The Impact of Social Transfers on Poverty Reduction in EU Countries

Abstract

Available studies indicate a strong negative correlation between poverty and social expenditures in EU countries. It means that the country’s at-risk-of-poverty rate tends to erode with increasing social expenditure. However, the studies have demonstrated that the impact of government spending on poverty may vary according to the sector of spending, how well it is targeted, and the way in which it is financed. Some countries manage to achieve a rather significant poverty rate reduction even with relatively low, in the context of other Member States, social expenditure (percentage of GDP). This suggests that in order to reduce poverty rates, it is important to consider not only the amount allocated to social spending, but also the areas the social transfers are channelled to. The article aims to analyse how the composition and the extent of social spending/transfers may affect poverty reduction in EU countries. The analysis showed that social protection transfers reduce the percentage of people at-risk-of-poverty in all countries, however, to a very different extent. Regression analysis demonstrated that social exclusion and family/children expenditure was found to be the most important predictor for a relative antipoverty effect of social transfers: even a small percentage increase in such expenditure allows quite a significant increase in the relative antipoverty effect of social transfers.

Full text

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The Impact of Social Transfers on Poverty Reduction in EU Countries
Baltic Journal of European Studies
Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
The Impact of Social Transfers on Poverty Reduction
in EU Countries
RasaMiežienė
SandraKrutulienė
Lithuanian Social Research Centre,
Labour Market Research Institute
Goštauto str. 9,
Vilnius 01108, Lithuania
E-mail: rasa.zabarauskaite@dsti.lt
E-mail: sandra.krutuliene@dsti.lt
Abstract: Available studies indicate a strong negative correlation between
poverty and social expenditures in EU countries. It means that the
country’s at-risk-of-poverty rate tends to erode with increasing social
expenditure. However, the studies have demonstrated that the impact
of government spending on poverty may vary according to the sector
of spending, how well it is targeted, and the way in which it is  nanced.
Some countries manage to achieve a rather signi cant poverty rate
reduction even with relatively low, in the context of other Member
States, social expenditure (percentage of GDP). This suggests that
in order to reduce poverty rates, it is important to consider not
only the amount allocated to social spending, but also the areas
the social transfers are channelled to. The article aims to analyse
how the composition and the extent of social spending/transfers
may affect poverty reduction in EU countries. The analysis showed
that social protection transfers reduce the percentage of people at-
risk-of-poverty in all countries, however, to a very different extent.
Regression analysis demonstrated that social exclusion and family/
children expenditure was found to be the most important predictor
for a relative antipoverty effect of social transfers: even a small
percentage increase in such expenditure allows quite a signi cant
increase in the relative antipoverty effect of social transfers.
Keywords: EU, poverty reduction, social protection expenditure, social transfers
doi: 10.1515/bjes-2019-0009 Baltic Journal of European Studies
Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)

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Sandra Krutulienė
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Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
1. Introduction
Social spending is one of the most important instruments to ght against poverty
in most countries. Eurostat estimates that in 2017 social transfers resulted in
a reduction of almost one third (32.4%) in the number of people classied
as poor within the EU (pensions are not considered social transfers in these
calculations). The extent to which social transfers reduce the number of people
at risk of poverty varies across EU Member States. In 2017, there were three
Member States where the number of people at risk of poverty was more than
halved as a result of social transfers: Finland (a 56.9% reduction), Ireland
(52.6%) and Denmark (51%). In nine Member States the reduction was below
25%, and of these the smallest reductions were in Greece (15.8%) and Romania
(16.6%) (Eurostat, 2018). The question that arises is why some countries are
more effective in alleviating poverty than others.
Many quantitative studies have showed that there is a strong negative correlation
between poverty and social expenditures across European countries (Cantillon,
2009; Esping-Andersen & Myles, 2009; Mehmood & Sadiq, 2010; Caminada
& Goudswaard, 2010; Caminada et al., 2011). It means that the country’s at-
risk-of-poverty rate tends to erode with increasing social spending. Despite
this strong negative correlation between poverty and social expenditures, some
countries manage to reduce poverty quite signicantly even with relatively
low social expenditure (in the context of other Member States). Looking at
Eurostat data, we can see large differences prevailing among EU countries
in social protection expenditure as a percentage of GDP. In 2016, the highest
levels of social protection expenditure as a percentage of GDP were in France
(34.3%), Finland (31.8%), and Denmark (31.6%); countries with the lowest
levels included Romania (14.6%), Latvia (15.2%), Lithuania (15.4%), and
Ireland (15.8%). However, Ireland was among the countries where poverty rate
after social transfers was more than halved. It may be assumed that in order to
reduce poverty rates, it is important to consider not only the amount allocated to
social spending (as a percentage of GDP), but also the areas the social transfers
are channelled to. This issue has been little addressed in scientic literature
and brings novelty to studies on poverty reduction. The aim of this article is
to analyse how the composition and the extent of social transfers may affect
poverty reduction in EU countries.
Social sector expenditures in this article are dened in accordance with
the European system of integrated social protection statistics (ESSPROS)
classication. According to this classication, social expenditure includes

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social protection transfers which are provided to households and individuals
affected by a specic set of social risks. The terms “social transfers”, “social
expenditure” and “social spending” are used interchangeably in the article. In
order to identify the poor, we use the European Commission’s income poverty
denition according to EU-SILC methodology.
It is important to note that the article is limited to the analysis of the effects of
social protection transfers on poverty reduction, although some other strategies
can be also chosen to alleviate poverty, such as improving job opportunities,
increasing labour force participation, etc.
The research techniques applied in the article include: analysis of literature,
comparative analysis, descriptive statistics, correlation analysis, and regression
analysis. The analysis is based on Eurostat data.
2. Social transfers as an instrument for poverty reduction
Over the last few decades, economic growth has been given particular importance
with regard to poverty reduction. Many authors noted that economic growth
has been one of the main drivers for reduction of poverty and improvement of
the quality of life (Schmidt, 2005; Foster & Székely, 2001; Dagdeviren et al.,
2002; Troitiño, 2013). According to Kraay (2006), growth in average incomes
accounts for some 70% to 95% of poverty reduction. Other studies nd that
around two-thirds of the drop in poverty rates is the result of economic growth
(Pérez de la Fuente, 2016).
Despite the importance of economic growth, a number of studies emphasise
that economic growth alone is not sufcient to reduce relative poverty unless
accompanied by government efforts (Narayan et al., 2013; Moges, 2013).
Findings of the studies at issue are in line with the ideas of the Social Democratic
Theory of Poverty, which highlights the importance of welfare states in the ght
against poverty and exclusion and in increasing the opportunities for the poor to
participate in the labour market and social life. The Social Democratic Approach
strongly favours a welfare state and suggests that welfare is vital in order to
regulate the negative effects of a capitalist society. According to supporters of
this approach, states must ensure that all citizens are guaranteed a minimum
income, which in turn would further serve poverty alleviation (Odekon, 2015).
Today, social transfers are being increasingly recognised as an instrument that
has proven to be effective in reducing poverty in many countries. Caminada et

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Sandra Krutulienė
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Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
al. (2011) have examined the relationship between poverty and social transfer
spending, as well as a number of macroeconomic and demographic variables.
They found that such indicators as the unemployment rate, the elderly population
and GDP per capita all affect the poverty rate. However, they suggest that the
most important and effective tool for ghting poverty is social spending.
Countries may provide universal or means-tested social benets depending on
the welfare model. Universal social protection means that the entire population
of a country (regardless of economic or socio-demographic characteristics) is
granted a guaranteed minimum income or consumption level and access to
basic services. On the other hand, targeted social support refers to the process
when public resources are focused on a target group of population, identied
on the basis of certain criteria, such as income or vulnerability (Hujo & Gaia,
2011).
A review of studies on the relationship between social spending and poverty
reduction in EU and non-EU countries is provided in this article below.
3. Relationship between social transfers and poverty reduction
A number of studies conducted over the past two decades have found that there is
a strong negative correlation between poverty and social transfers. It means that
countries with a higher level of social expenditure are likely to have lower poverty
rates (Caminada & Goudswaard, 2009; Forster & d’Ercole, 2005; Anderson et al.,
2018; Kim, 2000; Leventi et al., 2018). Public spending affects poverty reduction
in several ways: it can raise the overall growth performance of the economy, and
it can increase the chance of the poor to contribute to the growth process (mainly
by strengthening human capabilities and reducing transaction costs). Government
social spending may also have positive impacts on growth and poverty reduction
by improved provision of social services, public goods spending, and better
infrastructure access (Wilhelm & Fiestas, 2005).
However, despite the strong negative correlation between poverty and social
expenditures, it should be noted that the impact of government spending on
poverty may vary according to the sector of spending, how well it is targeted,
and the way in which it is nanced. The effect may also differ according to the
time period of analysis, since some types of spending have direct, immediate
impacts on poverty (e.g., transfers and subsidies), while others only have
more indirect, medium-term effects (e.g., health, education, and infrastructure

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spending) (Anderson et al., 2018). Caminada and Goudswaard (2009) found
that the effect of public spending on poverty is less strong in EU countries
compared to non-EU-15 countries. Celikay and Gumus (2017) found that in
the short run there is a negative relationship between social expenditure and
poverty, but in the long run there exists a positive correlation between social
expenditure and poverty.
In Table 1, we provide the review of the studies that focus on the relationship
between social spending and poverty reduction.
Table 1. Studies focusing on the relationship between social spending and poverty
reduction
Authors Aim/Methodology Main results
Leventi, C.;
Sutherland, H.
& Valentinova
Tasseva, I. (2018)
The authors examined how
income poverty is affected by
changes to the scale of tax-
benet policies and which are
the most cost-effective policies
in reducing poverty or limiting
its increase in seven diverse
EU countries.
The researchers found that
the most preferred options
in terms of poverty reduction
cost-effectiveness were child
benets and social assistance.
Anderson, E.;
M. d’Orey, A. J.;
Duvendack, M.
& Espositoa, L.
(2018)
The authors carried out a
meta-regression analysis
of the relationship between
government spending and
income poverty, with a focus
on low- and middle-income
countries.
The authors found no
clear evidence that higher
government spending had
played a signicant role in
reducing income poverty in low-
and middle-income countries.
The authors concluded that
scal policy plays a much
more limited redistributive
role in developing countries,
in comparison with OECD
countries.
Celikay, F. &
Gumus, E. (2017)
The authors analysed the
relationship between social
expenditure and poverty in
Turkey. The authors used panel
error correction models and
employed Turkish statistical
territorial units data (26
regions) covering the period
2004–2011 in the analysis.
The authors have found that
in the short run, there is a
negative relationship between
social expenditure and poverty.
The authors obtained a
negative relationship between
education expenditure and
poverty, both in the short run
and in the long run.

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Authors Aim/Methodology Main results
Lustig, N.;
Pessino, C. &
Scott, J. (2016)
The authors analysed the
impact of taxes and social
spending on inequality and
poverty in Latin American
countries. The method of
standard scal incidence
analysis using a comparable
methodology was implemented.
The authors found that direct
taxes and cash transfers
reduce inequality and poverty
by nontrivial amounts in
Argentina, Brazil, and Uruguay,
less so in Mexico and relatively
little in Bolivia and Peru. The
authors also conclude that in-
kind transfers in education and
health reduce inequality in all
countries by considerably more
than cash transfers.
Notten, G. &
Guio, A. C. (2016)
The authors aimed to
determine the degree to which
social transfers reduce material
deprivation using a simulation
method. The method was
applied to pre-recession and
post-austerity EU-SILC data for
Germany, Greece, Poland and
the United Kingdom.
The authors found that a 1%
income transfer reduces the
number of material deprivations
by an order of 0.51% in
Germany, 0.43% in Greece,
0.40% in Poland, and 0.33% in
the United Kingdom.
Caminada, K. &
Goudswaard, K.
(2010)
The authors performed a
cross-national analysis of
the relationship between
(public and private) social
expenditures and poverty
reduction through transfers and
taxes.
The authors found that each
percentage point of social
expenditure alleviates poverty
in both EU-15 and non-EU-15
on average by 0.7 percentage
points.
Caminada, K. &
Goudswaard, K.
(2009)
The authors analysed the
effectiveness of social transfers
in alleviating poverty by
focusing on EU-15 countries
and some OECD countries.
The authors found that social
spending is an important
determinant of a country’s
poverty outcome, especially
among the elderly, when
pensions are considered as
transfers.
Wilhelm, V. &
Fiestas, I. (2005)
The study explored how the
composition of public spending
and the manner in which the
public resources are spent may
have affected the ability of poor
people to connect to growth in
the 1990s.
The study found that in a period
of declining overall spending
in per capita terms, spending
increased most signicantly in
non-productive sectors (except
for education).
Source: Composed by the authors

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Despite the multiplicity of the studies, there appears to be little research on
what particular types of social spending contribute most to the reduction of
poverty in EU countries. The present study builds on the existing literature to
statistically test how the composition and the extent of social spending affect
poverty reduction in EU countries.
4. Research methodology
In this article, social expenditures are dened as social protection expenditures
which include eight main types of social risks according to the ESSPROS
classication: disability, sickness/health care, old age, survivors, family/
children, unemployment, housing, social exclusion. According to Eurostat
methodology, expenditures on social protection include social benets, which
consist of transfers in cash or in kind, administration costs, and other expenditure
(payment of property income and other).
Statistics on income and living conditions (EU-SILC) methodology is used to
identify the poor. An individual is considered to be at risk of poverty when he or
she lives in a household whose total equivalised income is below the at-risk-of-
poverty threshold, dened as 60% of the national median equivalised income.
In order to assess the linkages between social transfers and variation of poverty
rates, Eurostat data for the years 2008 to 2016 are used in the analysis (N = 252).
There are three main indicators used to measure changes in the at-risk-of-
poverty rate before and after social transfers:
1) The difference between the at-risk-of-poverty rate before and after
social transfers (in percentage points) which is indicative of an absolute
antipoverty effect.
2) A percentage change in the poverty rate after social transfers compared to
the at-risk-of-poverty rate before social transfers, which is indicative of a
relative antipoverty effect.
3) Public policy effectiveness on poverty alleviation is calculated based on the
methodology introduced by Caminada and Goudswaard (2010). Following
this methodology, absolute antipoverty effects are rst calculated for each
country. Then absolute antipoverty effects are divided by social spending
ratios (as a percentage of GDP) to see which country targets poverty best per
one point of GDP spent on social expenditure (Caminada & Goudswaard,
2010, p. 6).

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It should be noted that pensions are excluded from measuring antipoverty effects
(absolute and relative) in this article. Account is taken of the EC’s position
whereby pensions “are considered primary income since their role is not only
to redistribute resources across income groups but also, and primarily, over the
life-cycle of individuals and/or across generations” (Joint Report 6694/07, p. 25).
It is important to mention that the depth of the analysis in the article was
constraint by the limited availability of comparable data on poverty rates and
public spending. It was important to use the indicators that were calculated
using a similar (in our case, Eurostat) methodology. For this reason, only 28
EU countries were included in the analysis. Furthermore, the literature analysis
has showed that cross-country regressions and computable general equilibrium
(CGE) models are the most common tools used to establish the links between
expenditure components and poverty reduction. However, CGE models are
technically demanding and data-intensive as well as structural parameters are
difcult to estimate (Wilhelm & Fiestas, 2005). For this reason, in order to
assess the relationship between relative antipoverty effects with different types
of social protection expenditure, the Spearman correlation was calculated and
a linear regression analysis was carried out. The regression analysis used the
indicator of relative antipoverty effect, as it allows a more accurate gauging of
changes in at-risk-of-poverty rates before and after social transfers.
5. Impact of social transfers on poverty in EU countries
Absolute antipoverty effects are shown in Figure 1. As we can see, social
transfers reduce the percentage of people at risk of poverty in all the countries,
however to a very different extent. The largest reduction is seen in Ireland and
Scandinavian countries (Finland, Sweden and Denmark), while Italy, Romania
and Greece demonstrate the lowest reduction.
As shown in Figure 2, results are similar in calculating relative antipoverty
effects. The highest percentage reduction is recorded in Finland (56.9%), Ireland
(52.6%) and Denmark (51%). The share of people at risk of poverty after social
transfers decreased by more than half in those countries, while Greece exhibited
only a 15.8% reduction.

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Figure 1. Absolute antipoverty effect in EU countries in 2017 (pensions excluded from
social transfers), %
However, the analysis above does not say anything about the amount of
expenditure on social protection in different EU countries. It could be that
countries exhibiting the greatest poverty alleviation also have the highest
expenditure on social protection. In order to determine the countries which are
the most effective in alleviating poverty, it is appropriate to measure public
policy effectiveness on poverty alleviation across Member States (Table 2).
When we rank countries according to their effectiveness in combating poverty
(Table 2, column 7), Ireland appears to stand out in its effectiveness. In this
country, each percentage point of social expenditure reduces poverty by 1.15
percentage points. Although Ireland’s spending on social protection as a
percentage of GDP is one of the lowest in the EU, its absolute antipoverty effect
of social transfers is the highest among the EU-28 countries, meaning that social
transfers in this country reach the most vulnerable population groups. According
to Heady et al. (2001), Ireland’s high effectiveness in alleviating poverty has
been determined by a combination of the high proportion of means-testing in
Ireland’s social transfers.
Other countries demonstrating sufciently high effectiveness in alleviating
poverty include Hungary (0.59), Finland (0.48), Luxembourg (0.48), the United

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Kingdom (0.47), and Cyprus (0.47). The lowest effectiveness is observed in
Greece and Italy (0.15 and 0.19 percentage points, respectively), although, as
seen in Table 2 (column 6), the latter countries spend considerably more on
social protection (as a percentage of GDP) compared to Hungary or Ireland.
It is important to mention that within the group of the EU-28 countries, a
statistically signicant relationship has been found between levels of social
expenditure and antipoverty effect (both absolute and relative) of social
expenditure. This supports the ndings of the abovementioned empirical
studies showing that the higher the social expenditures, the more noticeable the
antipoverty effect (Table 3).
Figure 2. Relative antipoverty effect in 2017 (pensions excluded from social
transfers), %

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Table 2. Targeting effect of social expenditure on poverty reduction in EU-28 in 2016
At-risk-of-poverty rate
before social transfers
(pensions excluded from
social transfers) (2016)
At-risk-of-poverty rate
before social transfers
(pensions included in
social transfers) (2016)
At-risk-of-poverty rate
(cut-off point: 60% of
median equivalised
income after social
transfers) (2016)
Effect of social transfers
– the difference between
at-risk-of-poverty rate
before and after social
transfers (percentage
points)
Social protection
expenditu-re, % of GDP
(2016)
Targeting effect – Public
Policy Effectiveness on
Poverty Alleviation
(2016)
1 2 3 4 5 6 7 8
1 - 3 2 - 3 4 / 6 5 / 6
Belgium 26.3 44.2 15.5 10.8 28.7 29.8 0.36 0.96
Bulgaria 27.9 45.6 22.9 5 22.7 17.5 0.29 1.30
Czechia 16.3 36.5 9.7 6.6 26.8 18.9 0.35 1.42
Denmark 24.9 40.3 11.9 13 28.4 31.6 0.41 0.90
Germany 25.3 43.5 16.5 8.8 27 29.4 0.30 0.92
Estonia 28.9 39.6 21.7 7.2 17.9 16.6 0.43 1.08
Ireland 34.7 44.6 16.6 18.1 28 15.8 1.15 1.77
Greece 25.1 52.9 21.2 3.9 31.7 26.6 0.15 1.19
Spain 29.5 46.8 22.3 7.2 24.5 24.3 0.30 1.01
France 23.5 45.1 13.6 9.9 31.5 34.3 0.29 0.92
Croatia 27.3 44.8 19.5 7.8 25.3 21.3 0.37 1.19
Italy 26.2 46.5 20.6 5.6 25.9 29.7 0.19 0.87
Cyprus 25.0 38.3 16.1 8.9 22.2 19.1 0.47 1.16
Latvia 27.8 40.2 21.8 6 18.4 15.2 0.39 1.21
Lithuania 27.9 42.1 21.9 6 20.2 15.4 0.39 1.31
Luxembourg 27.1 44.4 16.5 10.6 27.9 22.0 0.48 1.27
Hungary 25.8 47.7 14.5 11.3 33.2 19.2 0.59 1.73
Malta 23.8 37.9 16.5 7.3 21.4 16.7 0.44 1.28
Netherlands 22.0 38.5 12.7 9.3 25.8 29.5 0.32 0.87
Austria 26.3 44.8 14.1 12.2 30.7 30.3 0.40 1.01
Poland 22.7 43.5 17.3 5.4 26.2 20.3 0.27 1.29
Portugal 25.0 46.1 19.0 6 27.1 25.2 0.24 1.08
Romania 29.4 49.5 25.3 4.1 24.2 14.6 0.28 1.66
Slovenia 24.3 41.2 13.9 10.4 27.3 23.3 0.45 1.17
Slovakia 18.4 37.9 12.7 5.7 25.2 18.4 0.31 1.37
Finland 27.0 43.7 11.6 15.4 32.1 31.8 0.48 1.01
Sweden 29.8 45.0 16.2 13.6 28.8 29.6 0.46 0.97
United
Kingdom
28.1 42.7 15.9 12.2 26.8 26.2 0.47 1.02
EU-28 25.9 44.5 17.3 8.6 27.2 28.1 0.30 0.96
Calculations based on Caminada and Goudswaard’s (2010) methodology.
Data source: Eurostat ([spr_exp_sum], [ilc_li02], [ilc_li09b], [ilc_li10b])

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Table 3. Correlation between levels of social expenditure and antipoverty effects of
social expenditure (Spearman’s rho)
Absolute antipoverty
effect
Relative antipoverty
effect
Social protection
expenditure, percentage
of GDP
(2008–2016, N = 249)
0.493** 0.486**
Social protection benets,
percentage of GDP
(2008–2016, N = 249)
0.494** 0.486**
Social protection benets,
PPS per inhabitant
(2008–2016, N = 249)
0.586** 0.592**
** Correlation is signicant at the 0.01 level (2-tailed).
We carried out correlation and regression analyses to identify the particular
types of social expenditure that are the most effective in alleviating poverty
in EU countries. Table 4 illustrates the correlation between the absolute and
relative effect of social transfers on poverty reduction and different types of
social transfers. As shown, the absolute antipoverty effect appears to have the
strongest correlation with family/children and housing expenditure. The relative
antipoverty effect is found to have the strongest correlation with family/children
and social exclusion expenditure.
The Eurostat’s database also contains data for composite variables ‘Sickness,
health care and disability expenditure’ and ‘Housing and social exclusion
expenditure’. It is interesting to note that the linkages between the composite
variables and absolute/relative antipoverty effects demonstrate considerably
higher correlation coefcients compared to the correlation coefcients between
the original variables (Table 4). However, since our aim was to identify which
type of social expenditures has the strongest inuence on the relative antipoverty
effect in the regression analysis we will use separate variables.
As it was mentioned, in order to identify the inuence of social expenditures on
the relative antipoverty effect, the linear regression analysis was used. Before
the linear regression analysis, the linearity patterns between dependent and all
independent variables were checked using scatter plots (Fig. 3).

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Table 4. Correlation between the effect of social transfers on poverty reduction and
different types of social transfers (Spearman’s rho)
Percentage of GDP, 2013–2016
Sick-
ness/
Health
care
expendi-
ture
Disability
expendi-
ture
Old age
expendi-
ture
Survi-
vors
expendi-
ture
Family/
Children
expendi-
ture
Un-
employ-
ment
expendi-
ture
Housing
expendi-
ture
Social
ex-
clusion
expendi-
ture
Absolute
antipoverty
effect
(2008–2016,
N = 249*)
0.519** 0.488** 0.120 -0.130*0.689** 0.404** 0.550** 0.526**
0.590** 0.747**
Relative
antipoverty
effect
(2008–2016,
N = 249*)
0.524** 0.430** 0.121 -0.155*0.619*0.389** 0.496** 0.555**
0.588** 0.753**
* Exceptions: Housing expenditure N=166, Social exclusion expenditure N=247.
** Correlation is signicant at the 0.01 level (2-tailed).
The variables and characteristics of the initial and nal models are presented in
Table 5. The nal model includes three independent variables—social exclusion
as a percentage of GDP, family/children expenditure as a percentage of GDP, and
sickness/healthcare expenditures as a percentage of GDP—that are statistically
signicant at the 0.01 level. The nal model’s equation is:
Relative antipoverty effect of social transfers = 7.360 + 9.419*social
exclusion expenditure as % of GDP + 6.623*family/children
expenditure as % of GDP + 1.824*sickness and healthcare
expenditure as % of GDP + e
The nal model’s equation shows that social exclusion expenditure exhibits
the highest effect on poverty reduction in EU countries. Any 1% increase in
social exclusion expenditure as a percentage of GDP leads to a 9.4% increase
in relative antipoverty effect of social transfers when all other variables are
held constant in the model. Effects of family/children expenditure and sickness
and healthcare expenditure on poverty reduction are considerably lower but
nonetheless statistically signicant. According to Eurostat methodology, social
exclusion expenditures include targeted spending on social exclusion which is
not covered by other types of expenditure. As we can see, this type of social

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Sandra Krutulienė
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Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
Figure 3. Correlation between relative antipoverty effect and different types of social
expenditure

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Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
expenditure contributes most to poverty reduction. Since families with children
tend to be at risk of poverty more often compared to families without children
(according to Eurostat, in 2017, at-risk-of-poverty rate among families with
three or more dependent children was 26.9%, while the same indicator among
families without dependent children constituted only 11.1% in EU-28) family/
children expenditure also has a major impact on poverty reduction.
Table 5. Relative antipoverty effect variables (characteristics of linear regression)
Initial Model Final Model
Dependent variable:
Relative antipoverty effect
Regressors (independent variables)
Social exclusion expenditure
as a percentage of GDP
6.027*
0.003**
9.419
0.000
Family, children expenditure
as a percentage of GDP
5.515
0.000
6.623
0.000
Sickness, healthcare expenditure
as a percentage of GDP
1.054
0.021
1.824
0.000
Unemployment expenditure as a percentage
of GDP
1.325
0.101
Housing expenditure as a percentage
of GDP
0.465
0.874
Disability expenditure as a percentage
of GDP
-0.268
0.819
Constant 17.106 7.360
R square 0.442 .560
Adjusted R square 0.421 .554
N 164 247
* Unstandardized Coefcients B, ** p value.
The research ndings unambiguously reveal the interrelationship between social
expenditure and poverty. Actually all types of expenditure on social protection
(except old age expenditure) correlate with relative antipoverty effects
(survivors expenditure correlation is extremely weak), but social exclusion
expenditure, family/children expenditure and sickness/healthcare expenditure
have signicant effect on poverty reduction.
As the study examined the time period from 2008 to 2016, covering quite
different periods of economic cycle (economic crisis and economic upturn), a

172
Rasa Miežienė
Sandra Krutulienė
Baltic Journal of European Studies
Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
further regression analysis was conducted for the periods 2008–2012 (economic
downturn) and 2013–2016 (economic recovery period) to check whether the
efciency of social spending varies depending on the phase of the economic
cycle. It should be noted that the regression models obtained did not differ
substantially and showed that the relative antipoverty effect is inuenced by
the same factors—social exclusion expenditure, family/children and sickness/
healthcare expenditure.
6. Conclusions
The analysis has shown that social transfers are an effective tool for poverty
reduction in EU countries. Social transfers reduce the percentage of people at
risk of poverty in all the countries, however to a very different extent. If we
analyse absolute and relative antipoverty effects, we may see that Ireland and
Scandinavian countries (Finland, Sweden and Denmark) demonstrate the largest
reduction, while the lowest reduction is seen in Italy, Romania and Greece.
Similar results have been obtained from calculations of the indicator of public
policy effectiveness on poverty alleviation across EU countries, showing which
country targets poverty best per one percentage point of GDP spent on social
expenditure. Basing the calculations on this indicator, the countries found to be
most effective in alleviating poverty are Ireland (in this country, each percentage
point of social expenditure reduces poverty by 1.15 percentage points), Hungary
(0.59), Finland (0.48), and the United Kingdom (0.47). The indicator of public
policy effectiveness on poverty alleviation is the lowest for Greece, Italy and
Portugal.
The research has conrmed the ndings from previous studies that there exists
a statistically signicant relationship between levels of social expenditure
and antipoverty effects of social expenditure. Countries with higher social
expenditure exhibit higher antipoverty effects (both absolute and relative).
A strong correlation can be seen between social protection benets (PPS per
inhabitant) and antipoverty effects, showing that increasing social protection
benets are also increasing the difference between at-risk-of-poverty rates
before and after social transfers.
Based on the regression analysis, social exclusion expenditure has been found
to be the most important predictor of the relative antipoverty effect of social
transfers. Even a small increase in the social exclusion expenditure rather

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The Impact of Social Transfers on Poverty Reduction in EU Countries
Baltic Journal of European Studies
Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
signicantly amplies the relative antipoverty effect of social transfers. Effects
of family/children expenditure and sickness/healthcare expenditure on poverty
reduction are considerably lower but nonetheless statistically signicant. The
analysis yielded the same results for different phases of economic cycle—
economic downturn (2008–2012) and economic recovery (2013–2016).
It should be noted that this antipoverty effect analysis is limited to the effects
of different types of social protection expenditures on changes in poverty
rates after social transfers and excludes other variables likely to have effects
on poverty rates, for example GDP growth, employment, the share of older
people in populations, etc. Inclusion of more variables in the analysis is likely
to make some adjustments in the ndings of the regression analysis. Despite the
study limitations, the regression analysis allowed the identication of the most
important types of expenditure on social protection having effects on poverty
variations.
The analysis has also set a framework for further research. Due to the limited
scope of the paper it was not possible to analyse how other variables (e.g.,
duration of the spending in the specic type of social expenditure) may impact
the poverty reduction. Further research could also include the analysis of social
spending and anti-poverty effects in a broader context in different EU countries
in order to identify why some countries are more effective in reducing poverty
than others.
RasaMiežienė is a senior researcher at the Lithuanian Social Research Centre, Labour
Market Research Institute. Her research interests include labour market policy, working
conditions, living standards, and poverty measurement. Since 2006, she has been working
as a national correspondent for the European Foundation for the Improvement of Living
and Working Conditions.
Sandra Krutulienė is a doctor of social sciences (sociology), currently working as
researcher at the Lithuanian Social Research Centre, Labour Market Research Institute.
Her research interests include social welfare and employment policy, labour market, working
conditions, the situation of vulnerable groups under different types of welfare states, and
quality of life research.

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Tallinn University of Technology (ISSN 2228-0588), Vol. 9, No. 1 (26)
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