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Causal pathways of intergenerational poverty transmission in selected EU countries

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The paper investigates whether, in what way and to what extent the family of origin affects offspring’s poverty risk in selected EU countries representing different social protection systems. Employing logit models and utilizing EU-SILC data, the analysis brings to the forefront the importance of social protection for intercepting the intergenerational transmission of poverty. Denmark with the socialdemocratic welfare state is the most successful in mitigating the effect of the family of origin on offspring’s poverty risk, followed by France representing the conservative-corporatist welfare regime. Less effective οn this matter appear to be Greece and Great Britain representing the south-European and the liberal social protection system respectively
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Social Cohesion and Development
Vol. 12, 2017
Causal pathways of intergenerational poverty
transmission in selected EU countries
Papanastasiou Stefanos Democritus University of
Thrace
Papatheodorou Christos Panteion University
http://dx.doi.org/10.12681/scad.15941
Copyright © 2018 Stefanos Papanastasiou,
Christos Papatheodorou
To cite this article:
Papanastasiou, S., & Papatheodorou, C. (2018). Causal pathways of intergenerational poverty transmission in selected
EU countries. Social Cohesion and Development, 12(1), 5-19. doi:http://dx.doi.org/10.12681/scad.15941
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Articles | Άρθρα
Causal pathways of intergenerational poverty
transmission in selected EU countries
Stefanos Papanastasiou, Democritus University of Thrace
Christos Papatheodorou, Panteion University
Αιτιώδεις διαδροµές της διαγενεακής µεταβίβασης
της φτώχειας σε επιλεγµένες χώρες της ΕΕ
Στέφανος Παπαναστασίου, ∆ηµοκρίτειο Πανεπιστήµιο Θράκης
Χρίστος Παπαθεοδώρου, Πάντειο Πανεπιστήµιο
ΠΕΡIΛΗΨΗ
Το άρθρο διερευνά εάν, µε ποιο τρόπο και σε ποιο
βαθµό η οικογένεια προέλευσης επηρεάζει τον κίνδυ-
νο φτώχειας των απογόνων σε επιλεγµένες χώρες της
ΕΕ που αντιπροσωπεύουν διαφορετικά συστήµατα
κοινωνικής προστασίας. Κάνοντας χρήση logit µοντέ-
λων και αξιοποιώντας µικροδεδοµένα από την EU-
SILC, η ανάλυση αναδεικνύει τη σηµασία της κοινω-
νικής προστασίας για την αναχαίτιση της διαγενεακής
µεταβίβασης της φτώχειας. Η ∆ανία µε το σοσιαλδηµο-
κρατικό κράτος πρόνοιας είναι η πιο επιτυχηµένη στην
άµβλυνση της επίδρασης της οικογένειας προέλευσης
στον κίνδυνο φτώχειας των παιδιών, ακολουθούµενη
από την Γαλλία που αντιπροσωπεύει το συντηρητικό-
κορπορατιστικό καθεστώς ευηµερίας. Λιγότερο αποτε-
λεσµατικές σε αυτό το ζήτηµα εµφανίζονται η Ελλάδα
και η Μεγάλη Βρετανία που αντιπροσωπεύουν το νοτι-
οευρωπαϊκό και το φιλελεύθερο σύστηµα κοινωνικής
προστασίας αντίστοιχα.
ΛΕΞΕΙΣ-ΚΛΕΙ∆ΙΑ:
Φτώχεια, διαγενεακή κινητικό-
τητα, διαγενεακή µεταβίβαση φτώχειας, γονεϊκό
υπόβαθρο, κοινωνική προστασία, καθεστώτα ευ-
ηµερίας, ΕΕ.
ABSTRACT
The paper investigates whether, in what way
and to what extent the family of origin affects
offspring’s poverty risk in selected EU coun-
tries representing different social protection
systems. Employing logit models and utiliz-
ing EU-SILC data, the analysis brings to the
forefront the importance of social protection
for intercepting the intergenerational trans-
mission of poverty. Denmark with the social-
democratic welfare state is the most success-
ful in mitigating the effect of the family of
origin on offspring’s poverty risk, followed by
France representing the conservative-corpo-
ratist welfare regime. Less effective οn this
matter appear to be Greece and Great Brit-
ain representing the south-European and the
liberal social protection system respectively.
KEY WORDS:
Poverty, intergenerational mo-
bility, intergenerational poverty transmis-
sion, parental background occupation social
protection welfare regimes, EU.
Κοινωνική Συνοχή και Ανάπτυξη 2017 12 (1), 5-19
Social Cohesion and Development 2017 12 (1), 5-19
1. Introduction
This paper delves into the aspect of the causal dynamics by which poverty is transmitted from
parents to children. The aim is to investigate whether, in what way and to what extent the
family of origin affects children’s probability of falling below the poverty threshold in adulthood in
selected EU countries (Denmark, France, Great Britain and Greece). These countries represent differ-
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[6] ΚΟΙΝΩ ΝΙΚΗ ΣΥΝ ΟΧΗ Κ ΑΙ ΑΝΑΠΤ ΥΞΗ
ent welfare regimes according to the dominant debate on the welfare state typologies in the EU.
Thus, any systematic cross-national differences in the family background effect on adult’s poverty
risk can be attributed to the different institutional arrangements of the social protection systems.
The paper draws upon and advances earlier work carried out by Papanastasiou and Papatheo-
dorou (2010) and Papatheodorou and Papanastasiou (2010). It deepens the empirical analysis on the
intergenerational transmission of poverty (ITP) in selected EU countries by utilizing the microdata
from the intergenerational module of EU-SILC 2005. By gathering information on the family back-
ground of the respondents when they were 14-16 years of age, this retrospective survey allows for
comparable estimates across the EU countries. This dataset has no information on parents’ income
to investigate the effect of family poverty on children’s poverty, as a conventional study of ITP would
require. Alternatively, parental occupation is used as proxy of the family economic background, as it is
widely recommended in the relevant literature. Thus, offspring’s poverty risk is regressed on parental
occupation along a set of control variables by employing logit models.
The rest of the paper is structured as follows: The next section presents the theoretical back-
ground and summarizes the empirical findings on the causal mechanisms by which poverty is trans-
mitted from one generation to the next. The third section offers a description of the microdata and
other methodological parameters of the paper. The fourth section provides an empirical exploration
of the association between the family of origin and the adults’ poverty risk in the selected EU coun-
tries. The last section is devoted to summarizing and concluding.
2. Background to the study
The causal mechanisms by which poverty is transmitted from one generation to the next have
been characterized as “black box” of ITP because a large part - approximately the half (R2
0.5) - of the involved mechanisms remains obscure up to now (Bowles and Gintis, 2001). The “hu-
man capital” theory has become main tool to understand ITP by social researchers and policymak-
ers. It claims that the intergenerational reproduction of inequalities is due to the deficiency of the
less well-off families’ economic resources to invest in their children’s “quality” (e.g. education) due
to borrowing constraints in economy (Becker and Tomes, 1979; 1986). This approach has had a tre-
mendous impact on the scientific thinking and policy making (as it appears to be consistent with
the Paretian optimality) and, as result, the lion’s share of the anti-poverty funds has been placed
on childcare, education, training and lifelong learning. However, the emphasis placed on “human
capital” as the “great leveler” has seriously been contested by subsequent studies (Card, 1999;
Breen and Goldthorpe, 2001; Erikson and Goldthorpe, 2002; Warren et al, 2002). What is more,
the overly optimistic view of rapid regression to the mean between rich and poor families in the
developed nations, put forward by Becker and Tomes (1986), has been cast into doubt by newer
empirical assessments (Zimmerman, 1992; Solon 1989, 1992, 1999; Mazumder, 2001).
Furthermore, a popular belief among a group of social researchers and policymakers is that
the intergenerational inequalities are due to the cultural and behavioral traits of the poor. This
view draws upon the concepts of the “culture of poverty” (Lewis, 1965, 1969) and the “culture of
welfare dependency” (Murray, 1984; Mead, 1986, 1992), which ascribe poverty to dysfunctional
values, attitudes and behaviors of the poor. However, this view has attracted fierce criticism for its
incapacity to take account of structural and institutional aspects of poverty. The criticism is leveled
at the explicit blaming of the poor that tends to depoliticize the social problem of poverty, as eve-
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SOCIA L CO HESI ON AN D DE VELO PMEN T [7]
ryone is led to believe that poverty is associated with individual values and behaviors, rather than
structural factors of modern societies (Papatheodorou and Papanastasiou, 2017).
Similarly, a group of social researchers and policymakers has turned the discussion on ITP to
the idiosyncratic features of the poor. This view rests on empirical studies in which the cognitive
(Herrnstein and Murray, 1994; Saunders, 1996; 1997) and/or non-cognitive abilities (Heckman and
Rubinstein, 2001; Heckman and Carneiro, 2003; Heckman et al, 2006) appear to greatly predict
future attainments. Yet, these studies fail to capture the broader interactions of individual idiosyn-
crasy with the family and the societal milieu. Research suggests that 60% of the variance in IQ in
poor families is accounted for by socioeconomic factors, while the contribution of genes is close to
zero (Turkheimer et al, 2003).
A more radical approach on ITP is taken by social researchers, who emphasize the political
economy of capitalism (Myrdal, 1962; Wilson, 1987; Hariss-White, 2005). By political economy is
meant the approach that considers society as a field of conflict between antagonistic social groups
and classes (Papatheodorou and Papanastasiou, 2017). Thus, the inequalities produced and repro-
duced by capital accumulation, segregated labor markets, institutional discrimination, residual
social protection, etc. have been identified as main determinants of ITP. The political economy
approach offers some important conceptual tools to understand the causes of ITP, such as the inter-
play between economy and politics and the ensuing power relations, which appear to be lacking
from major theoretical schemes embracing a rather individualistic approach towards ITP.
There have been numerous empirical studies on ITP (for an overview see d’ Addio, 2007;
Jenkins and Siedler, 2007a). Here the attention is on those studies examining the effect of family
poverty on offspring’s future outcomes. Most of the empirical studies suggest that growing up in
a poor family raises the probability of falling below the poverty threshold in adulthood (Corcoran,
1995; Corcoran and Adams, 1997; Airio et al, 2004; Musick and Mare, 2004; Blanden and Gregg,
2004; Blanden, 2006; Blanden and Gibbons, 2006; Bellani and Bia, 2013; Serafino and Tonkin,
2014). A strand of empirical studies examines the effect of childhood poverty on individual attain-
ment in terms of education, occupation and income or wage. The empirical findings suggest there
is a pronounced negative association between childhood poverty and individual attainment (Have-
man and Wolfe, 1994; Haveman et al, 1997; Teachman et al, 1997; Ermisch et al, 2001). Moreover,
the empirical findings suggest that childhood poverty is associated with more pronounced dimin-
ishing outcomes, the longer one lives in it (Haveman et al, 1997; Teachman et al, 1997).
Papatheodorou (1997) and Papatheodorou and Piachaud (1998) offer estimates of the influence
of the family of origin on offspring’s poverty risk by utilizing microdata from a Greek study carried out
in 1988. Using parental occupation and education as proxies of the family background, the authors find
out that the poverty risk is affected directly by parental occupation and indirectly by parental education
through the effect the latter has on children’s education. Moreover, Papanastasiou and Papatheodorou
(2010), Papatheodorou and Papanastasiou (2010) and Papanastasiou et al (2016) found evidence of
extensive ITP in south European countries contrary to northwestern countries (and especially the Nordic
ones). The patterning in ITP outcomes across the EU that was found by those researchers leads to a
clustering of countries based on distinct and longstanding welfare states (Esping-Andersen, 1990; Lieb-
fried, 1993; Ferrera, 1996.) As also several studies have shown, the cross-country differences in poverty
and inequality in the EU are largely attributed to the social protection system that each member-state
has developed (Papatheodorou and Petmesidou, 2004; 2005; Papatheodorou et al, 2008; Dafermos
and Papatheodorou, 2010; Papatheodorou and Dafermos, 2010; Dafermos and Papatheodorou, 2013).
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[8] ΚΟΙΝΩ ΝΙΚΗ ΣΥΝ ΟΧΗ Κ ΑΙ ΑΝΑΠΤ ΥΞΗ
3. Data and methodology
The standard linear model of ITP can take the following form:
where Y is offspring’s poverty risk, Xi are the individual covariates, Xf are the family covariates, W is
the effect of unobservable individual factors and Z is the effect of unobservable family factors. This
model assumes non-correlation between observed and unobserved effects to produce unbiased coef-
ficients. If this hypothesis is violated, then one should adapt the statistical model with parametric
or non-parametric techniques, albeit none of them can guarantee the complete unbiasedness of the
estimates (see Jenkins and Siedler, 2007b).
Figure 1 delineates the potential causal associations taking place within the ITP process. The
causal pathways of the individuals’ future welfare could be both direct (A) and/or indirect (BC). The
family effect can take three forms: a) monetary and non-monetary investment (e.g. investment in hu-
man capital and incorporation in social networks), b) transmission of norms and values (e.g. transmis-
sion of cultural values and socially acceptable behaviors) and c) transmission of genetic characteristics
(e.g. transmission of cognitive abilities and personality traits) (see Roemer, 2004). As there is no rea-
son to assume any systematic cross-country differences in certain genetic characteristics of individuals
(e.g. IQ), the focus should be on the first two parameters, of which investment can be approximated
by parental occupation and family culture by parental education. The empirical investigation of the
effects A and BC is the subject-matter of this study, whereas preliminary attempts to kick father’s
education into the analysis were hindered by the presence of multicollinearity.
The paper utilizes microdata from the intergenerational module of EU-SILC 2005. This
dataset is preferred over the similar 2011 one because it has available intergenerational weights
for all the countries under consideration. The intergenerational module contains retrospective
information on the family background of the respondents when they were 14-16 years of age.
The retrospective data include parental age, parental occupation, parental education, family
composition and family financial di-stress. Since there is no information on parental income,
there is no possibility to assess the effect of parental income on children’s future outcomes. Still,
parental occupation is considered good proxy of parental permanent income because of its high
correlation with income (Nickell 1982; Erikson and Goldthorpe, 2002; Solon, 2002; Corak, 2006).
Moreover, parental occupation offers some advantages over income because it is relatively stable
over time and, hence, is less susceptible to transitory fluctuations (Nickell 1982; Ermisch and
Francesconi 2002; Zaidi and Zolyomi, 2007; Torch, 2013). In preliminary analyses, the variables of
father’s education and children’s education were considered, but eventually they were dropped
from the model due to multicollinearity issues.
( ) ( ) ( )
      
L N I
L N Q I Q
< ; ; : =
β β β
… …
= + + + +
∑ ∑
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SOCIA L CO HESI ON AN D DE VELO PMEN T [9]
Figure 1: The conceptual model of ITP
The empirical analysis employs binomial and ordered regression to investigate the main research
questions. In the analysis, the poverty risk is the response variable, while father’s occupation, family
structure, number of siblings, father’s age, children’s occupation, sex, age, locality, chronic illness and
degree of urbanization are the explanatory variables.1 The poverty risk is estimated following the well-
known and broadly used EU poverty line of the 60% of the median equivalized disposable income.
The coding of the variables of interest is as follows:
Poverty risk (poor, non-poor)
Father’s occupation (higher skilled non-manual, lower skilled non-manual, skilled or un-
skilled manual)2
Family type (single-parent, two-parent)
Number of siblings3
Children’s occupation (higher skilled non-manual, lower skilled non-manual, skilled or
unskilled manual)4
Gender (male, female)
Age (father’s/child’s)5
Locality (local, non-local)
Chronic illness (chronic, non-chronic)
Degree of urbanization (densely populated, thinly populated).
For comparative purposes, the study investigates ITP in four EU countries, namely Denmark,
France, Greece and Great Britain. These countries represent the four welfare state regimes according
to Esping-Andersen’s (1990) typology and the following debate on the welfare regime of the south-
European countries (Leibfried, 1993; Ferrera, 1996; Papatheodorou and Petmesidou, 2004; 2005).
That is, Denmark, France, Great Britain and Greece represent the social-democratic, the corporatist-
conservative, the liberal and the south-European welfare regime respectively. The choice of these
countries allows us to associate the cross-national differences in the family background effect on the
adults’ poverty risk to the different social protection system that each country has developed. In other
words, it allows us to examine the impact of the welfare state institutions and policies on ITP in the
EU in a highly indirect manner.
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[10] ΚΟΙΝΩ ΝΙΚΗ ΣΥΝ ΟΧΗ Κ ΑΙ ΑΝΑΠΤ ΥΞΗ
4. Empirical analysis
Advancing the methodology developed by Papanastasiou and Papatheodorou (2010) and
Papatheodorou and Papanastasiou (2010), the empirical analysis examines the effect of
family background variables
 
I Q
χ χ χ
= …
on the probability
݌݌߯
or, otherwise,
the risk of children falling below the poverty threshold in adulthood before and after controlling
for a series of individual variables
߯
ൌ ሺ߯
ǡ ǥ ǡ ߯
. The methodological choice is a logit model
in which the binary variable “poor/non-poor” is the response one with values 0 for “failure”
with probability
݌ݕൌ Ͳ݌
and 1 for “success” with probability
݌ݕൌ ͳൌ ͳ െ ݌
. The
poverty risk is computed according to the poverty line of the 60% of the median equivalized
disposable income. The modified OECD equivalence scale is employed to weigh the incomes
of individuals from households with different size and composition. This scale assigns a weight
of 1 to the first adult member of the household, 0.5 to each additional adult and 0.3 to each
child. The logit model is based on the Bernoulli distribution which is a special case of binomial
distribution with number of trials n = 1. The N for each country is chosen based on covariance
patterns to accommodate the goodness-of-fit of the models. The weighting procedure is based
on the available intergenerational cross-sectional base weight in EU-SILC 2005. This is the reason
why the 2005 dataset was chosen in this analysis instead of the 2011 one in which this weight
is missing for some countries (i.e. Denmark and Greece). The results are expressed in odds ratios
for the sake of easier interpretation. Based on the above methodological choices, the logit model
can be summarized as:
where p is the probability (or the risk) of poverty, xf are the family covariates, xi are the individual
covariates and ε is the error term (Hosmer and Lemeshow, 2000; Agresti, 2002; Hilbe, 2009;
Kleinbaum and Klein, 2010).
Table 1 presents the findings from the regression of poverty risk on the family covariates
before controlling for the individual covariates. The focus is on the association between father’s
occupation and adult children’s poverty risk, since father’s occupation is regarded the most
representative variable of the household’s economic situation. The analysis shows that only in
Denmark father’s occupation appears to have no statistically significant effect on the poverty
risk. This finding means that Denmark’s social protection system is probably more effective in
mitigating the effect of the family of origin on children’s poverty outcomes. By contrast, the
effect of father’s occupation on the poverty risk appears to be statistically significant in the other
three countries. However, the above analysis provides only a partial view on the determinants of
children’s poverty when they become adults since there was no control for individual variables.
Therefore, it is important to test whether the direct effect of father’s occupation on the adults’
poverty risk that we found earlier persists after controlling for individual characteristics.
By regressing the poverty risk on parental and individual covariates, it appears that the
direct effect of father’s occupation on offspring’s poverty risk disappears in France altogether
from a statistical point of view (see Table 1). This indicates that the effect of father’s occupation
on the poverty risk that we found earlier may be mediated by individual variables such as
ሺൌ ͳ
ൌ 
ǡǤǤǡ
ǡǥǡ
ǡǥǡ
ǡǥǡ
൅ 
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SOCIA L CO HESI ON AN D DE VELO PMEN T [11]
children’s occupation. In contrast, the direct effect of father’s occupation on the poverty risk
remains statistically significant in Greece and Great Britain even after controlling for individual
background variables. This finding indicates that the countries with south-European or liberal
social protection system respectively are probably less effective in reducing the influence of the
family of origin on children’s future outcomes. The findings suggest there is still no statistically
significant effect of father’s occupation in Denmark as demonstrated earlier. The results also
indicate that the adult’s occupation is a basic determinant of poverty risk in all countries except
Denmark. This country is distinguished because neither father’s nor children’s occupation can
predict the poverty risk. This could be an indication of the effectiveness of the redistributive
mechanisms of Denmark’s welfare state that manage to protect the individuals from poverty
irrespective of the family of origin and individual characteristics.
Table 1: The effect of parental background on offspring’s poverty risk
Poverty risk Denmark France Greece Great Britain
Without individual covariates
Manual (father) .870
(.110)
.832**
(.058)
.662**
(.073)
.678***
(.079)
Lower skilled non-
manual (father)
.890
(.107)
.848**
(.070)
.668***
(.070)
.791**
(.088)
N4290 11548 8269 5880
Poverty risk Denmark France Greece Great Britain
With individual covariates
Manual (father) .912
(.073)
.945
(.071)
.756**
(.090).756**
(.090)
Lower skilled non-
manual (father)
.956
(.059)
.987
(.087)
.794**
(.092)
.830
(.095)
Manual
(child)
.960
(.062)
.636***
(.047)
.571***
(.060).664***
(.068)
Lower skilled non-
manual (child)
(.980)
(.071)
.765***
(.061)
.634***
(.074)
.667***
(.064)
N4090 11176 7191 5772
Control variables: Family structure (not available for Great Britain), number of siblings, father’s age, locality,
chronic illness, child’s age, gender and degree of urbanization.
Reference category: Higher skilled non-manual work (father/child).
The table contains odds ratios and robust standard errors. The constant term is omitted.
*** p<0.01, ** p<0.05, *p<0.10
Source: Elaboration of data from EU-SILC 2005.
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[12] ΚΟΙΝΩ ΝΙΚΗ ΣΥΝ ΟΧΗ Κ ΑΙ ΑΝΑΠΤ ΥΞΗ
Among the above findings, the one that child occupation is a main determinant of poverty
risk in France, Greece and Great Britain gives grounds to assume that there might be a mediating
effect of children’s occupation in the relationship between father’s occupation and poverty
risk. Therefore, it is purposeful to examine whether father’s occupation has a causal effect on
children’s occupational achievement. This analysis makes use of a standard ordered model in
which the coefficients of the explanatory variables do not vary in the cut points k=1, …, m-1
of the response variable. This choice is justified upon the Brant test indicating that there is no
violation of the parallel regression assumption of the standard ordered model (Proportional Odds
Model) for the selected countries. The Proportional Odds Model has children’s occupation as the
response variable with values 1 = “skilled or unskilled manual”, 2 = “lower skilled non-manual”
and 3 = “higher skilled non-manual” with probabilities:
݌ݕൌ ͳܨሺെݔ
ߚ
͕
݌ݕൌ ʹܨሺെݔ
ߚ
ሻ െ ܨሺെݔ
ߚ
where p is the probability of child occupation in the dividing point k, xf are the family covariates,
k are the dividing points 1 and 2 and ε is the error term.
Table 2 confirms that father’s occupation has a statistically significant effect on children’s
occupation in all countries. That is, there is greater probability for children to attain non-manual
compared to manual work when fathers occupy a non-manual position in the occupational
hierarchy, holding all other factors constant. This finding means that, even if there is no direct
effect, father’s occupation can be associated with offspring’s poverty risk in an indirect manner
through children’s occupational achievement, as is the case of France. The indirect effect is evident
in Greece and the UK, but alongside the direct effect shown earlier in Table 1. Papatheodorou
(1997) reaches similar conclusions when it comes to the relationship between father’s occupation
and offspring’s poverty risk. In contrast, it appears there is no mediating effect in Denmark
since, notwithstanding the association between father’s and children’s occupation, there is no
statistically significant effect of child occupation on the poverty risk, as shown earlier in Table
1. All in all, the findings suggest that when studying ITP caution should be given to indirect
channels through which the family background affects children’s poverty risk which may not be
observable or be traceable at first sight.
and
݌ݕ    ܨݔ
ߚ
respectively

௬வ௞
௬ஸ௞
ǡǤǤǡ

This model can be summarized as:
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SOCIA L CO HESI ON AN D DE VELO PMEN T [13]
Table 2: The effect of parental background on children’s occupational attain-
ment
Child occupation Denmark France Greece Great Britain
Manual (father) 3.056***
(0.234)
4.003***
(0.234)
4.443***
(0.327)
3.971***
(0.291)
Lower skilled non-manual
(father)
2.471***
(0.213)
3.703***
(0.183)
3.200***
(0.241)
1.913***
(0.133)
N4103 11253 7212 5799
Control variables: Family structure (not available for Great Britain), number of siblings, father’s age.
Reference category: Higher skilled non-manual (father/child).
The table contains odds ratios and robust standard errors. The constant term is omitted.
*** p<0.01, ** p<0.05, *p<0.10
Source: Elaboration of data from EU-SILC 2005.
5. Conclusion
The aim of this paper was to investigate ITP in the EU by utilizing the EU-SILC 2005
intergenerational microdata. The focus was on the association between the family
background and the risk of children falling below the poverty line in adulthood in four EU
countries representing different welfare state regimes. The emphasis was mainly placed on the
effect of father’s occupation, since it is considered the best proxy of parental socioeconomic
background according to the available information in the EU-SILC 2005 survey. The findings
suggest that father’s occupation is associated with offspring’s poverty risk in differing ways: in
Greece and Great Britain the effect is both direct and indirect, in France it is only indirect, while
in Denmark there is no effect altogether (see Table3). Thus, children’s occupation and, more
generally, children’s attainments appear to be an important mediator that should be considered
in studies of ITP.
Table 3: The effect of parental background on the adults’ poverty risk
Direct Indirect
Denmark - -
France -
Great Britain √ √
Greece √ √
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[14] ΚΟΙΝΩ ΝΙΚΗ ΣΥΝ ΟΧΗ Κ ΑΙ ΑΝΑΠΤ ΥΞΗ
From a social policy perspective, the findings provide insights for the significant impact
that the social protection system and the welfare state institutions have on ITP in the EU. The
findings suggest that Denmark with the social-democratic welfare state is the most successful in
mitigating the effect of the family of origin on adults’ poverty risk, followed by France that repre-
sents the conservative welfare state. Less effective in this matter appear to be Greece and Great
Britain with the south-European and the liberal social protection system respectively. In terms of
policy implications, the results suggest that priority should be placed in breaking the cycle of ITP
through policies that disassociate children’s socioeconomic attainment from the parental back-
ground. Finally, more detailed evidence on the performance of different welfare states on ITP are
of great importance in understanding the mechanisms by which poverty is reproduced over time
as well as in reforming, implementing and evaluating the relevant policies.
Notes
1. In preliminary analyses, we considered the variable of mother’s occupation as explanatory
one, but eventually it was dropped from the analysis due to assortative mating (Rauum et al,
2007) and the cumulative effect with other parental characteristics (Papatheodorou, 1997;
Papatheodorou and Piachaud, 1998).
2. This classification allows for the ordering of parental occupation based on status and re-
muneration. The category higher skilled non-manual refers to managers, professionals and
technicians. The category lower skilled non-manual refers to clerks and service workers. The
category skilled or unskilled manual refers to agricultural and fishery workers, craft workers,
plant and machine operators and unskilled manual workers (see Maitre and Whelan, 2008).
3. The number of siblings is used in numeric format because the association with the poverty
risk is approximately linear.
4. The category of self-employed is left out of the analysis because there are known problems of
reliability along the income dimension which bias the results on the poverty indicator.
5. Age is used in numeric format because the association with the poverty risk is approximately
linear.
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Biographical Notes
Stefanos Papanastasiou, (PhD) studied Social Policy at Democritus University of Thrace (Greece)
and holds an MSc in Applied and Comparative Social Policy from IMPALLA (University of Leuven)
and a PhD from Democritus University. He worked as adjunct lecturer and research associate at
Democritus University (i.e. CESSDA-ERIC). He was researcher at the Observatory of Economic
and Social Developments, Labour Institute, Greek General Confederation of Labour (INE/GSEE)
and at PAF-EAK (a collaboration between INE/GSEE and UADPhilEcon, University of Athens). He
has participated in international scientific conferences and workshops and has been reviewer in
scientific journals. He is experienced in quantitative analysis using microdata. His research interest
and publications are concerned with applied and comparative social policy, social inequality,
poverty, intergenerational mobility and social protection. He has participated and coordinated
research projects in these fields.
Christos Papatheodorou is Professor of Social Policy at the Panteion University, Greece. He is a
graduate in Economics from the University of Athens, and holds an MSc in Social Policy Analysis
from the University of Bath, and a PhD from the London School of Economics and Political Science
(LSE). At the LSE he also conducted postdoctoral research. He was Dean of the School of Social,
Political and Economic Sciences and Professor of Social Policy at the Democritus University of
Thrace, Greece. He was head of the Research Unit “Social Policy, Poverty and Inequalities”,
Labour Institute, Greek General Confederation of Labour. He was a Researcher at the National
Centre for Social Research (Athens), a visiting academic at LSE-STICERD and a visiting professor
at the VU Amsterdam. He is a founder member of the Hellenic Social Policy Association and was
chairman 2010-2011 and a board member 2002-2008. His research interests and publications
are in the fields of political economy of social policy, social and economic inequality, poverty,
macroeconomic environment and social protection, functional and personal distribution of
income. He has participated and coordinated a large number of research projects in the above
fields.
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