. The empirical findings suggest

that the social transfers smoothens inequalities. The same applies for taxes. It is not

clear, though, whether the very lower income class (the lowest two deciles) benefits

from the tax system. Finally, the incorporation of imputed rent (taken into account the

measurement difficulties) reduces aggregate income inequality.



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1. Introduction

The empirical study of economic inequality utilizes several data sources

either on aggregate or on micro level. The European Union has set up a

survey for collecting household data on income, poverty, social exclusion and

living conditions, known as European Union Survey on Income and Living

Conditions (EU SILC). This survey was launched in 2003 for Greece and can

be used for the estimation of income distribution.

More specifically, the European Union Survey on Income and Living

Conditions provides two types of annual data:

- Cross sectional data with variables on income, poverty, social

exclusion and other living conditions

- Longitudinal data for changes over time in individual level.

The data are produced on annual basis and the reference population is all

private households and their current members residing in the territory of the

Member State at the time of data collection. The year of the survey contains

data for the previous year; thus survey for 2011 illustrates information for the

year 20101.

EU SILC data contain information for various components of income.

Therefore, several variables that approach the concept of income have been

calculated and have been utilized to estimate the distribution of income in the

whole population. Seventeen (17) variables were compiled. The most

appropriate - according to the topic - have been used for income inequality

analysis [for details see Chrissis (2013)].

These variables describe the concept of income on household level. The size

of the household and the age of its members are important factors, therefore

the use of an equivalence scale is appropriate. In this study the "OECD-

modified scale" is utilized. This scale, first proposed by Haagenars et al.

(1994), assigns a value of 1 to the household head, of 0.5 to the second and

each subsequent person aged 14 and over and of 0.3 to each child aged under 14.

The time period of the analysis is from the year 2002 to the year 2010.

1 For more analytical technical details of the survey the interested user could visit the Eurostat’s

website.



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The structure of the paper is the following. Section 2 includes the empirical

findings for income inequality measurement. Section 3 and section 4 describe

the decomposition of income inequality by sub -groups and the decomposition

of income inequality by income sources respectively. Section 5 refers to the

redistributive effects of social transfers and taxes whereas section 6 describes

the effects of the inclusion of imputed rents in the income components.

Finally, section 7 concludes.

2. Measurement of income inequality

2.1. Statistical specification for EU-SILC data

Four inequality indices (with various parameters) are compiled for the EU

SILC micro data. The formulae for the indices are:

Gini index

(1)

Where and and

(3.29)

Generalized entropy index

(2)

Atkinson index

(3)



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Coefficient of Variation

(4)

The notations are

Symbol Indication

y Variable of interest

i Observation number

Value of the variable of interest for observation i

hw Sampling weight

Sampling weight for observation i

hs Size variable

Size of observation i

hg Group variable

Group of observation i

n Sample size

The estimations of aggregate inequality measures from EU SILC micro data

were conducted using software STATA/SE 11.0 (module DASP ver. 2.1).

2.2. Empirical results

The variable used for the estimation of income distribution is the ‘Total net

household income’. This variable includes net income on household level

taking into account, also, components of personal net income; it is noted that

we do not take into account the negative values in the variable net cash

benefits or losses from self -employment (including royalties). It has been

adjusted for the size of household and the age of the members of household

with the OECD-modified scale.

The indices2 that indicate the gap between the income shares of certain

portions of population are S80/S20 and S90/S10, which is simply the ratio

2 For inequality measurement from different data sources see Chrissis and Livada (2013).



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between the income share of upper and lower income classes. There has been

a small decrease in both indices; nevertheless the trend is not stable for the

whole period. The decrease is more obvious in the year 2009 especially for

S90/S10. Both ratios indicate increase for the year 2010. This implies that the

recession, which is more apparent from 2009, seems to affect the distribution

of income with ambiguous results.

The behavior of the aggregate inequality indices (GINI, Atkinson (0,5),

Atkinson (1,5), General Entropy (0), General Entropy (1), General Entropy

(2) and Coefficient of Variation) is rather stable with miniscule d ecline. In all

cases the absolute values are slightly changing in both directions (increase or

decrease); nevertheless, in all cases a small decrease is noted from 2008 to

2009 and a small increase from 2009 to 2010. This element, also, implies a

miniscule decline in inequality in the beginning of economic recession in

Greece and a small increase onwards.

Figure 1 contains the indices of S90/S10 and S80/S20 and Figure 2 illustrates

the trend of the seven aggregate inequality indices.

0,00

2,00

4,00

6,00

8,00

10,00

12,00

14,00

2002 2003 2004 2005 2006 2007 2008 2009 2010

FIG. 1. S90/S10 AND S80/S20 FOR GREECE

S90/S10 S80/S20

0,000

0,100

0,200

0,300

0,400

0,500

0,600

0,700

0,800

0,900

2002 2003 2004 2005 2006 2007 2008 2009 2010

FIG. 2. AGGREGATE INEQUALITY INDICES FOR GREECE

GINI Atkinson 0,5 Atkinson 1,5 GE(0)=Theil L

GE(1)=Theil T GE(2) CV



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International experience

The main variable used in this paper for the estimation of income distribution

is the ‘Total net household income’, which incorporates the net components

of household income without taking into account negative values for net cash

benefits or losses from self-employment (including royalties). This variable is

slightly different in interpretation and in compilation procedure from the

corresponding one (‘Total disposable household income (HY020)’) used by

ELSTAT.

Figures 3 and 4 illustrate the ratio S80/S20 and Gini coefficient for total

disposable household income for Greece and European Union 27 and Euro

Area 17. The reason for the sort period for comparison is due to the lack of

data for European averages.

The empirical findings indicate that aggregate income inequality in Greece is

in higher level than the average of both European Union and Euro area.

0

1

2

3

4

5

6

7

2004 2005 2006 2007 2008 2009 2010

FIG. 3. S80/S20 – INTERNATIONAL COMPARISON I

EU (27 countries) Euro area (17 countries) Greece

27

28

29

30

31

32

33

34

35

2004 2005 2006 2007 2008 2009 2010

FIG. 4. GINI COEFFICIENT – INTERNATIONAL COMPARISON II

EU (27 countries) Euro area (17 countries) Greece



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3. Decomposition of income inequality by sub-groups

3.1. Choice of categories

Certain indices can be decomposed by population subgroups in order to define

which components contribute to total inequality. The decomposition

procedure is applied to the ‘Total net household income’ .

Eight (8) categories were indented to be examined. These categories are

region, urbanization, citizenship of household head (hh), education of hh,

current economic status of hh, occupation status of hh, classification of

activity by NACE of hh and managerial position of hh. Nonetheless, the

limitations on data availability due to the response rate on these questionnaire

codes pose significant obstacles.

Table 1. Valid values of the categorical variables file Year

ofsurvey

2003(N=6665)

2004(N=6252)

2005(N=5568)

2006(N=5700)

2007(N=5643)

2008(N=6504)

2009(N=7036)

2010(N=7005)

2011(N=6029)

Region 6665 6252 5568 5700 5643 6504 7036 7005 6029

Urbanization 6665 6252 5568 5700 5643 6504 7036 7005 6029

Citizenship 5927 5522 4945 5059 5033 5803 6308 7005 6029

Education 5667 5275 4702 4814 4790 5540 6048 6779 6029Currenteconomic

status

5927 5522 4945 5059 5033 5803 6308 7005 6029

Occupation 4718 4475 4025 4142 4147 4783 5269 6388 5536

Activity by NACE

2480 2303 2042 2045 1994 2346 2488 3140 2334

ManagerialPosition

1540 2615 2294 2377 2396 2877 3169 3789 3154

Complete data availability exists for the categorical variables of region and

degree of urbanization. There are many missing values for all years for the

categories occupation, activity by NACE and managerial position. The valid

values are in satisfactory3 level for citizenship, education and current

economic status for 2010 and 2011 (reference year 2009 and 2010

respectively).

Therefore five (5) categorical variables are utilized; region and degree of

urbanization for all years and citizenship, education and current economic

3 According to Table 1 the coverage for both years is 100% with the exception of ‘education’ for 2010

(year of survey) which is 97%.



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status for 2010 and 2011 (reference year 2009 and 2010 respectively) 4. It is

noted, nonetheless, that estimations have been made for all variables for all

years and they are available upon request.

3.2. Technical details for income decomposition by sub-groups

Following Araar and Duclos (2009), Gini index and the Generalized Entropy

indices can be decomposed in order to determine the contribution of each

subgroup to total inequality. G is the number of population subgroups.

Gini index

(5)

Where

the population share of group g

the income share of group g

between-group inequality (when each individual is assigned the averageincome of his group)

R The residue implied by implied income overlap

It is noted that the fi rst component is ‘between’ contribution of inequality, the

second is the ‘within’ and the third is the ‘overlap’

Generalized entropy indices

The mathematical expression of decomposition is

(6)

Where

4 Details for the five categorical variables are presented in the Annex.



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Bf(k) is the proportion of the population found in subgroup k

Bm(k) is the mean income of group k

BI(k;θ) is inequality within group k

is population inequality if each individual in subgroup k is given themean income of subgroup k,m(k)

3.3. Empirical findings for income decomposition by sub-groups

The decomposition procedure can indicate the contribution of the population

subgroups’ inequality to the total inequality. According to this procedure it

can be defined whether the inequality derives from factors ‘between’ or

‘within’ the population subgroups. The four aggregate income inequality

indices [Gini coefficient, General Entropy 0 (GE0), General Entropy 1 (GE1)

and General Entropy 2 (GE2)] are decomposed by five categories ( region,

degree of urbanization , citizenship, education and current economic status).

The main results of the decomposition of aggregate inequality indices for the

categorical variable ‘region’ are presented in Table 2.

Table 2. Decomposition of aggregate inequality indices by ‘Region’

ge0 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 93,6% 94,4% 96,2% 96,7% 95,0% 95,5% 95,5% 95,7% 97,4%

between 6,4% 5,6% 3,8% 3,3% 4,9% 4,8% 4,8% 4,2% 2,5%

ge1 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 93,6% 94,4% 96,2% 96,7% 95,1% 95,7% 95,7% 95,8% 97,4%

between 6,5% 5,6% 3,8% 3,3% 4,7% 4,6% 4,6% 4,1% 2,4%

ge2 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 95,2% 95,9% 97,1% 97,6% 96,7% 97,0% 97,0% 97,1% 98,3%

between 4,8% 4,1% 2,9% 2,4% 3,3% 3,0% 3,0% 2,9% 1,7%

gini 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 18,5% 16,8% 14,5% 14,9% 15,2% 16,8% 16,7% 15,8% 13,4%

between 25,6% 23,9% 19,6% 18,5% 22,6% 20,6% 21,8% 20,7% 15,7%

overlap 56,0% 59,3% 65,9% 66,5% 62,2% 62,7% 61,6% 63,6% 70,9%

Source: Authors’ calculations

The findings indicate that decomposing aggregate inequality by region the

main contribution to total income inequality is the ‘within’ inequality. Therelative contribution for General Entropy (0) varies from 93,6% to 97,4%, for



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General Entropy (1) varies from 93,6% to 97,4% and for General Entropy (2)

varies from 95,2% to 98,3%. In all three GE’s cases a small increasing trend

exists. The picture is vaguer for the outcome for Gini coefficient, since a

component of ‘overlap’ effect exists. The ‘within’ inequality contribution is

smaller than the ‘between’, with no big differences nevertheless. According,

thus, to the empirical results, the aggregate income inequality is mainly due to

the differences in the income distribution ‘within’ each of the thirteen

regions.

Table 3 summarizes the results for the decomposition procedure for the

categorical variable ‘degree of urbanization’.

Table 3. Decomposition of aggregate inequality indices by ‘Degree of urbanization’

ge0 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 93,2% 92,7% 94,0% 94,8% 93,9% 96,1% 96,1% 95,9% 97,4%

between 6,8% 7,4% 5,9% 5,1% 6,0% 3,8% 3,8% 4,0% 2,6%

ge1 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 93,3% 92,7% 94,1% 95,0% 94,2% 96,3% 96,3% 96,1% 97,4%

between 6,6% 7,4% 5,8% 5,0% 5,7% 3,5% 3,5% 3,9% 2,5%

ge2 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 95,2% 94,7% 95,6% 96,3% 96,1% 97,7% 97,7% 97,3% 98,3%

between 4,8% 5,3% 4,4% 3,7% 3,9% 2,3% 2,3% 2,7% 1,7%

gini 2002 2003 2004 2005 2006 2007 2008 2009 2010

within 38,3% 38,4% 39,1% 38,7% 38,2% 38,5% 39,2% 39,4% 42,2%

between 24,6% 25,8% 22,9% 21,3% 23,2% 20,8% 18,0% 19,0% 15,0%

overlap 37,1% 35,8% 38,0% 39,9% 38,7% 40,7% 42,7% 41,6% 42,8%


The findings indicate, once again, that the main contribution to total income

inequality is the ‘within’ inequality. The relative contribution for General

Entropy (0) varies from 93,2% to 97,4%, for General Entropy (1) varies from

93,3% to 97,4% and for General Entropy (2) varies from 95,2% to 98,3%. In

all three cases a small increasing trend exists. These findings are verified also

from the outcome for Gini coefficient, despite of the existence of the

‘overlap’ effect. Similar to the case of regions, the aggregate income

inequality is mainly due to the differences in the income distribution ‘within’

the areas of different degree of urbanization.



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The main results of the decomposition of aggregate inequality indices for the

categorical variable ‘citizenship’ for the years 2009 and 2010 (year of survey

2010 and 2011 respectively) are presented in Table 4.

Table 4. Decomposition of income

inequality indices by ‘citizenship’

ge0 2009 2010

within 98,3% 99,2%

between 1,8% 0,9%

ge1 2009 2010

within 98,6% 99,3%

between 1,5% 0,8%

ge2 2009 2010

within 99,1% 99,5%

between 0,9% 0,5%

gini 2009 2010

within 91,4% 92,7%

between 4,7% 3,1%

overlap 3,8% 4,1%


The results indicate that the main contribution to the total inequality is the

‘within’ inequality. In all cases the relative contribution of the ‘within’

component for the general entropy indices exceeds 98%. Gini coefficient

indicates very high values of the ‘within’ component (over 91%) as well. This

certifies the a-priori expectations since the main percentage of the

respondents (over 95% for both years) have Greek citizenship.

Table 5 illustrates the decomposition according to the category of education.


inequality indices by ‘education’

ge0 2009 2010

within 75,0% 74,9%

between23,4% 25,0%

ge1 2009 2010

within 75,4% 74,0%

between 23,7% 26,0%

ge2 2009 2010

within 81,5% 80,2%

between 18,1% 19,8%

gini 2009 2010

within 18,5% 18,0%

between 55,7% 50,0%

overlap 25,8% 32,0%




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The empirical findings indicate a different pattern. The main contribution to

the total inequality remains the ‘within’ inequality; nevertheless the effect of

between inequality is significant. The relative contribution of ‘between’

inequality is 23,4%-25%, 23,7%-26,1% and 18,1%-19,8% for General

Entropy (0) (1) and (2) respectively. The picture is vaguer for the outcome for

Gini coefficient, since a component of ‘overlap’ effect exists. The ‘within’

inequality contribution is smaller than the ‘between’. According, thus, to the

empirical results, the aggregate income inequality stems from the differences

in the income distribution ‘within’ the ‘education classes’, but there is strong

evidence that inequality is affected, also, from dif ference ‘between’

‘education classes’.

The final category for income decomposition by sub-groups is ‘current

economic status’.


inequality indices by ‘current

economic status’

ge0 2009 2010

within 92,1% 88,8%

between 8,3% 11,9%

ge1 2009 2010

within 92,8% 89,5%

between 7,5% 11,1%

ge2 2009 2010

within 94,9% 92,6%

between 5,1% 7,4%

gini 2009 2010

within 24,1% 24,7%

between 27,6% 33,3%

overlap 48,2% 42,1%


The findings indicate, once again, that the main contribution to total income

inequality is the ‘within’ inequality. The relative contribution of ‘within’

inequality for all General Entropy indices exceeds 88% with a decrease being

detectable from 2009 to 2010. Similar to some of the previous cases, the



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‘overlap; effect poses certain difficulties. The ‘within’ inequality contribution

is smaller than the ‘between’, with no big differences nevertheless.

According, thus, to the empirical results, the aggregate income inequality is

mainly due to the differences in the income distribution ‘within’ each of

eleven ‘current economic status’ classes.

Comparing sub- groups’ inequality indices

Being the ‘within’ inequality the main contribution to aggregate inequality,

does not mean that there are no differences among the population sub-groups.

The income has a more ‘unequal’ distribution in the region of ‘Ipeiros’ and

‘Sterea Ellada’ and more ‘equal’ in the region of ‘Kriti’ and ‘ West

Makedonia’ (although in certain years some indices indicate other regions for

both cases; it is noted that there is evidence of increase of inequali ty in Attiki

for 2010). As far as the categorical variable of urbanization is concerned,

income inequality is more intense in the intermediate areas and less intense in

the densely populated areas. For the years 2009 and 2010 (year of survey

2010 and 2011 respectively) the inequality for citizenship, education and

current economic status is the following: Inequality is more intense in the

Greek citizens for 2009; nonetheless this is not the case for 2010. The income

has a more ‘unequal’ distribution among the people that have attained first

stage of tertiary education and more ‘equal’ in the education class of pre -

primary education. As far as the current economic status is concerned, income

inequality is more intense in self-employed (full time) and less intense in

people that are in compulsory military or community service.

4. Decomposition of income inequality by income sources

4.1. Technical details for income decomposition by income sources

In this section the decomposition of the Gini coefficient by income

components will be presented. This decomposition allows to have a clear idea

on how each component contributes to the total inequality. The Araar (2006a)

approach will be implemented. First, one supposes that the sum of K



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components equals the total income and the amount of component k, noted by

, equals or is greater than zero. The analytical decomposition of Gini

coefficient is:

Where is the income share of the component k, is the level of

component k for household I and is the single-parameter concentration

coefficient of component k. This is the mathematical expression of

decomposition according to Rao (1969). Araar (2006a) 5 proposes the

following decomposition of the Gini coefficient:

where definitions of symbols with (*) are similar to those already defined

except that Araar uses the translated income components instead of the usual

components, i.e. and . The

component is the variation effect (VE) and the component is the

constant effect (CE). It is noted that this decomposition is similar to Rao’s if

.

5 For more technical details the interested reader could see Araar (2006a) and for implications of the

constant effect impact could, also, see Shorrocks (1988) and Potter and Chatterjee (2002).



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4.2. Empirical findings for income decomposition by income sources

The decomposition by income sources will be applied for the Gini coefficient

for the years 2002-2010 (years of reference). The income components of the

underlying variable that is being used are presented in the following table.

Table 7. Income components

Code Income component

1 sum of net employee cash or near cash income

2 company car

3 sum of net cash benefits from self-employment (including royalties)_no negative values

4 sum of unemployment benefits

5 sum of old-age benefits

6 sum of survivor' benefits

7 sum of sickness benefits

8 sum of disability benefits

9 sum of education-related allowances

10 income from rental of a property or land

11 family/children related allowances

12 social exclusion not elsewhere classified

13 housing allowances

14 regular inter-household cash transfers received

15 interests, dividends, profit from capital investments in unincorporated business

16 income received by people aged under 16Source: Authors’ calculations and ELSTAT

The results of the decomposition procedure are presented in Table 8.

Table 8. Relative contribution of income components to total income inequality

Relative

contribution

2002

Relative

contribution

2003

Relative

contribution

2004

Relative

contribution

2005

Relative

contribution

2006

Relative

contribution

2007

Relative

contribution

2008

Relative

contribution

2009

Relative

contribution

2010

1. net employee

cash or near cash

income

58,19% 55,08% 55,08% 54,03% 52,92% 55,09% 54,26% 52,87% 51,99%

2. company car0,12% 0,16% 0,16% 0,18% 0,18% 0,18% 0,20% 0,21% 0,17%

3. sum of net cash

benefits from self-

employment

(including

royalties)

27,57% 32,93% 32,93% 31,38% 30,72% 28,93% 28,22% 27,82% 29,32%

4. unemployment

benefits 0,46% 0,21% 0,21% 0,14% 0,10% 0,16% 0,25% 0,33% 0,50%

5. old-age benefits 8,50% 6,88% 6,88% 8,30% 9,85% 10,55% 11,88% 14,49% 13,39%

6. survivor'

benefits-0,58% -1,08% -1,08% -0,98% -1,15% -1,36% -1,02% -1,31% -1,57%

7. sickness

benefits0,00% 0,05% 0,05% 0,02% 0,01% 0,07% 0,04% 0,05% 0,03%

8. disability

benefits-0,03% 0,05% 0,05% 0,09% 0,13% 0,01% 0,33% 0,52% 0,12%

9. education-

related allowances0,04% 0,09% 0,09% 0,04% 0,08% 0,09% 0,04% 0,05% 0,06%

10. income from

rental of a

property or land

5,28% 6,40% 6,40% 7,24% 7,63% 6,28% 5,87% 5,52% 6,13%

11. family/children

related allowances0,31% 0,30% 0,30% 0,27% 0,27% 0,24% 0,50% 0,41% 0,70%

12. social exclusion

not elsewhere

classified

-0,09% -0,33% -0,33% -0,33% -0,34% -0,35% -0,42% -0,42% -0,28%

13. housingallowances -0,01% -0,01% -0,01% -0,01% 0,00% 0,01% 0,01% -0,01% 0,02%

14. regular inter-

household cash-1,10% -0,98% -0,98% -1,08% -1,15% -0,76% -0,89% -1,27% -1,11%



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transfers received

15. interests,

dividends, profit

from capital

investments in

unincorporated

business

1,34% 0,27% 0,27% 0,69% 0,72% 0,85% 0,73% 0,73% 0,54%

16. income

received by people

aged under 16

0,00% 0,00% 0,00% 0,02% 0,01% 0,01% 0,00% 0,00% 0,00%

total 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00% 100,00%


The empirical findings indicate that the main contribution to the total income

inequality stems from salaries and wages, income from the self employed, and

to a lesser extent from pensions and property income. More specifically,

salaries and wages are the main source of income inequality; the level varies

from approximately from 52% to 58%. The second most important factor of

influence in the inequality structure is the income from self-employment with

a range of 28% to 33%. The volume of the effect that the other two

components pose to the aggregate inequality is significantly smaller. The

level of old age benefits (mostly pensions) and property income ranges from

approximately from 7% to 15% and from 5% to 8% respectively. The other

income components do not pose significant effect on the aggregate income

inequality.

An interesting fact is that, although the time period is short, the contribution

of income components changes. The effect of the salaries and wages

decreases (from 58,19% to 51,99%) whereas the trend of the pensions’ ef fect

is increasing (from 8,50% to 13,39%), although this trend seems to be

interrupted for 2010. The contribution of the self -employment income yielded

an increasing trend until 2005 followed by a decrease in the next years. The

pattern is similar for property income with the only difference being the

turning point (2007 instead of 2006).

5. Redistributive effects of social transfers and taxes

The components of total household income include various social t ransfers. In

the following section the redistributive effects of these transfers are reviewed.

Moreover, the effects of the taxation system on income distribution are

analyzed.



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5.1. Redistributive effects of social transfers

The study of the income distribution before and after social transfers is

important, since it reveals the impact of social policy. In order to quantify

these effects two variables are compiled.

Total net household income before social transfers except old-age and

survivor’s benefits_ no negative PY050N (HY022net_nn):

This variable includes income on household level taking into account, also,

components of personal income. It, therefore, includes net employee cash or

near cash income, company car, net cash benefits or losses from self-

employment including royalties), old-age benefits, survivor' benefits, income

from rental of a property or land, regular inter-household cash transfers

received, interests, dividends, profit from capital investments in

unincorporated business and income received by people aged under 16.

In this case we do not take into account the negative values in the variable

net cash benefits or losses from self-employment (including royalties).

Total net househol d in come before social t r ansfer s incl udi ng old -age and

survivor’s benefits_ no negative PY050N (HY023net_nn):




employment (including royalties), income from rental of a property or land,

regular inter-household cash transfers received, interests, dividends, profit

from capital investments in unincorporated business and income received by

people aged under 16.

In this case we do not take into account the negative values in the variable net

cash benefits or losses from self-employment (including royalties).

The effect of the two types of pensions (old age and survivors) is isolated

since one of the most important policy tools is the pension system. The



20

distribution of these two variables is compared with the corresponding one of

the ‘ Total net household income_ no negative PY050N (HY010net_nn)’ .

Therefore the analysis ‘moves’ from the variable with the less income

components (HY023_net_nn) to variable with all income components

(HY010net_nn)

It is noted that all variables under review have been adjusted for the size of

the household according to the "OECD-modified scale".

The analysis constitute of the typical comparison of the main inequality

measures (axiomatic approach) and of second order stochastic dominance.

In Table 9 the basic statistics, income shares and aggregate income inequality

measures under the three alternative household income definitions are

presented. Figure 5 presents the 10% top income shares of the three income

definitions.

Table 9. Redistributive effects of social transfers

2002 2003 2004 2005 2006 2007 2008 2009 2010

Average

HY023NET_NN 6.916 7.127 7.539 7.892 8.210 8.577 8.739 8.465 7.195HY022NET_NN 9.506 9.934 10.606 11.108 11.739 12.472 12.948 12.932 11.310

HY010NET_NN 9.756 10.211 10.945 11.480 12.133 12.905 13.441 13.503 11.813

Shares

Decile_01

HY023NET_NN 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00

HY022NET_NN 0,02 0,02 0,02 0,02 0,02 0,02 0,02 0,02 0,02

HY010NET_NN 0,02 0,02 0,03 0,03 0,03 0,03 0,02 0,03 0,03

Decile_02

HY023NET_NN 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00 0,00

HY022NET_NN 0,04 0,04 0,04 0,04 0,04 0,04 0,04 0,04 0,04

HY010NET_NN 0,04 0,04 0,04 0,04 0,04 0,04 0,04 0,05 0,04

Decile_03

HY023NET_NN 0,01 0,01 0,01 0,01 0,01 0,00 0,00 0,00 0,00HY022NET_NN 0,05 0,05 0,05 0,05 0,05 0,05 0,05 0,05 0,05

HY010NET_NN 0,05 0,06 0,05 0,05 0,05 0,06 0,06 0,06 0,06

Decile_04

HY023NET_NN 0,04 0,04 0,03 0,03 0,03 0,03 0,03 0,03 0,01

HY022NET_NN 0,06 0,06 0,06 0,06 0,06 0,06 0,06 0,06 0,06

HY010NET_NN 0,06 0,07 0,07 0,06 0,06 0,07 0,07 0,07 0,07

Decile_05

HY023NET_NN 0,07 0,07 0,06 0,06 0,06 0,06 0,06 0,06 0,05

HY022NET_NN 0,08 0,08 0,08 0,07 0,07 0,08 0,08 0,08 0,07

HY010NET_NN 0,08 0,08 0,08 0,08 0,08 0,08 0,08 0,08 0,08

Decile_06

HY023NET_NN 0,09 0,09 0,09 0,09 0,08 0,09 0,09 0,09 0,08

HY022NET_NN 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09HY010NET_NN 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09

Decile_07



21

HY023NET_NN 0,11 0,12 0,12 0,11 0,11 0,11 0,11 0,11 0,11

HY022NET_NN 0,11 0,11 0,10 0,10 0,10 0,10 0,10 0,10 0,10

HY010NET_NN 0,10 0,11 0,10 0,10 0,10 0,10 0,10 0,10 0,10

Decile_08

HY023NET_NN 0,15 0,15 0,15 0,15 0,15 0,15 0,15 0,15 0,15

HY022NET_NN 0,13 0,13 0,13 0,13 0,12 0,13 0,12 0,12 0,13

HY010NET_NN 0,13 0,13 0,12 0,12 0,12 0,12 0,12 0,12 0,12Decile_09

HY023NET_NN 0,19 0,19 0,19 0,20 0,19 0,20 0,19 0,20 0,20

HY022NET_NN 0,16 0,16 0,16 0,16 0,16 0,16 0,15 0,16 0,16

HY010NET_NN 0,16 0,16 0,15 0,16 0,15 0,15 0,15 0,15 0,15

Decile_10

HY023NET_NN 0,34 0,33 0,35 0,35 0,36 0,36 0,37 0,37 0,39

HY022NET_NN 0,27 0,26 0,27 0,27 0,28 0,27 0,28 0,27 0,27

HY010NET_NN 0,26 0,25 0,26 0,27 0,27 0,26 0,27 0,26 0,26

GINI

HY023NET_NN 0,539 0,537 0,560 0,560 0,569 0,568 0,585 0,582 0,614

HY022NET_NN 0,366 0,354 0,365 0,369 0,373 0,363 0,370 0,358 0,368

HY010NET_NN 0,352 0,340 0,348 0,350 0,354 0,343 0,349 0,335 0,343

Atkinson 0,5HY023NET_NN 0,327 0,332 0,359 0,353 0,360 0,367 0,374 0,384 0,430

HY022NET_NN 0,116 0,112 0,117 0,116 0,120 0,116 0,117 0,112 0,125

HY010NET_NN 0,104 0,100 0,102 0,102 0,106 0,101 0,103 0,096 0,104

Atkinson 1,5

HY023NET_NN 0,461 0,491 0,533 0,532 0,558 0,558 0,570 0,587 0,608

HY022NET_NN 0,302 0,280 0,291 0,298 0,307 0,294 0,287 0,282 0,289

HY010NET_NN 0,280 0,259 0,269 0,268 0,273 0,267 0,265 0,254 0,263

GE(0)=Theil L

HY023NET_NN 0,357 0,365 0,398 0,408 0,433 0,419 0,437 0,435 0,455

HY022NET_NN 0,231 0,209 0,221 0,230 0,236 0,223 0,221 0,214 0,219

HY010NET_NN 0,214 0,193 0,204 0,207 0,211 0,200 0,200 0,190 0,198

GE(1)=Theil T

HY023NET_NN 0,304 0,292 0,313 0,325 0,351 0,335 0,355 0,353 0,353

HY022NET_NN 0,228 0,205 0,220 0,230 0,241 0,229 0,232 0,193 0,225

HY010NET_NN 0,216 0,193 0,207 0,213 0,222 0,210 0,213 0,199 0,207

GE(2)=CV

HY023NET_NN 0,641 0,626 0,673 0,690 0,776 0,781 0,848 0,813 0,946

HY022NET_NN 0,316 0,287 0,299 0,316 0,353 0,341 0,358 0,320 0,343

HY010NET_NN 0,295 0,268 0,276 0,288 0,322 0,310 0,324 0,284 0,305

CV

HY023NET_NN 1,132 1,119 1,160 1,175 1,245 1,250 1,303 1,275 1,375

HY022NET_NN 0,795 0,757 0,773 0,794 0,840 0,826 0,847 0,799 0,829

HY010NET_NN 0,769 0,732 0,742 0,759 0,803 0,788 0,805 0,754 0,782




22

In all three cases the nominal average income increases for the whole time

period. As expected, the incorporation of social transfers increases average

income. The behavior of income shares reveals more significant results. The

lower classes yield an increased part of the generated income; nevertheless

the income shares remain in low levels. These levels are stable over time.

More specifically social transfers resulted in an increase from 0% to 2%-3%

for the lower 10% income share. The corresponding figures for the next lower

10% (decile 2) modified from 0% to 4%-5%. The amounts for decile 3 show

also an increase from 0%-1% to 5%-6%. The next two classes indicate an

increase of proportion of generated income; nevertheless not as intense as in

the previous cases. On the other side, the income shares for the upper

economic classes deteriorate. This is more intense for the upper 10% income

share. The proportion of income drops from a level of 34%-37% to 26%-27%.This decline is observed for the two previous 10% of the population but to a

significantly less degree. The impact for the middle class is very small since

the magnitude of changes in the income shares is small; almost zero for decile

6 and approximately at the level of 1% for decile 7.

The usage of two variables makes feasible the discrimination of the impact of

the types of social transfers. Old age pensions and survivor’ pensions pose the

most significant effect on the behavior of income shares. This is more obvious

in the three lower income shares and in the 10% top income share. The rest of

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,45

2002 2003 2004 2005 2006 2007 2008 2009 2010

FIG. 5. 10% Top Income Shares

HY023NET_NN HY022NET_NN HY010NET_NN



23

the social transfers impose a small impact on income distribution being

negligible mainly in the middle income classes.

The empirical findings suggest that the social transfers smoothens the

inequalities, since the part of the income share of the upper classes is

decreasing. This effect is more intense for the 10% top income share. The

lower classes are benefited from the redistribution; still though the proportion

of the generated income for them is in low levels. The higher parts of middle

income classes are affected in low levels whereas the lower parts are

benefited; in less degree, though, than the lower income classes. From all the

types of social transfers the most significant effect derives from old age and

survivor’s benefits.

The decline of inequality is captured from the behavior of the aggregate

inequality measures [Gini, Atkinson (0,5), Atkinson (1,5), General Entropy

(0), General Entropy (1), General Entropy (2) and Coefficient of Variation].

Nevertheless, not all three cases yield a homogeneous pattern over time. Total

net household income before social transfers except old-age and survivor’s

benefits has a miniscule increase (except CV, which decreases), while total

net household income before social transfers including old-age and survivor’s

benefits has a minuscule decrease (except GE (2) and CV which are virtually

constant). The difference in GE (2) and CV may provide a justification for

the interception in the very tails of distributions (see below), since these

indices are sensitive to movements in the ‘ends’ of the distribution. Still

though, social transfers except old age and survivor’s benefi ts decrease

inequality and then social transfers including old age and survivor’s benefits

results in reduced aggregate income inequality.

The widely used approach to test the stochastic dominance in inequality is the

comparison between the Lorenz curves. Atkinson (1970) refers that all indices

that respect the Pigou-Dalton principle should indicate that inequality in A is

higher than inequality in B when is everywhere above . Thus,

distribution B inequality dominates distribution A at the second order if and

only if

(11)

where p refers to percentile [see also Araar (2006b)].



24

The empirical results are verified to a significant extent from the calculation

of Lorenz curves for each distribution. The following figures illustrate the

‘movement’ of Lorenz curve when social transfers are incorporated in the

components of the aggregate income (the differences are available upon

request). It is apparent that the old age and survivor’s benefits have the most

influential impact on the distribution of income.

Figure 6. Stochastic dominance for social transfers: 2002-2010

0

. 2

. 4

. 6

. 8

1

0 .2 .4 .6 .8 1Percentiles (p)

45° line hy023net_nn_eq

hy022net_nn_eq hy010net_nn_eq

Lorenz Curves_2002

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2003

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2004

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2005

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2006

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2007



25


Applying the inequality dominance test we observe that there is no

intersection of the Lorenz curves for the years 2009 and 2008. The other years

bear ambiguous results (one to three intersections) but only in the tails of the

distributions. These cases occur below 0.009 percentile (from 0.003 to 0.009

– seven cases) and above 0.999 percentile (two cases) 6. The analytical results

are presented in the Annex. The main conclusions do not alter. Inequality

dominance test indicate that social transfers reduce aggregate income

inequality.

5.2. Redistributive effects of taxes

The study of the income distribution before and wealth and income taxes is

important, since it reveals the impact of taxation policy on income

distribution. In order to quantify these effects one variable is compiled. Due

to data restrictions the variable is calculated from the year 2006 (year of

6 The analytical results are available upon request.

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2008

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2009

0

. 2

. 4

. 6

. 8

1




Lorenz Curves_2010



26

survey 2007) onwards. The analysis, thus, is confined to a shorter time

period.

Total net household income minus taxes_ no negative PY050N

(HY020net_nn):




employment (including royalties), unemployment benefits, old-age benefits,

survivor' benefits, sickness benefits, disability benefits, education-related

allowances, income from rental of a property or land, family/children related

allowances, social exclusion not elsewhere classified, housing allowances,

regular inter-household cash transfers received, interests, dividends, profit

from capital investments in unincorporated business, income received by

people aged under 16 minus regular taxes on wealth and tax on income and

social insurance contributions (if applicable).

In this case we do not take into account the negative values in the variable net

cash benefits or losses from self-employment (including royalties).

It is noted that the variable tax on income hardly contains data for social

insurance contributions. This small distortion, nevertheless, should be taken

into account.

The effect of wealth taxes and taxes on income is isolated in order to estimate

the impact of taxation policy. The distribution of the new variable is

compared with the corresponding one of the ‘ Total net household income_ no

negative PY050N (HY 010net_nn)’ .

It is noted that both variables under consideration have been adjusted for the

size of the household according to the "OECD-modified scale".

As in this case of the redistributive effects of social transfers, the analysis

constitute of the typical comparison of the main inequality measures

(axiomatic approach) and of second order stochastic dominance.

In the Table 10 the basic statistics, income shares and aggregate income

inequality measures under the two alternative household income definitions

are presented.



27

Table 10. Redistributive effects of taxes

2006 2007 2008 2009 2010

Average

HY010NET_NN 12.133 12.905 13.441 13.503 11.813

HY020NET_NN 8.577 9.340 9.866 10.064 8.809Shares

Decile_01

HY010NET_NN 0,03 0,03 0,02 0,03 0,03

HY020NET_NN 0,02 0,03 0,02 0,03 0,03

Decile_02

HY010NET_NN 0,04 0,04 0,04 0,05 0,04

HY020NET_NN 0,05 0,05 0,05 0,05 0,05

Decile_03

HY010NET_NN 0,05 0,06 0,06 0,06 0,06

HY020NET_NN 0,06 0,06 0,06 0,06 0,06

Decile_04

HY010NET_NN 0,06 0,07 0,07 0,07 0,07

HY020NET_NN 0,07 0,08 0,08 0,08 0,07Decile_05

HY010NET_NN 0,08 0,08 0,08 0,08 0,08

HY020NET_NN 0,09 0,09 0,09 0,09 0,08

Decile_06

HY010NET_NN 0,09 0,09 0,09 0,09 0,09

HY020NET_NN 0,10 0,10 0,10 0,10 0,10

Decile_07

HY010NET_NN 0,10 0,10 0,10 0,10 0,10

HY020NET_NN 0,11 0,11 0,11 0,11 0,11

Decile_08

HY010NET_NN 0,12 0,12 0,12 0,12 0,12

HY020NET_NN 0,13 0,12 0,12 0,12 0,13

Decile_09

HY010NET_NN 0,15 0,15 0,15 0,15 0,15

HY020NET_NN 0,15 0,14 0,14 0,14 0,15

Decile_10

HY010NET_NN 0,27 0,26 0,27 0,26 0,26

HY020NET_NN 0,22 0,22 0,23 0,22 0,23

S90/S10

HY010NET_NN 10,52 9,63 11,56 9,37 10,31

HY020NET_NN 9,54 8,38 10,76 7,45 9,05

S80/S20

HY010NET_NN 6,21 5,86 6,22 5,57 5,90

HY020NET_NN 5,06 4,73 5,16 4,39 5,10

GINI

HY010NET_NN 0,354 0,343 0,349 0,335 0,343

HY020NET_NN 0,299 0,289 0,299 0,278 0,305

Atkinson 0,5

HY010NET_NN 0,106 0,101 0,103 0,096 0,104

HY020NET_NN 0,073 0,071 0,075 0,066 0,078

Atkinson 1,5

HY010NET_NN 0,273 0,267 0,265 0,254 0,263

HY020NET_NN 0,220 0,212 0,229 0,198 0,228

GE(0)=Theil L

HY010NET_NN 0,211 0,200 0,200 0,190 0,198

HY020NET_NN 0,152 0,143 0,151 0,134 0,159

GE(1)=Theil T

HY010NET_NN 0,222 0,210 0,213 0,199 0,207

HY020NET_NN 0,143 0,138 0,145 0,126 0,153

GE(2)=CV

HY010NET_NN 0,322 0,310 0,324 0,284 0,305



28

HY020NET_NN 0,184 0,186 0,206 0,156 0,202

CV

HY010NET_NN 0,803 0,788 0,805 0,754 0,782

HY020NET_NN 0,607 0,609 0,642 0,559 0,636


The average income for the two alternative household income definitions

increases for the whole time period. The average income after the

implementation of taxes decreases. The behavior of income shares reveals

more significant results. The income shares for the lower classes either

remain unchanged or slightly increases. The levels of the proportion of

generated income do not change for deciles 1 (around 3%) and 3 (around 6%)

and slightly increases for decile 2 (from 4% to 5%). Small increases are, also,

observed in the middle income classes; approximately 1% in each decile (4, 5,

6 and 7). In all cases the levels of income proportion are relatively stable over

time. Finally, the income shares for the upper economic classes decrease. This

is more intense for the upper 10% income share. The proportion of income

drops from a level of 26%-27% to 22%-23%. This decline is observed for the

previous 10% of the population but to a signi ficantly less degree (around 1%).

The empirical findings suggest that the taxation system smoothens

inequalities. The income share of the upper classes is decreasing. This effect

is more intense for the 10% top income share. The lower classes are either not

affected or slightly benefited from the taxes imposed. The middle income

classes are, also, slightly positively affected from the taxation system.

These findings are also supported by the trend of ratios S90/S10 and S80/S20.

The ratios are lower when taxes are imposed.

The decline of inequality is captured from the behavior of the aggregate

inequality measures [Gini, Atkinson (0,5), Atkinson (1,5), General Entropy(0), General Entropy (1), General Entropy (2) and Coefficient of Variation].

For both income definitions the indices suggest for the time trend a miniscule

decrease in aggregate inequality with a detectable increase in 2010.

As in the case of the analysis of redistributive effects of social transfers, the

approach of stochastic dominance is applied.

The empirical findings for the effects of taxation are verified to a significant

extent from the calculation of Lorenz curves for each distribution. The



29

following figures illustrate the ‘movement’ of Lorenz curve when taxes are

imposed on the household net aggregate income.

Figure 7. Stochastic dominance for taxes: 2002-2010


Applying the inequality dominance test, nevertheless, some ambiguous results

are detected. In all years the Lorenz curves seem to intersect. The critical

percentile is 0.107 for 2010, 0.08 for 2009, 0.137 for 2008, 0.112 for 2007

and 0.131 for 2006. Below this intersection the curve for household net

aggregate income is above the corresponding curve after taxes. This imposes

an ambiguity for the benefits of taxes for the lower class. Still, though, the

0

. 2

. 4

. 6

. 8

1



hy020net_nn_eq

Lorenz Curves_TAXES_2006

0

. 2

. 4

. 6

. 8

1



hy020net_nn_eq


0

. 2

. 4

. 6

. 8

1



hy020net_nn_eq


0

. 2

. 4

. 6

. 8

1



hy020net_nn_eq


0

. 2

. 4

. 6

. 8

1



hy020net_nn_eq

Lorenz Curves_TAXES 2010



30

main conclusions do not alter. Inequality dominance test indicate that the

taxation system results in the reduction of aggregate income inequality.

6. Income inequality and imputed rent

The data set of EU-SILC contains information on imputed rent. The imputed

rent refers to the amounts that should be imputed for all households that do

not pay rent. The reason for nonpayment could be either because they are

owner-occupiers or because the pay rent at lower prices than the market price

or because the accommodation is provided for free.

In order to estimate the impact on income inequality the following variable is

compiled:

Total net household income_ imputed rent _ no negat i ve PY050N

(HY010net_nn_imp): It is the total net household income_ no negative

PY050N (HY010net_nn) with imputed rent.

There is difficulty in the measurement of imputed rent and this fact should be

taken into consideration in the interpretation of results.

It is noted that both variables under review have been adjusted for the size of

the household according to the "OECD-modified scale".

As in this case of the redistributive effects of social transfers and taxes, the

analysis constitute of the typical comparison of the main inequality measures

(axiomatic approach) and of second order stochastic dominance.

In the Table 11 the basic statistics, income shares and aggregate income

inequality measures of the comparison for the two distributions are presented.

Table 11. Impact of imputed rent

2002 2003 2004 2005 2006 2007 2008 2009 2010

Average

HY010NET_NN 9.756 10.211 10.945 11.480 12.133 12.905 13.441 13.503 11.813

HY010NET_NN_IMP 11.531 12.004 12.874 13.596 14.373 15.212 15.773 15.837 14.229

Shares

Decile_01

HY010NET_NN 0,02 0,02 0,03 0,03 0,03 0,03 0,02 0,03 0,03HY010NET_NN_IMP 0,03 0,03 0,03 0,03 0,03 0,03 0,03 0,03 0,03

Decile_02



31

HY010NET_NN 0,04 0,04 0,04 0,04 0,04 0,04 0,04 0,05 0,04

HY010NET_NN_IMP 0,05 0,05 0,05 0,05 0,05 0,05 0,05 0,05 0,05

Decile_03

HY010NET_NN 0,05 0,06 0,05 0,05 0,05 0,06 0,06 0,06 0,06

HY010NET_NN_IMP 0,06 0,06 0,06 0,06 0,06 0,06 0,06 0,06 0,06

Decile_04

HY010NET_NN 0,06 0,07 0,07 0,06 0,06 0,07 0,07 0,07 0,07HY010NET_NN_IMP 0,07 0,07 0,07 0,07 0,07 0,07 0,07 0,07 0,07

Decile_05

HY010NET_NN 0,08 0,08 0,08 0,08 0,08 0,08 0,08 0,08 0,08

HY010NET_NN_IMP 0,08 0,08 0,08 0,08 0,08 0,08 0,08 0,08 0,08

Decile_06

HY010NET_NN 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09

HY010NET_NN_IMP 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09 0,09

Decile_07

HY010NET_NN 0,10 0,11 0,10 0,10 0,10 0,10 0,10 0,10 0,10

HY010NET_NN_IMP 0,10 0,11 0,10 0,10 0,10 0,10 0,10 0,10 0,10

Decile_08

HY010NET_NN 0,13 0,13 0,12 0,12 0,12 0,12 0,12 0,12 0,12

HY010NET_NN_IMP 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12 0,12Decile_09

HY010NET_NN 0,16 0,16 0,15 0,16 0,15 0,15 0,15 0,15 0,15

HY010NET_NN_IMP 0,15 0,15 0,15 0,15 0,15 0,15 0,15 0,15 0,15

Decile_10

HY010NET_NN 0,26 0,25 0,26 0,27 0,27 0,26 0,27 0,26 0,26

HY010NET_NN_IMP 0,25 0,24 0,25 0,25 0,25 0,25 0,25 0,24 0,25

S90/S10

HY010NET_NN 11,11 10,45 10,41 10,05 10,52 9,63 11,56 9,37 10,31

HY010NET_NN_IMP 8,28 8,20 8,22 7,98 7,93 7,59 8,62 7,32 7,52

S80/S20

HY010NET_NN 6,38 5,98 6,14 6,12 6,21 5,86 6,22 5,57 5,90

HY010NET_NN_IMP 5,26 5,17 5,28 5,21 5,11 4,88 5,11 4,69 4,72

GINI

HY010NET_NN 0,352 0,340 0,348 0,350 0,354 0,343 0,349 0,335 0,343

HY010NET_NN_IMP 0,323 0,318 0,325 0,325 0,323 0,314 0,319 0,307 0,308

Atkinson 0,5

HY010NET_NN 0,104 0,100 0,102 0,102 0,106 0,101 0,103 0,096 0,104

HY010NET_NN_IMP 0,086 0,084 0,087 0,086 0,087 0,083 0,085 0,079 0,080

Atkinson 1,5

HY010NET_NN 0,280 0,259 0,269 0,268 0,273 0,267 0,265 0,254 0,263

HY010NET_NN_IMP 0,233 0,229 0,235 0,230 0,226 0,222 0,220 0,208 0,215

GE(0)=Theil L

HY010NET_NN 0,214 0,193 0,204 0,207 0,211 0,200 0,200 0,190 0,198

HY010NET_NN_IMP 0,176 0,170 0,178 0,176 0,174 0,166 0,166 0,157 0,161

GE(1)=Theil T

HY010NET_NN 0,216 0,193 0,207 0,213 0,222 0,210 0,213 0,199 0,207

HY010NET_NN_IMP 0,182 0,172 0,182 0,184 0,186 0,177 0,179 0,168 0,171

GE(2)=CV

HY010NET_NN 0,295 0,268 0,276 0,288 0,322 0,310 0,324 0,284 0,305

HY010NET_NN_IMP 0,241 0,227 0,234 0,243 0,260 0,249 0,260 0,230 0,238

CV

HY010NET_NN 0,769 0,732 0,742 0,759 0,803 0,788 0,805 0,754 0,782

HY010NET_NN_IMP 0,694 0,673 0,685 0,697 0,722 0,706 0,722 0,678 0,689


In both cases the average nominal income increases for the whole time period.

The incorporation of imputed rent has a positive impact on average income.



32

The behavior of income shares reveals more significant results. The income

shares for the lower classes either remain unchanged or slightly increases.

The levels of the proportion of generated income do not change for deciles 1

(around 3%) and 3 (around 6%) and slightly increases for decile 2 (from 4%

to 5%). No significant changes are observed in the middle income classes.

The same patterns relatively apply for the lower parts of upper income

classes. Finally, the income shares for the 10% upper economic class

deteriorate. The proportion of income drops from a level of 26%-27% to 24%-

25%.

The empirical findings suggest that the incorporation of imputed rent

smoothens the inequalities. The lower classes are either not affected or

slightly benefited. The middle income classes and the lower parts of upper

classes are, relatively, not affected from the incorporation of imputed rent.

These findings are also supported from the ratios S90/S10 and S80/S20; both

are decreasing.

Finally, the decline of inequality is captured from the behavior of the

aggregate inequality measures [Gini, Atkinson (0,5), Atkinson (1,5), General

Entropy (0), General Entropy (1), General Entropy (2) and Coefficient of

Variation]. In both cases the indices suggest for the time trend a miniscule

decrease in aggregate inequality with an increase being detectable in 2010.

Figure 8. Stochastic dominance for imputed rent: 2002-2010

0

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hy010net_nn_imp_eq

Lorenz Curves_Imputed_2002

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33


Applying the inequality dominance test we observe that there is no

intersection of the Lorenz curves for the years 2009 and 2008. The other yearsindicate one to two intersections but only in the tails of the distributions.

0

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hy010net_nn_imp_eq


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Lorenz Curves_Imputed 2005

0

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hy010net_nn_imp_eq


0

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hy010net_nn_imp_eq


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Lorenz Curves_IMPUTED_2010



34

These cases occur below 0.003 percentile (from 0.000 to 0.003 – seven cases)

and above 0.999 percentile (one case)7. The main conclusions do not alter.

Inequality dominance test indicate that the incorporation of imputed rent

(taken into account the measurement difficulties) reduce aggregate income

inequality.

7. Conclusions

This paper utilizes data from the European Union Survey on Income and

Living Conditions (EU SILC) for examining the structure of income

inequality. EU SILC includes micro data on income, on household and

personal level that can be used for the estimation of income distribution. The

size of the household and the age of its members are important factors,

therefore the use of an equivalence scale is appropriate. In this study the

"OECD-modified scale" is utilized. The time period of the analysis is from

the year 2002 to the year 2010.

The empirical findings indicate that aggregate income inequality in Greece is

in higher level than the average of both European Union and Euro area.

Certain indices can be decomposed by population subgroups in order to define

what components contribute to total inequality. According to this procedure it

can be defined whether the inequality derives from factors ‘between’ or

‘within’ the population subgroups. Five (5) categorical variables were used:

region, urbanization, citizenship of household head (hh), education of

household head, current economic status of household head. The empirical

findings indicate that the main contribution to total income inequality is the

‘within’ inequality. The pattern is different only for the categorical va riable

of education. The education level attained imposes effect on the distribution

of income. It is noted, nonetheless, that being the ‘within’ the main

contribution to aggregate inequality, does not mean that there are no

differences among the sub-groups.

7 The analytical results are available upon request.



35

The decomposition by income components allows having a clear idea on how

each component (sixteen) contributes to the total inequality. The empirical

findings indicate that the main contribution to the total income inequality

stems from salaries and wages, income from the self employed, and to a lesser

extent from pensions and property income. More specifically, salaries and

wages are the main source of income inequality; the level varies from

approximately from 52% to 58%. The second most important factor of

influence in the inequality structure is income from self-employment with a

range of 28% to 33%. The volume of the effect that the other two components

poses to the aggregate inequality is significantly smaller. The level of old age

benefits (mostly pensions) and property income ranges approximately from

7% to 15% and from 5% to 8% respectively. The other income components do

not pose significant effect on the aggregate income inequality.

The analysis for the examination of the redistributive effects of social

transfers and taxes constitutes of the typical comparison of the main

inequality measures (axiomatic approach) and of second order stochastic

dominance. The empirical findings suggest that the social transfers smoothens

inequalities. The same applies for taxes. It is not clear, though, whether the

very lower income class (the lowest two deciles) benefits from the tax system.

Finally, the incorporation of imputed rent (taken into account the

measurement difficulties) reduces aggregate income inequality.



36

ANNEX

The following tables indicate the values of assigned values of the five (5)

variables (region, degree of urbanization, citizenship, education and currenteconomic status).

Table A.6.1. Codes of categorical variable ‘Region’

NUTS code Code Name

GR11 1 Anatoliki Makedonia, Thraki

GR12 2 Kentriki Makedonia

GR13 3 Dytiki Makedonia

GR14 4 Thessalia

GR21 5 Ipeiros

GR22 6 Ionia Nisia

GR23 7 Dytiki Ellada

GR24 8 Sterea Ellada

GR25 9 Peloponnisos

GR30 10 Attiki

GR41 11 Voreio Aigaio

GR42 12 Notio Aigaio

GR43 13 Kriti

Source: Eurostat

The first column describes the regions according to NUTS level 2, the second

column describes the codes used in the decomposition analysis, whereas the

last column contains the names of the Greek regions.

Table A.6.2. Codes of categorical variable ‘Degree of urbanization’ Code Degree of urbanization

1 Densely populated area

2 Intermediate area

3 Thinly populated area

Source: Eurostat

According to classification of Eurostat, the densely populated area is a

contiguous set of local areas, each of which has a density superior to 500

inhabitants per square kilometer, where the total population is at least 50.000

inhabitants. The intermediate area is a contiguous set of local areas, not belonging to a densely populated area, each of which has a density superior to

100 inhabitants per square kilometer, and either with a total population for the

set of at least 50.000 or adjacent to densely-populated area. The thinly-

populated area is the area that does not belong to the two previous cases. The

column ‘code’ describes the labels used in the analysis.

Table A.6.3. Codes of categorical variable ‘Citizenship’

Code Citizenship

1 Greek

2 OtherSource: Eurostat



37

According to Eurostat, citizenship is defined as the particular legal bond

between the individual and his/her State acquired by birth or naturalization,

whether by declaration, choice, option, marriage or other means according to

the national legislation. Eurostat notes that it generally corresponds to the

country issuing the passport.

Table A.6.4. Codes of categorical variable ‘Education’

Code Education (according to ISCED-97)

0 pre-primary education

1 primary education

2 lower secondary education

3 (upper) secondary education

4 post-secondary non tertiary education

5 first stage of tertiary education (not leading to an advanced research qualification)

6 second stage of tertiary education (leading to an advanced research qualification)

Source: Eurostat

According to Eurostat, educational attainment of a person is the highest level

of an educational programme the person has successfully completed and the

study field of the programme. The educational classification is the

International Standard Classification of Education (ISCED 1997).

Table A.6.5. Codes of categorical variable ‘Current Economic Status’

Code Self-defined current economic status

1 Employee working full-time2 Employee working part-time

3 Self-employed working full time (including family worker)

4 Self-employed working part-time (including family worker)

5 Unemployed

6 Pupil, student, further training, unpaid work experience

7 In retirement or in early retirement or has given up business

8 Permanently disabled or/and unfit to work

9 In compulsory military community or service

10 Fulfilling domestic tasks and care responsibilities

11 Other inactive person

Source: Eurostat

According to Eurostat, the concept of ‘current’ implies that any definite

changes in the activity situation are taken into account. Moreover, the

variable captures the person’s own perception of their main activity and it

may differ from the ILO (International Labor Organization) concept to the

extent that people’s perception could be different from the strict d efinitions of

ILO. The self-declared main activity status is, in principle, determined on the

basis of the most time spent. This classification is applied from 2009 and

onwards; for the previous years the codes were slightly different (9 in total).



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Income Inequality in Greece:EU SILC Evidence

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