Post on 11-Oct-2020
Female Labour Market Participation, Social Policy and the Gender Care Gap. A
Fuzzy-Set Analysis
Barbara Da Roit*, Marcel Hoogenboom* and Bernhard Weicht*
* Faculty of Social Sciences, Utrecht University, the Netherlands
Correspondence address: m.j.m.hoogenboom@uu.nl.
FIRST DRAF: PLEASE DO NOT QUOTE WITHOUT PERMISSION OF THE
AUTHORS
Abstract
In this paper we investigated the relationship between the relative contributions of
women – in comparison to men: the “gender care gap” – to the informal care for their
partners, government care policies and the labour market position of European women.
We analysed the interlinkages between the three factors in thirteen European countries
by applying a research model based on the Fuzzy set/Qualitative comparative analysis
method. We chose this approach in order to be able identify patterns in the relationship
between the three factors, since in the literature it is suggested that none of the factors
alone can explain the presence or absence of the gender care gap. The results of our
analysis suggests that the extent to which countries are confronted with the ageing of
their populations and the (absence of a) policy reactions to this problem are crucial to
understanding the gender care gap in the care for elderly parents in need of care, while
the presence or absence of gendered care attitudes and labour market characteristic play
a relatively minor role.
Keywords:
Elderly care; gender care gap; labour market; social policy; fuzzy-set analysis
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1. Introduction
The gender gap in family caregiving is an established research finding: men tend to
dedicate less time and energy than women to caregiving and to provide specific
gendered types of help. Yet while the genderedness of caregiving has been well
documented in the literature, its explanations are less conclusive. In the literature
roughly three alternative explanations can be distinguished. One explanation seeks the
roots of the “gender care gap” between men and women in (the interiorization of)
gender norms, while a second one explains the gap by pointing to differences between
the positions of men and women on the labour market. Finally, a third type of
explanation relates the gender care gap to (the absence of) welfare state policies.
Following recent claims in literature that the gender care gap should be explained by a
combination of the above mentioned factors, in this paper we use Fuzzy set/Qualitative
comparative analysis (Fs/QCA) (Ragin 2000, Kvist 2007) to identify patterns in the
relationship between gendered care giving for elderly people (75+), labour market
position of men and women and the availability of government care arrangements for
elderly people in thirteen European countries. After discussing the theoretical
background (Section 2) and specifying the methodology of the research (Section 3) we
present our findings (Section 4). Finally, in Section 5 we highlight the contribution of
the research to the debate, its limitations and suggestions for future investigation.
2. Theoretical background
2.1 Gendered division of care
Gendered patterns of care-giving have been of interest for a long time (Neal et al. 1997).
However, these practices have largely been described as representing gender patterns
and cultures and cross-national variations in the gender division of care are often
explained through a focus on normative dimensions of welfare policies which are
themselves mainly based on societal gender cultures (Aboim 2010). It has been
established in the literature that in the context of elder care women fulfil the larger part
of care-giving in most countries. In a cross-national study Bracke et al. (2008) show that
the spouse is the number one caregiver in all age categories and that especially women
fulfil care activities when their partner is ill. While the share of men caring for an
elderly person increases dramatically with age (Kahn et al. 2011, Del Bono et al. 2009,
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Cahill 2000) men’s caring involvement is predominantly linked to spouses (Bracke et
al. 2008). Dahlberg et al. (2007) also confirm that the time spent caring increases with
age, with the highest levels of caring commitment in people aged over 80 years, and that
overall women commit more time to caring than men. The authors also indicate,
however, that men take over a large proportion in later life (caring for their partners), a
time when people have usually left the labour market. Also in the type of care delivered
a gender division can be found. Many studies report that women fulfil more intense,
personal care and often provide also more managerial care (Rosenthal et al. 2007,
Kruijswijk, Da Roit and Hoogenboom, forthcoming) both in countries with a more
equal gender division, such as Sweden (Jegermalm 2006) and countries with a stronger
divide, such as Japan (Hanaoka and Norton 2008) or Italy (Toffanin 2011). In terms of
consequences of caring Rosenthal et al. (2007) report that the provision of care often
leads to increased stress for women while for men care delivery often interferes with
work commitments.
Apart from different gender cultures how can the discrepancy between men and
women’s caring practices be explained? Geist (2005) argues that while occupational
gender segregation, gender differences in wages and workplace authority and the gender
gap in poverty have received widely attention, the factors determining stratification
processes within families have been studied less and that, in particular, an integration of
both perspectives within one framework is missing.
2.2 Structural factors
It has widely been argued that the gendered division of care labour cannot sufficiently
be explained by individual decisions but are rather shaped by structural factors linked to
economic, political and social conditions (Cooke 2006). Several structural factors have
been identified in shaping the gendered division of household labour and care labour.
The access to and the use of long-term care services varies according to health status,
gender and socio-economic position (Portrait et al. 2000). Similarly, in terms of support
for informal carers, Rogero-Garcia and Rosenberg (2011) observe that support (paid and
unpaid) is significantly lower among households with female caregivers and that in
particular the lower educated caregivers receive little outside support. Also Ungerson
(2000) emphasises the importance of economic and structural factors in determining the
distribution of care labour. In particular she argues that gender on its own is not
sufficient as a social category to understand the social division of care. Rather,
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economic inequalities linked to jobs and wages are equally important in creating the
link between labour market inequalities and care inequalities, both between men and
women, and between women from different social economic backgrounds.
Arksey and Morée (2008) identify an important tension between the fact that
several countries introduce policies to increase the participation of disadvantaged
groups on the labour market (such as women and older workers) while at the same time
demanding more from people in terms of care giving. This tension between the demands
of employment and the requirement of caring (see Crompton 2001) carries particular
gendered connotations, in that gender equality is promoted in the context of the labour
market, while the gendered division of care work often remains unchallenged
(MacLeavy 2007). Öun (2012) and Meiko (2010) therefore emphasises the important
role welfare institutions can also play in the household division of labour.
Thus, two structural factors specifically influence the realm of private care
giving and the division of care labour within people’s households: the labour market
conditions and structures and the social policies in place.
2.2.1 The labour market
In the literature so far inequality in the division of housework has often been linked to
labour market inequality where labour market differences are usually seen as
consequences of domestic labour (Geist 2005). This causal relationship is assumed in
much of the literature studying the gendered division of care labour. Jang et al. (2012),
for example, using SHARE data, emphasise that intensive care negatively affects labour
force participation among middle aged women in both northern and southern European
countries. They conclude that introducing further formal arrangements for care which
allow in particular women to share their informal carer’s roles might lead to an increase
in the participation of women in the labour market. Knijn and Kremer (1997) establish a
framework to analyse the relationship between labour market and care obligations,
inherently linked to gendered discussions of care as public or private possibility and
paid or unpaid work. They particularly focus on the development of social policies,
originally designed to ‘liberate people from the obligation to work so that they could
care’ (329). In the context of child care the relationship between the participation in the
labour market and care responsibilities has been studied widely. Ellingsæter and
Gulbrandsen (2007) argue that, in the case of Sweden or Denmark, the development of
well-funded public child care was explicitly linked to the facilitation of mothers’
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employment and gender equality. However, political discourses and policies still remain
to imagine women to be the main provider of informal care (Outshoorn 2002).
Spiess and Schneider (2003) identify a negative relationship for women between
the changes in care giving and changes in working times in European Union countries
arguing that a change in work hours is negatively associated with the beginning of a
care giving period. In their analysis they could not, however, establish a relationship
between the ending of a care giving period, or the reduction of care hours and increasing
labour market participation. The authors argue that this suggests that reductions or
terminations of work due to care giving responsibilities are not compensated later. They
also find important differences between northern European countries and Southern
European countries (including Ireland), linking the consequences of care giving on
working hours to the availability of formal care arrangements.
Similarly, Kotsadam (2011), drawing on data from the ECHP, finds women’s
employment to be negatively associated with care-giving to elderly people. However,
the gendered effects seem to be more negative in Southern European countries and less
negative in the Nordic countries, and in between in the Central European countries. He
demonstrates that not only do women provide more care in Southern European
countries but that also the negative correlation with the probability of being employed
and the number of working hours is stronger. Other authors, however, argue that a
straightforward link between women’s increased labour force participation and
reduction of informal care cannot be observed (Doty et al. 1998), as care responsibilities
are often taken over at times when people have already left the labour force.
In an analysis of the weaker labour market involvement of informal carers in the
UK Henz (2006) concludes that the lower levels of involvement of female carers to the
labour market was predominantly a result of their adaptation to caring. This means that
part-time working women are more likely to leave the labour market than those working
full-time. The reason she finds not in the idea that part-time work is easier to combine
with care obligations but rather that part-time work is seen as marginal work and
temporary work in comparison to full-time work. However, also this link is influenced
by socio-economic differences in that rather working class women reported effects of
caring on their work arrangements. In another contribution Henz (2010) applies a
household-division-of-labour perspective to analyse the distribution of care, showing
that those working full-time provide lower shares of care for their parents with needs
than those who are less strongly attached to the labour market. Henz (2010) argues that
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this effect is not only linked to time constraints of carers but rather higher bargaining
power derived from paid works.
Elsewhere, Henz (2009) argues that in particular for men full-time employment
seems to be a reason not to engage in care. However, also the distribution of fulltime
and part-time work is only one factor in the link between labour market characteristics
and care divisions. Tavora (2012) shows with the case of Portugal that high rates of
female fulltime employment can also be linked to high levels of familialism in the realm
of care. Putten et al. (2010) in a study on the Netherlands find no empirical relationship
between work hours and the provision of support to parents. They therefore argue that
the feared declining support for older people as a result of changing labour market
participation for women cannot be observed in the Netherlands. For men they find a
particularly inelastic relationship between work hours and caring responsibilities (men
do not cut down working hours as a result of supporting parents in need). However, the
Dutch case is particular in the sense that part-time work is widely available and that in
middle age the vast majority of women (and increasingly men) work part-time, which
might enable an easier combination for both men and women of working and caring
responsibilities.
Sarkisian and Gersel (2004) specifically analyse the effects of different
employment characteristics (and differences between men and women) on the gender
gap in helping parents. They find that apart from the crucial factor of having or not
having a job (which in particular counts for women’s availability to care) certain job
characteristics can explain the gender gap. While the analysis suggests that, all things
being equal, employed women and men provide equal amounts of help the authors
strongly emphasise the fact that employment patterns differ significantly and that
therefore, all things are not equal. In particular they identify different wage levels and
the number of self-employed people as defining the gender gap. As higher wages are
typically associated with fewer hours of supporting parents the gender wage gap
translates itself into a gender care gap. Similarly, the fact that fewer women are self-
employed leads to a higher probability to take over the help for parents. Henz (2010)
agrees that spouses do not heavily negotiate the care for their parents but that rather
employment conditions play a crucial role. In particular full-time employment, wage
differences (in particular in low-income households) drive the gender care division (see
also Heitmueller and Inglis 2007). While Sarkisian and Gersel (2004) therefore
recommend that a change in the payment structures of jobs would directly change
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gender divisions in people’s support of their parents, they do not take into account the
role social policies can play in this equation.
2.2.2 Social policies
Social policies can be found in relation to both, labour market and care. Generally social
policies for supporting unpaid care work have developed rather modestly all over
Europe when compared with labour market activation policies (Pascall and Lewis
2004). Bühlmann et al. (2010) argue that a comparative perspective shows that the
division of labour is different in countries with more egalitarian values and that this
shift in values is strongly moderated by welfare policies. These policies are furthermore
linked to equality policies on a broader scale. Fuwa and Cohen (2007) in that context
observe how women’s fulltime employment and higher income has strong effects on the
gender division of housework in countries with greater equality of access policies.
At the same time it is important to pay attention to the fact that policies are also
based on an image of and that they also reproduce images of women and men in certain
social roles (Rake 2001). Hammer and Oesterle (2003) for example, show the
reproductive effect of (social) policies on the gendered division of care labour arguing
that in Austria only for those with higher financial means alternatives of informal care
are accessible, and Morgan and Zippel (2003), demonstrate how paid child care leave
policies are reinforcing the traditional division of care work in people’s homes, also
observed by Kvande and Brandth (2009) in relation to cash for care systems.
The fact that the design of the welfare state and its (care) policies is affecting both
women’s labour force participation (Semyonov 2006) and the gendered division of
informal care labour (Ungerson 2000) requires a framework that links together the
effects of public interventions and policies on both fields of interest (Saraceno and Keck
2011). Therefore the question we aim to answer in this paper is: is there a relationship
between government care policies and the labour market position of European women
on the one hand, and the relative contributions of women (in comparison to men: the
“gender care gap”) to the informal care for partners on the other? And if so, what
patterns between countries can be identified how can these patterns be explained? In
order to be able to investigate the interlinkages between the three factors – gender care
gap, labour market position and social policies – in the next section we will develop a
research model based on the Fuzzy set/Qualitative comparative analysis method which
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enables the identification of patterns in the relationship between the three factors in
thirteen European countries.
3. Methods
In this paper we choose to apply the Fuzzy set/ Qualitative comparative analysis method
(Fs/QCA) in stead of the “classic” quantitative of qualitative approaches for two
connected reasons. First, the Fs/QCA method allows us to discover ‘configurations of
causes’ (Ragin 1994:114). Thus while the literature suggests that individual factors
cannot account for the gender care gap in various European countries, the FS/QCA
method helps to discover combinations of factors producing a certain outcome.
Moreover, the method opens the possibility to find different sets of causal conditions
producing the same outcome, in our case the presence/absence of a gender care gap.
Second, the Fs/QCA method is particularly useful when a limited number of cases in
analyzed, which is mostly the case in welfare state research. In this paper, due to the
limited availability of data only thirteen European countries can be included in the
analysis.
Following the Fuzzy set/ Qualitative comparative analysis method we first
translate “outcome variables” (variables related to the gender care gap) and “condition
variables” (variables related to social policies and labour market) into fuzzy sets that
‘reflect theoretical concepts and analytical constructs’ (Kvist 2007:204). Thus, on the
basis of theoretical considerations we determine the degree to which a case (a country)
belongs to a certain set. For example, on the basis of substantive criteria we decide how
high the score of a country on the indicator must be to be “included” in the set “gender
care gap”. Yet in stead of creating binary “crisp sets” (cases are either “in” or “out”), we
make four-value fuzzy sets with value 1 when a case is “fully in”, 0.67 when a case is
“more in than out”, 0.33 when a case is “more out than in” and 0 when a case is “fully
out of” the set (Rihoux and Ragin 2008: 91).
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Outcome variable: gender care gap
The outcome variable in our analysis is the gender care gap (CAREGAP), which we
define as the difference between the contributions of men and women in the caring for
an elderly parent. The variable is calculated by dividing the proportion of men and
women with at least one non co-resident natural parent caring for mother and/or father
"almost weekly" or more often, by the proportion of men with the same characteristics
(see Annex 1 for the sources and calculation methods). When constructing the fuzzy set
we consider that cases are “fully in” (1) when the value of the outcome variable is
higher than 3, i.e. if women dedicate three times as much time to the caring for their
elderly parents as men (see Table 1). Countries with a score between 1 and 3 are
deemed “mostly in” (0.67), countries with a score between 0 and 1 are considered
“more out than in” (0.33), and countries with a score smaller than 0 are deemed “fully
out” (0) which means that in these countries there is no gender care gap (see Table 1 for
the fuzzy-set score conversion table, and Table 2 for the CAREGAP scores).
fuzzy set score 1 0.67 0.33 0
CAREGAP >3 between 1 and 3 between 0 and 1 <0
EXPSERV >2 between 1 and 2 between 0.5 and 1 <0.5
PTGAP >3 between 2 and 3 between 1 and 2 <1
PAYGAP >20 between 10 and 20 between 2 and 10 <2
CARERES >=0.5 between 0.4 and 0.5 between 0.3 and 0.4 <0.3
GENDCARE > 30 between 20 and 30 between 10 and 20 <10
Table 1: Fuzzy-set score conversion table
Page 9 of 24
Country Gender care gap CAREGAP
Austria 2.8 0.67
Belgium 1.2 0.67
Czech Rep. 0.4 0.33
Denmark 1.1 0.67
France 1.2 0.67
Germany 0.1 0.33
Greece 4.9 1
Italy 1.4 0.67
Netherlands -0.1 0
Poland 4.1 1
Spain 0.1 0.33
Sweden -0.2 0
Switzerland 1.7 0.67
Table 2: The outcome variable: the gender care gap in thirteen European countries, and
the fuzzy set
Condition variables
On the basis of our discussion of the literature in Section 2, we select two clusters of
conditional variables: the labour market position of women relative to men and social
policies aimed at elderly people in a country. Following Sarkisian and Gersel (2004),
Henz (2006) and Heitmueller and Inglis (2007), we use two indicators to measure the
relative position of women to men on the labour market: the “part-time gap” and the
“pay gap”. The part-time gap (PTGAP) is defined as the difference between the part-
time employment rate of women and men aged 50-64, an age category which is most
likely to be active on the labour market while caring for an elderly parent (Dahlberg et
Page 10 of 24
al. 2007). We borrow the condition variable pay gap (PAYGAP) from Eurostat that
defines it as the difference in average wages between men and women. We measure the
level of social policies for elderly people in a country (EXPSERVE) by taking the total
public expenditure on long-term services for non co-resident natural parent as a
proportion of GDP.
In addition to the labour market position of women relative to men and social
policies aimed at elderly people in a country, we selected two extra conditional
variables: problem pressure and gendered care attitude. The variable problem pressure
(CARERES) is included in the analysis since it is likely that the gender care gap
increases when societies are confronted with growing numbers of elderly people due to
the ageing of their populations (Meiko 2010). Finally, the conditional variable gendered
care attitudes (GENDCARE) is included in order to check to what extent the magnitude
of the gender care gap can in a country be attributed to its prevailing attitudes towards
the role of men and women in caring gap (see Table 1 for the fuzzy-set score conversion
table, Table 3 for the scores, and Annex 1 for the sources and calculation methods).
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Gen
dere
d
care
att
itude
s
Fs-v
alue
0.67
0.33 1 0.33
0.33
0.67 1 0.67
0.67
0.33
0.67 0 0.33
Scor
e
20.9
17.0
34.1
13.0
11.6
26.2
35.3
27.7
22.4
16.5
20.6
7.6
16.5
Prob
lem
pres
sure
Fs-v
alue
0.67
0.67
0.33
0.33
0.67
0.67
0.67 1 0.33
0.33 1 0.67
0.67
Scor
e
0.43
0.45
0.31
0.36
0.45
0.45
0.48
0.53
0.34
0.30
0.50
0.43
0.42
Pay
gap
Fs-v
alue
1 0.33 1 0.67
0.67 1 1 0.33 1 0.33
0.67
0.67
0.67
Scor
e
25.5
9.1
23.6
17.7
16.9
23.0
21.5
5.1
23.6
7.5
17.1
17.9
18.7
Part
-tim
e
gap Fs
-val
ue
1 0.33
0.33
0.67
0.67 1 0.33
0.33
0.33 0 1 0.33 1
Scor
e
3.0
1.6
1.1
2.4
2.4
3.9
1.1
1.8
1.6
0.4
3.2
1.8
3.3
Publ
ic
expe
nditu
re
Fs-v
alue
0.67
0.67
0.67
0.67
0.33
0.67 0 0.33 1 0 0.33 1 0.33
Scor
e
1.1
1.7
1.2
1.8
0.7
1.1
0.3
0.9
3.5
0.4
0.6
3.6
0.8
Cou
ntry
Aus
tria
Bel
gium
Cze
ch R
ep.
Den
mar
k
Fran
ce
Ger
man
y
Gre
ece
Italy
Net
herla
nds
Pola
nd
Spai
n
Swed
en
Switz
erla
nd
Table 3: The condition variables: labour market position of women relative to men,
social policies aimed at elderly people, problem pressure and gendered care attitudes in
thirteen European countries, and the fuzzy sets
Page 12 of 24
4. Results
In this section we present the results of the analysis of our data using the Fz/QCA
software (Ragin 2008). The aim of the analysis is to identify possible combinations of
conditions leading to a given outcome, in our case the presence of a gender care gap or
its opposite, the absence of a gender care gap. To do so, Fuzzy set analysis requires the
determination of the “necessary conditions” and the “sufficient conditions” for a
specific outcome. A condition is “necessary” for the outcome when all the membership
scores of the outcome are less than or equal to the membership scores of the condition.
When a condition is necessary its “consistency score” (the extent to which one set is
contained in another) exceeds a certain threshold set by the researcher, generally 0.90 or
higher. The “coverage” indicates what proportion of the cases is ‘covered’ by the
condition (Ragin 2000, Rihoux and Ragin 2009). The analysis of our data shows that
there are no necessary conditions for the gender care gap outcome, since non of the
consistency scores exceeds 0.90 (see Table 4). This means that non of our condition
variables – social policy, part-time gap, pay gap, problem pressure or gendered care
attitudes – necessarily needs to be present to produce a gender care gap in the countries
that we analyse.
Consistency Coverage
~EXPSERV 0.854494 0.946287
PTGAP 0.664765 0.636612
PAYGAP 0.807418 0.605996
CARERES 0.808845 0.707865
GENDCARE 0.710414 0.711429
Table 4: Analysis of necessary conditions for the “gender care gap” outcome
(CAREGAP)
Yet even if not necessary a condition variable or a combination variable can be
“sufficient” to produces the outcome, a gender care gap. To find out to what extent this
is the case we need to build a truth table containing all the possible combinations of
Page 13 of 24
conditions leading to the outcome (Rihoux and Ragin 2009). After building the truth
table a “frequency threshold” is defined for the number of cases in each configuration in
the truth table. Since our N is relatively small (thirteen), the threshold is set at 1. In
addition, a “consistency threshold” is set in order to discern configurations that are
consistent subsets of the outcome from those that are not. We set the threshold at 0.80.
On the basis of our frequency and consistency thresholds and by choosing the so-called
the “intermediate solution” (see Ragin 2008) the Fz/QCA software recalculates the data
and identifies the combinations of conditions that are sufficient to produce the outcome,
a gender care gap. For the analysis of the results, three criteria are crucial: “raw” and
“unique coverage”, and “solution coverage”. The raw coverage indicates the proportion
of the outcome cases covered by a specific combination of conditions. The unique
coverage indicates the proportion of the outcome cases covered solely by a given
combination of conditions, which means that no other combination of conditions covers
those cases. Finally, the solution coverage indicates the proportion of cases covered by
all the combinations of factors included in the solution (Rihoux and Ragin 2009).
Our analysis of the sufficient conditions for the CAREGAP outcome is
presented in Table 5. The table indicates three paths which can produce a gender care
gap. The first path, associated with four European countries (France, Greece, Italy and
Poland), produces a gender care gap as a result of a relative lack of public services for
elderly people in need of care (~EXPSERVE, “~” indicates the negation of a condition).
The second path, associated with two countries (Belgium and Italy), combines a high
problem pressure (CARERES) with a relatively low pay gap (~PAYGAP), indicating
that in these two countries even with the absence of a pay gap between men and women
on the labour market, the relatively high care needs of elderly people “induces” women
to do more than men in the care for an elderly parent. Finally, the third path, also
associated with two countries (France and Switzerland), combines three factors that
together lead to a gender care gap: a high problem pressure (CARERES), a relatively
large occurrence of part-time labour by women (PTGAP) and little gendered care
attitudes (~GENDCARE). This third solution suggests that even if gendered attitudes
towards caring are mild in these countries, the fact that women hold more often than
men part-time jobs induces women to care more than men for an elderly parent. The
three-paths model presented in Table 5 shows satisfactory consistency (0.83) as well as
a satisfactory coverage (0.95).
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Solution ~EXPSERVE + CARERES*
~PAYGAP
+ CARERES*PTGAP*
~GENDCARE
Cases with
greater than 0.5
membership
France (0.67)
Greece (1.0)
Italy (0.67)
Poland (1.0)
Belgium (0.67)
Italy (1.0)
France (0.67)
Switzerland (1)
Consistency 0.946288 0.900602 0.782796
Raw coverage 0.854493 0.426533 0.519258
Unique coverage 0.288160 0.048502 0.048502
Solution consistency: 0.832709; solution coverage: 0.951498; Frequency cut off in
truth-table: 1.0; consistency cut off in truth table: 0.831658. Causal conditions included
for minimization: ~EXPSERV, PTGAP, PAYGAP, CARERES, GENDCARE.
Note: * logical AND; + logical OR; ~ negation.
Table 5: Analysis of necessary conditions for the “gender care gap” outcome
(CAREGAP), intermediate solution
We now turn to evaluation of the conditions for the negated “gender care gap” outcome
(~CAREGAP) to find out what combination(s) of conditions may produces a situation
in which there is no gendered care gap. Based on the same model, we perform the same
analyses as performed above concerning the presence of a gendered care gap
(CAREGAP). When we set the threshold for the consistency score again at 0.90, there is
one necessary condition for the situation in which a gendered care gap is absent,
relatively high public expenditures for elderly people in need of care (EXPSERV, see
Table 6). Subsequently, following the same procedures as for the presence of a
gendered care gap our analysis of the sufficient conditions for the ~CAREGAP outcome
suggests that there are two paths which can produce a situation in which a gender care
gap is absent (see Table 7). The first path combines relatively high public expenditures
Page 15 of 24
for elderly people in need of care (EXPSERV) with a low problem pressure
(~CARERES), i.e. relatively few elderly people in need of care. This path is associated
with the Czech Republic and the Netherlands. The second path, which is only associated
with Sweden, combines relatively high public expenditures for elderly people in need of
care (EXPSERV), a relatively small part-time gap between men and women (~PTGAP)
and relatively mild gendered care attitudes (~GENDCARE). The model presented in
Table 7 shows satisfactory consistency (0.80) and coverage (0.89).
Consistency Coverage
EXPSERVE 0.943239 0.847076
~PTGAP 0.555927 0.586268
~PAYGAP 0.385643 0.631148
~CARERES 0.609349 0.731463
~GENDCARE 0.662771 0.661667
Table 6: Analysis of necessary conditions for the negated “gender care gap” outcome
(~ CAREGAP)
Solution EXPSERV*~CARERES + EXPSERVE*~PTGAP*
~GENDCARE
Cases with
greater than 0.5
membership
Czech Rep. (0.67)
The Netherlands (1.0)
Sweden (1.0)
Consistency 0.914787 0.872180
Raw coverage 0.609349 0.387312
Unique coverage 0.113522 0.056761
Page 16 of 24
Solution consistency: 0.797904; solution coverage: 0.889816; Frequency cut off in
truth-table: 1.0; consistency cut off in truth table: 0.829146. Causal conditions included
for minimization: EXPSERV, ~PTGAP, ~PAYGAP, ~CARERES, ~GENDCARE.
Table 7: Analysis of sufficient conditions for the negated “gender care gap” outcome (~
CAREGAP)
5. Conclusion
In this paper we investigated the relationship between the relative contributions of
women – in comparison to men: the “gender care gap” – to the informal care for their
partners, government care policies and the labour market position of European women.
We analysed the interlinkages between the three factors in thirteen European countries
by applying a research model based on the Fuzzy set/Qualitative comparative analysis
method. We chose this approach in order to be able identify patterns in the relationship
between the three factors, since in the literature it is suggested that none of the factors
alone can explain the presence or absence of the gender care gap. The results of our
analysis in this paper suggests that the extent to which countries are confronted with the
ageing of their populations and the (absence of a) policy reactions to this problem are
crucial to understanding the gender care gap in the care for elderly parents in need of
care, while the presence or absence of gendered care attitudes plays a relatively minor
role. Only in Sweden relatively mild gendered care attitudes contribute to an equal
distribution of care obligations between men and women, but only in combination with
relatively high government expenditures for elderly people in need of care and the
absence of a part-time gap between men and women on the Swedish labour market. In
France and Switzerland relatively mild gendered care attitudes can not prevent a gender
care gap from occurring. Labour market characteristic seem more important in the
creation of a gender care or its opposite, but only in combination with other factors.
What seem crucial in understanding the gender care gap or its opposite are two factors:
public expenditure and problem pressure. In all the paths to a gender care gap or its
opposite our analyses produced one of these factors or both play a role. Most important
seem public expenditures for elderly people in need of care, which in Sweden, Czech
Republic and the Netherlands contribute to a relative equal distribution of
Page 17 of 24
responsibilities between men and women, while in France, Greece, Italy and Poland
relatively low expenditures alone explains the presence of a gender care gap. Likewise,
problem pressure figures in three of the five paths we discerned, but always in
combination with another factor.
The conclusions of this paper should be taken as preliminary, however, due to
study limitations, more specifically data availability and the small number of countries
included in the study, which increase the problem of “non-observed diversity” (Ragin
2008). As to the former limitation, especially the data we used to measure the dependent
variable, the gender care gap, in various European countries seem questionable. These
data are based on the self-reported contributions of men and women, which may have
been affected by socially desirable responding, and contain figures that contradicts other
research results. For example, the value of Spain for the gender care gap appears too
low, while the value of Denmark seems too high (see Table 1, cf. [SOURCE]). Future
research should be based on more “objective” data on the contributions of men and
women to the informal care for their parents.
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ANNEX 1: Definitions and sources of variables
Name Definition Calculation (if
applicable)
Source
CAREGAP Difference between
the proportion of men
and women with at
least one non co-
resident
natural parent caring
for mother and/or
father "almost
weekly" or more
often, over the
proportion of men
with
the same
characteristics
(Proportion of women
with at least one living non
co-resident parent caring
"almost weekly" for
mother or father MINUS
proportion of men with the
same characteristics)
DIVIDED BY proportion
of men with the same
characteristics
www.share-
project.org, Survey
of Health, Ageing
and Retirement in
Europe (SHARE),
own elaborations,
retrieved 8 August
2012.
EXPSERV Public expenditure on
long-term services for
non co-resident
natural parent as a
proportion of GDP
www.stats.oecd.org
, OECD statistics,
retrieved 8 August
2012.
PTGAP Part-time
employment gap, i.e.
the difference
between part-time
employment rate
of women and men
50-64
Proportion of women 50-
64 employed in part time
jobs MINUS proportion of
men with the same
characteristics DIVIDED
BY proportion of men
with the same
characteristics
www.eps.eurostat.e
c.europe.eu,
Eurostat, online
data from LFS,
retrieved 8 August
2012.
Page 23 of 24
PAYGAP The gender pay gap,
(GPG), i.e. the
difference in average
wages between men
and women. The
definition and
calculation are
provided by Eurostat
on line and are not
changed by the
authors.
“The unadjusted gender
pay gap is calculated as the
difference between the
average gross hourly
earnings of male and
female paid employees as
a percentage of average
gross hourly earnings of
male paid employees.”*
www.eps.eurostat.e
c.europe.eu,
Eurostat, online
data from LFS,
retrieved 8 August
2012.
CARERES The intensity of need
of people 75+
Number of people aged
75+ over number of people
aged 50-64
www.eps.eurostat.e
c.europe.eu,
Eurostat, online
data from LFS,
retrieved 8 August
2012.
GENDCAR
E
Gendered care
attitudes
Proportion of people
disagreeing or strongly
disagreeing with the
statement "fathers are as
suited as mothers to look
after their children"
http://
www.europeanvalu
esstudy.eu,
European Value
Study, 2008 wave,
retrieved 8 August
2012.
*. epp.eurostat.ec.europa.eu/statistics_explained/index.php/Glossary:Gender_pay_gap_(GPG), retrieved 20 August 2012.
Page 24 of 24