THE MATTHEW EFFECT IN EARLY CHILDHOOD EDUCATION AND CARE - How family policies may amplify inequalities Wim Van Lancker
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THE MATTHEW EFFECT IN EARLY CHILDHOOD
EDUCATION AND CARE
How family policies may amplify inequalities
Wim Van LanckerCENTRE FOR SOCIOLOGICAL RESEARCH
SOCIAL POLICY & SOCIAL WORK
SPSW Working Paper Series
CeSo/SPSW/2021-02
The Matthew Effect in early
childhood education and care
How family policies may amplify inequalities
Wim Van Lancker
Citation: Van Lancker, W. (2021). The Matthew Effect in early childhood
education and care: How family policies may amplify inequalities.
SPSW Working Paper No.CeSo/SPSW/2021-01. Leuven: Centre for
Sociological Research, KU Leuven.Corresponding author
Wim Van Lancker
Centre for Sociological Research
KU Leuven
Parkstraat 45 box 3601
B – 3000 Leuven
wim.vanlancker@kuleuven.be
Acknowledgements
The author would like to thank Alzbeta Bartova and Mary Daly for helpful and constructive
comments on earlier drafts of this working paper.
This working paper is forthcoming as a book chapter in: Daly, Mary; Gilbert, Neil; Pfau-
Effinger, Birgit; Berashov, Douglas (eds.) International Handbook of Family Policy : A Life-
Course Perspective. Oxford University Press.
© Centrum voor Sociologisch Onderzoek (CeSO)
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B – 3000 Leuven
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ABSTRACT | 3Abstract
This working paper reviews the current evidence on the Matthew effect and its relevance
for understanding the outcomes of present-day family policies. It is discussed how the
Matthew effect is studied and interpreted in sociology and in the field of family policy,
focusing on subtleties involved in studying the phenomenon and its root causes, how it is
conceptualized, and its functions or dysfunctions. An empirical illustration is presented of
how the Matthew effect in childcare services across European countries can be studied
and understood. The results show that in the majority of countries, childcare participation
is biased against poor children. While childcare use has risen over time, inequality did not
decline to the same extent. This means that the children who would benefit most from being
integrated into high-quality childcare are the ones currently most likely to be excluded. This
not only jeopardizes the potential of childcare provision to reduce inequalities in early life,
it might even fuel compounding inequalities over the life-course. Potential pathways to
redress childcare policies in order to foster socioeconomic equality in childcare participation
are explored. The paper ends with a call to arms for more advanced studies into the causes,
mechanisms and consequences of the Matthew effect in social and family policies, with a
particular focus on life-course approaches.
Keywords: Matthew effect, family policy, childcare, ECEC, inequality
4 | ABSTRACTContent
1 Introduction ............................................................................................................. 6
2 The Matthew effect as a process of cumulative advantage ............................... 7
3 The Matthew effect in social and family policy .................................................... 9
4 The Matthew effect in childcare services ........................................................... 12
4.1 Data and operationalization .......................................................................... 13
4.2 The evolution of childcare spending and participation over time ................. 13
4.3 The Matthew effect in childcare in Europe ................................................... 15
4.4 Composition and policy design effects ......................................................... 17
5 Conclusion ............................................................................................................ 18
6 References ............................................................................................................. 19
7 Appendix ................................................................................................................ 24
CONTENT | 51 Introduction “The poor stay poor, the rich get rich. That’s how it goes, everybody knows.” Few will dispute that the poet and singer Leonard Cohen touches in his song Everybody Knows on a commonly shared intuition that reality often – if not always – seems to work that way: the rich get richer while the poor stay poor. The phenomenon has been designated a Matthew effect by the sociologist Robert K. Merton (1968), referring to a verse in the Gospel of Matthew: “For unto every one that hath shall be given, and he shall have abundance: but from him that hath not shall be taken away even that which he hath” (Matthew 25:29, King James translation). Merton introduced the term Matthew effect to describe how the prevailing reward and communication system in science gives far more credit to well-known scientists, Nobel Prize laureates in particular, than to relatively unknown scientists for comparable contributions. He observed how high status gives academics an advantage for accruing resources, citations and academic success. In turn, their recognition grows and their high status is affirmed, closing a feedback loop that enables them to garner even more resources. This process of ‘cumulative advantage’ is not limited to scientific endeavour, but can be observed in a variety of social situations and institutional contexts: “[it] is a general mechanism for inequality across any temporal process [..] in which a favourable relative position becomes a resource that produces further relative gains” (DiPrete and Eirich 2006, 271 ). As it is understood in popular discourse, the Matthew effect is very simple: the rich get richer, the poor stay poor. In reality, however, the Matthew effect is a complex phenomenon with a variety of possible causes and a diverse set of potential outcomes, depending on the context in which it occurs. In particular in the field of family policy the Matthew effect can have major ramifications for the objectives and outcomes of early childhood policies such as childcare. In this working paper I review the current evidence on the Matthew effect, discuss its relevance for understanding the outcomes of present-day family policies, and argue why and how it should be avoided. The remainder of this paper is structured as follows. First, I outline how the Matthew effect is discussed and interpreted in sociology and adjacent disciplines, focusing on subtleties involved in studying the phenomenon and its root causes. Second, I turn attention to the Matthew effect in social and family policies, how it is conceptualized, and its functions or dysfunctions. Finally, I present an empirical illustration of how the Matthew effect in childcare services across European countries can be studied and understood, and argue why childcare policies should be redressed in order to foster socioeconomic equality and promote employment in the future. I conclude with a call to arms for furthering the study of the Matthew effect in family policies in the future. 6 | INTRODUCTION
2 The Matthew effect as a process of cumulative
advantage
The pattern of cumulative advantage consistent with the Matthew effect has been observed
in variety of fields such as, to name a few, sports, literature, music, art, business, education,
the fiscal system, or politics (see Rigney 2010; DiPrete and Eirich 2006 for more examples).
The returns on investments, assets and bonds, for instance, are larger for investors who
are able to invest more, fuelling a feedback loop in which these higher returns can be
invested again (Jordà et al. 2019). In sports, athletes who perform well in youth leagues
are likely to get the most attention and coaching which in turn breeds more opportunities
to become even better and to widen the gap (e.g. Barnsley et al. 1985). Products sold on
online markets that get early positive reviews collect more clicks, votes and reviews,
pushing these products to top sales which in turn garners more clicks, votes and reviews
(Wan 2015). Recently, Bol and colleagues (Bol et al. 2018) studied the Matthew effect in
science funding. They find that the candidates who had won prior awards or grants are
more likely to be evaluated positively by reviewers in grant competitions, increasing their
chances to collect new grants, again fuelling the feedback loop.
In the sociological literature, research into the Matthew effect is strongly connected to
issues of fairness. It is long recognized that the Matthew effect may undermine the
meritocratic ideals of modern societies. In Merton’s (1968) original study, status emerges
as the key driver of the process of cumulative advantage. High-status signals give
academics an advantage for accruing resources and academic success. However, as long
as the feedback loop of status and rewards is a reflection of actual differences in
performance and quality, one could argue the Matthew effect is not at odds with meritocratic
ideals; i.e. the best scientists reap the greatest rewards. According to such a meritocratic
perspective, scientists deserve their distinct status as long as it is based on actual quality
differences, and their status advantage is used to improve the quality of their contributions
(Podolny 2005). Obviously it is a matter of debate whether this process can be conceived
as ‘fair’. Still, recent empirical research in which the effect of status on cumulative
advantage is examined separately from the effect of quality or performance tends to show
that status fuels a feedback loop irrespective of quality. Bol and colleagues (2018), for
instance, find no evidence that the improved chances of scientists to acquire new grants
after securing grants previously is the result of their achievements. Researchers acquire
more grants because they won grants in the past, not because they are better scientists.
Attempting to uncover the root cause of the Matthew effect brings further complexity. How
did the initial advantage occur that set the feedback loop in motion? Many of the
inequalities, disadvantages and wrongdoings we observe find their origin in the accident
(or lottery) of birth. Several crucial elements are more or less fixed at birth: not only genetic
endowments, cognitive abilities and talents, but also parental educational attainment,
socio-economic background of the family, the quality of the house in which one lives, the
neighbourhood in which one grows up. Sociological research has demonstrated forcefully
how the family in which one is born reproduces social advantage or disadvantage, through
economic (Erikson and Goldthorpe 1992) as well as cultural channels (Bourdieu 1984).
The consequences of growing up poor are negative and long-lasting, for individuals and for
society as a whole. Poor children exhibit lower levels of well-being, lower educational
achievement, and poorer health which translates into lower levels of employment, lower
earnings, poorer health, and more benefit dependency in adult life (see Van Lancker and
THE MATTHEW EFFECT AS A PROCESS OF CUMULATIVE ADVANTAGE | 7Vinck 2020 for an overview). In sum, luck, or the chance of being born into a poor or well- off family, sets in motion a process of cumulative (dis)advantage before any conscious decision was taken by these children. Considering the perspective of the life-course adds other dimensions of complexity (Bask and Bask 2015; Dannefer 2003). Over the life-course, people constantly make decisions under conditions of uncertainty and contextual constraint, for themselves or for their children. Each of these decisions affects the feedback loop, and how Matthew effects evolve in the long-run. Research shows that transitions from one social institution to another, e.g. from the education system into the labour market into retirement, tend to amplify inequalities over time: “those who are initially advantaged [...] are more likely to receive a good education, leading to good jobs, leading to better health and better pension coverage, leading to higher savings and better postretirement benefit income” (Crystal and Shea 1990, 437). These dynamic of widening inequalities over time spill over to the next generation. Research shows that poor children are likely to become poor parents themselves (Bellani and Bia 2019; Wagmiller and Adelman 2009). It is important to understand that the consequence of the Matthew effect in each of these transitions over the life-course is influenced by policies. Reducing poverty in early life, for instance, might halt or slow down the process of cumulative disadvantage. There is research to indicate that more generous and more equal welfare states do better in mitigating the intergenerational transmission of poverty and in promoting the education and labour market opportunities of children growing up in low-income families (Corak 2013). Moreover, the issue of timing is crucial. Shorter poverty spells are associated with less adverse outcomes. Recent analyses based on the UK Millennium Cohort Study, for instance, show that any exposure to poverty in childhood is associated with adverse health outcomes but that for children who were persistently poor throughout childhood the effects are larger (Lai et al. 2019). Cross-country comparisons also demonstrate the importance of policy factors. Some longer-term consequences of growing up poor, for instance late-life criminal behaviour and incarceration, are almost exclusively linked to the situation in the United States, suggesting the influence of criminal justice polices and welfare state generosity (Cooper and Stewart 2020). Still, research has been unable to pinpoint exactly how the interaction between agency and policy structure over the life-course influences the Matthew effect. Conceptually, most research focuses on the outcomes of the Matthew effect, or the accumulation of different Matthew effects occurring in different institutions, rather than on the actual mechanisms that generate these processes (Diprete and Eirich 2006). In any case, the sociological literature suggests that the Matthew effect is not an inescapable fact of life, but that it is strongly determined by policies. But how policies affect the Matthew effect is contingent on their design and implementation. That is the issue to which I now turn. 8 | THE MATTHEW EFFECT AS A PROCESS OF CUMULATIVE ADVANTAGE
3 The Matthew effect in social and family policy
The Matthew effect has been a subject of study in the field of social and family policies
since the 1970s. Yet the way it was, and still is, operationalized and studied differs from
the traditional sociological approach discussed in the previous section. In the field of social
and family policy, the Matthew effect refers to the allocation and distribution of public
spending on social measures.
The Belgian scholar Herman Deleeck was among the first to document the existence of a
Matthew effect in family policy in such a way. Based on data from the 1970s, Deleeck et
al. (1983) found that the universal child benefit system in Belgium, designed to compensate
for the costs of child upbringing for all families, in fact benefited the middle and higher
income families disproportionally. Children were entitled to child benefits up to age 18
unless they continued studying in which case eligibility was extended to age 25. The
Matthew effect occurred because: 1) the number of eligible children increased with income;
and 2) children from a high income family were overrepresented in higher education. Child
benefits had a regressive distributional effect (from low to higher incomes): because child
benefits were part of the social insurance system, families without children at the lower
ends of the income distribution in fact contributed to the benefit of families with children at
the higher ends of the income distribution.
Belgian policymakers did not intend to implement a child benefit system that would benefit
the rich; rather the occurrence of the Matthew effect was an unintended consequence
produced by the interplay between the rules of the game (a policy design effect) and the
social structure and situation of families with children (a compositional effect). Already in
the 1930s, Robert Merton pointed out that unintended consequences are an integral part
of purposive action and deemed this a ‘fundamental process’ that calls for a ‘systematic
and objective study of the elements involved in the development of unintended
consequences’ (Merton 1936). Anthony Giddens in turn emphasized the role of unintended
consequences of policy action in that they promote social reproduction across long periods
of time (Giddens 1984). Thus while the method of study is different from the original
sociological approaches to the Matthew effect, the consequences can be similar: the
(mis)allocation of public resources through social or family policies can widen inequalities
over time setting in motion a pernicious feedback loop, particularly so if the policies
displaying a Matthew effect are crucial to safeguard one’s living standard or to foster social
mobility.
Deleeck, et al. (1983) showed that similar mechanisms were at play in social housing,
pensions, healthcare, cultural participation, and education. Julian Le Grand sketched a
similar picture of welfare service use in the United Kingdom: the better-off made
disproportionate use of public and social services such as education, housing, healthcare,
social care, and transportation (Le Grand 1982). Similar research efforts have since been
carried out in several industrialized countries and identified the presence of Matthew effects
in a diverse set of social policy fields, such as education, healthcare, parental leave use,
infant mortality, career longevity, early childhood intervention, social security, and housing
(Bakermans-Kranenburg 2005; Dzakpasu et al. 2000; Gal 1998; Gouyette and Pestieau
1999; Petersen et al. 2011; Van Lancker 2017; Walberg and Tsai 1983).
In a functionalist, Mertonian fashion, studying the distribution of resources over intended
beneficiaries is a way of evaluating the outcomes of policies. If child benefits mainly benefit
THE MATTHEW EFFECT IN SOCIAL AND FAMILY POLICY | 9higher income groups while the objective of government spending on child benefits is to support the lowest income groups, for instance, one could argue that the presence of a Matthew effect is a policy dysfunction. Here too, however, the matter quickly becomes more complex. Policy measures usually serve multiple purposes, objectives may change over time, and the context changes as well. From the immediate post–World War II period onwards, for instance, most of the measures taken in the field of family policy in industrialized countries were income oriented, shaped by ideological considerations and gendered views on society and the role of men and women as breadwinners and homemakers respectively (Gauthier 1999; Daly 2020). In some countries, child benefits were a means to encourage women to stay at home, in others to encourage parenthood and increase fertility, while in still others child benefits have been a response to a concern for the well-being of children. Over time, some of these objectives disappeared from policy- makers’ vocabulary, sometimes to emerge again in later times, while other objectives gained more prominence. Given this, when evaluating the outcomes of deliberate policy action, the unintended presence of a Matthew effect and its potential consequences in terms of widening inequalities should be weighed against other (un)intended objectives and functions of policies. One famous example in the social policy literature relates to the so-called paradox of redistribution. We are all familiar with the truism that programmes for the poor end up being poor programmes. Or as Amartya Sen has put it: “Benefits meant exclusively for the poor often end up being poor benefits” (Sen 1995, 14). Variations on the same theme can be found all over the social science literature, but it was only with the publication of the 1998 seminal article ‘The Paradox of Redistribution’ in the American Sociological Review that it was established empirically for a set of rich countries (Korpi and Palme 1998). In this article, Walter Korpi and Joakim Palme demonstrated that universal welfare states with earnings- related (contributory) benefits tend to be more effective with regard to poverty alleviation than targeted welfare states with flat-rate (non-contributory) benefit systems. They, further, argued that social programmes including all citizens garner more cross-class political support leading to higher levels of public spending on redistributive programs, ultimately to the betterment of the poor. The flip side of this is that the middle classes typically benefit more from universally- oriented welfare states than do the poor. Following the logic of Korpi and Palme, such Matthew effect in social spending is a constitutive part of the success of the universal welfare state in that it secures broad-based public support for high levels of social spending. Aptly summarized: because all citizens are entitled to a slice of the pie in universal welfare states, everybody, including the poor, ends up being better off. It is important to emphasize that the paradox of redistribution is often misunderstood. The claim made was not simply that universal welfare states do better. First, Korpi and Palme argued that ‘encompassing’ welfare states, relying heavily on earnings-related social insurance programmes for those who contribute, achieve higher levels of redistribution than ‘targeted’ or ‘basic security’ welfare states relying on flat-rate benefits for those in need. Note that while social insurance is doing the heavy lifting, encompassing welfare states too can have flat-rate minimum income protection benefits targeted to the poor. In a second step, the analysis demonstrated for 11 Organisation for Economic Co-operation and Development (OECD) countries that there is a strong correlation between redistribution - measured as the reduction in inequality - and the size of the redistributive budget, or the total amount of public social spending. Finally, the article showed that redistribution within welfare states is negatively associated with the degree of low-income targeting - which is 10 | THE MATTHEW EFFECT IN SOCIAL AND FAMILY POLICY
effectively the share of the redistributive budget accruing to individuals with low gross
incomes. The causal chain is as follows: (1) encompassing welfare states with big social
insurance programmes, covering all workers, have higher redistributive budgets; (2)
because all workers benefit from social insurance programmes and the benefits are
earnings-related, a higher share of the budget accrues to middle and high income workers
(the Matthew effect); but (3) this leaves the lowest income individuals better off as well. A
political economy argument is central: social-insurance ensures the sustainability of cross-
class coalitions with regard to high levels of welfare state spending.
In this famous case, the Matthew effect is an unintended consequence of deliberate policy
action; policymakers usually do not intend to give less to the poor. However, it is functional
since the Matthew effect helps sustaining cross-class coalitions in favour of the welfare
state in general and large social insurance programmes in particular. The Matthew effect
in social insurance programmes is a feature, not a bug.
To conclude, the Matthew effect can be observed in many social policy programmes in
different times and contexts. Gauging the consequences is complex, because depending
on the interplay between policy design and the underlying composition of the population it
can be a function or a dysfunction, and it should be interpreted taking into account the
multiple objectives attaching to social and family policies. In the next section, I integrate the
sociological perspective on cumulative (dis)advantage with the social policy tradition of
investigating the distribution of public resources by discussing the relevance, breadth and
consequences of the Matthew effect in childcare services. The provision of childcare
services is one of the mainstays of contemporary family policies in the majority of
developed welfare states. It is also one of the fields where the Matthew effect threatens to
ignite a feedback loop in which the gap between the haves and the have-nots grows.
THE MATTHEW EFFECT IN SOCIAL AND FAMILY POLICY | 114 The Matthew effect in childcare services Across European countries, the number of children under three enrolled on a full-time basis in formal childcare services rose almost continuously since the turn of the century and governments increasingly devoted public resources to the provision of childcare, strongly encouraged by international organisations such as the OECD and the European Union (EU). While in aftermath of the 2008 Great Recession many social programmes including family transfers were subjected to cuts, childcare services were hardly affected at all, and pre-crisis reforms and investments were carried out as planned (Van Lancker and Ghysels 2014). Government spending on childcare services is also popular amongst the general public (Garritzmann et al. 2018). The popularity of childcare services can be understood with reference to the so-called ‘social investment turn’ in welfare state policies. According to the logic of social investment, social policy in contemporary welfare states should not only provide a buffer for protection against social risks, but should focus at least as much on preparing people for today’s and tomorrow’s labour markets (Hemerijck 2017). In this respect, children and childhood are key to any successful investment strategy, not only because the sustainability of the welfare state hinges on the number and productivity of future taxpayers but also because inequalities in childhood pose a real threat to the accumulation of human capital and are the root cause of unequal opportunities in the labor market and later life. Successful investment policies hence mean intervening as early as possible to stop the process of cumulative advantage in its tracks. This is exemplified in the European Pillar of Social Rights, in which childcare is designated a right for children under principle 11, where explicit reference is made to ‘the right from protection from poverty’ (European Commission 2021). In the same vein, the 2015 European Parliament resolution on a European Child Guarantee states that all children in Europe at risk of poverty should have access to essential services of good quality, including early childhood education and care services (e.g. Daly 2019). As such, one of the explicit intentions of policymakers is to facilitate the participation of poor children into childcare services. In fact, childcare services are deemed an effective instrument to attain social investment objectives, thus to combat Matthew effects from materializing over time, for two particular reasons. First, childcare services help achieve social inclusion through the labor market by allowing parents of young children to engage in paid employment. Second, being enrolled in high-quality childcare services is beneficial for children in terms of cognitive and non- cognitive development and improving school readiness which will in turn increase later labor market opportunities. This obviously means that public spending on childcare services should benefit those disadvantaged children first and foremost and that they need to be enrolled in high-quality care. In what follows, I first describe the evolution of public spending and childcare participation amongst children below three years old across European countries. This is followed by an assessment of the inequalities in participation rates by social background. Finally, I review the consequences of inequalities in childcare participation, and discuss how composition and policy design effects might help explain the patterns observed. 12 | THE MATTHEW EFFECT IN CHILDCARE SERVICES
4.1 Data and operationalization
Data are drawn from the OECD Social expenditures (SOCX) database and the European
Union Statistics on Income and Living Conditions (EU-SILC) database. SOCX includes
detailed information on specific categories of public spending, and allows to isolate
spending on childcare services for young children from other spending categories such as
pre-primary education (OECD 2020). Spending on childcare services is expressed as a
percentage of gross domestic product (GDP). The EU-SILC is a harmonized cross-national
survey which includes detailed information on European households’ income and living
conditions, as well as questions on children’s participation in early childhood education and
services (Eurostat 2020). Childcare services refer to childcare centers, crèches,
professional childminders and preschool settings. To take into account differences in the
intensity of use (i.e. hours of attendance per week), enrolment rates are presented in full-
time equivalents (FTE). Full-time is defined as 30 hours per week or more. Data are
available for 25 European countries over the period 2005 to 2015. The results are
presented in figures in the main text; tables with the full set of data are in the appendix.
4.2 The evolution of childcare spending and participation over time
Figure 1 shows the change in public spending on childcare services for young children from
2005 to 2015 for 25 European countries. In 2005 there were important differences in the
level of public investment in childcare services between countries. Countries such as
Denmark, France, Iceland, and Sweden spent more than one percent of GDP on childcare
provision, with Finland and Norway following suit. Most countries however spent between
0.2 and 0.6 percent of GDP on childcare provision. A decade later, all but three countries
increased spending, often substantially. Only in Denmark, Slovenia and the United
Kingdom has spending remained at similar levels. At the later date most countries spent
between 0.4 and 0.8 percent of GDP on childcare provision. In Figure 2, I calculate
enrolment rates for children aged under three years old in 2005 and in 2015, using the EU-
SILC data. The results show that the rise in spending translated into higher enrolment rates.
In 2005, enrolment rates in formal childcare services ranged from only 5% of children aged
zero to three in the Czech Republic to 90% of children in Denmark. Not surprisingly, there
is a strong correlation between spending and enrolment rates (r = 0.70). A decade later,
enrolment rates increased in all but three countries. In the Lithuania, the Slovak Republic,
and the United Kingdom participation in childcare declined somewhat, in Germany,
Luxemburg, Norway, and Portugal enrolment rates increased substantially. A rise in
enrolment rates went together with a rise in public spending (r = 0.35). As a matter of fact,
European countries converged in terms of both public spending on childcare services and
participation in childcare services. The coefficient of variation for spending declined from
0.66 in 2005 to 0.56 in 2015; for participation it declined from 0.62 in 2005 to 0.54. Akin to
the earlier studies of the Matthew effect in social policy, we can now turn to the distribution
of resources over intended beneficiaries as a way to evaluate the outcomes of child-centred
investment.
THE MATTHEW EFFECT IN CHILDCARE SERVICES | 13Figure 1. Spending on childcare services (in % of GDP), 2005 and 2015
2,0
Spending on childcare services in 2015 (% of GDP) 1,8 IS
1,6 SE
1,4
NO FR
1,2 DK
FI
1,0
BE
0,8 LT
LV EE LU
HU
PL DENL UK
0,6 AT IT
SK ES
SI
0,4 PTCZ
IE
0,2
GR
0,0
0,0 0,5 1,0 1,5 2,0
spending on childcare services in 2005 (% of GDP)
Source: own calculations on the basis of the detailed Social expenditure data from the OECD.
http://www.oecd.org/socx.
Figure 2. FTE enrolment rates in childcare services (0-2 year olds), 2005 and 2015
100%
DK
FTE childcare enrollment rates (0-3 year olds) in
90% IS
80% NO
SE
70%
LU BE
PT SI
60%
FR ES IT
2015
50% DE
EE FI
40% NL LV
30% AT IE
HU GR LT
20% PL UK
10% CZ
SK
0%
0% 20% 40% 60% 80% 100%
FTE childcare enrollment rates (0-3 year olds) in 2005
Source: own calculations on the basis of EU-SILC, waves 2005 and 2015.
14 | THE MATTHEW EFFECT IN CHILDCARE SERVICES4.3 The Matthew effect in childcare in Europe
One simple way to uncover the Matthew effect is to examine the distribution of childcare
participation by family income. To do this, first, families with young children are divided into
five income groups (quintiles) for each country on the basis of their disposable household
income. Subsequently, the average childcare participation rates of children living in low-
income and high-income households is compared. Figure 3 presents an inequality ratio
(IR) for each country for 2005 and 2015. This is the average childcare participation rate of
children living in the highest income family (fifth quintile) divided by the average childcare
participation rate of children living in a low income family (first quintile). An IR of 2 thus
means that children from high-income families are enrolled in childcare twice as much as
their counterparts from low-income families, while an IR of 1 represents an equal
distribution of childcare use.
The results show that childcare use amongst young children is socially stratified in the
majority of countries. In 2005, inequalities were particularly striking in countries such as
Ireland (IR: 13), Poland (IR: 11), the United Kingdom (IR: 7), Greece (IR: 7), and Lithuania
(IR: 7). In the United Kingdom, for instance, an IR of 7 translates into participation rates of
6% amongst the poorest 20% of children compared to 45% amongst the richest 20% of
children. But also in countries with relatively low IRs, differences in participation rates can
be substantial. In France, an IR of 3 means that 21% of the poorest children participate in
childcare while 69% of the richest children do. In Norway, with an IR of 2, 31% of the
poorest children participate in childcare while 64% of the richest children do. Only in
Denmark, Slovenia, and Estonia is childcare participation equally distributed over income
groups. A decade later, despite an increase in public spending and enrolment rates in
almost all European countries, inequalities in childcare participation decreased
substantially in only seven countries: Austria, Greece, Hungary, Ireland, Luxemburg,
Norway, and Portugal. In the majority of countries, inequalities did not decrease. In fact, in
five countries, childcare inequalities increased substantially. That is the case in France,
Lithuania, Poland, Slovak Republic, and the United Kingdom. In Slovak Republic, for
instance , childcare participation amongst the lowest income families decreased
substantially while it remained on par for the middle and high income groups. However,
childcare participation rates remained extremely low overall in Slovak Republic; here a
social investment turn has not been initiated at all. In the United Kingdom, childcare
participation declined across all income groups, but more so amongst the poorest children.
In France, childcare participation rose in all but the poorest income groups. In general,
while convergence has occurred in terms of childcare spending and participation, European
countries diverged in terms of inequality and inequality rose. In 2005, the coefficient of
variation for inequality was 0.93, in 2015 it rose to 1.23.
Exercises in which inequality ratios of childcare participation were based on occupation
class or educational level instead of income, or in which different inequality indices such as
concentration coefficients or relative inequality indices were used, yield similar outcomes
(OECD 2016; Van Lancker and Ghysels 2016; Van Lancker 2013). The same is true for
calculations based on different datasets or a different set of countries and country cases
(Abrassart and Bonoli 2015; Blossfeld et al. 2017; Krapf 2014; Mamolo et al. 2011; Pavolini
and Van Lancker 2018; Vandenbroeck et al. 2014). Arguably, more sophisticated analyses
are needed to measure the actual allocation of public resources over different income
groups, because parental fees can be differentiated by income level, governments can
encourage childcare participation through fiscal measures, and subsidies can be targeted
directly to low-income parents. However, the limited number of studies in which this is taken
THE MATTHEW EFFECT IN CHILDCARE SERVICES | 15into account point in the same direction: public spending on childcare services tends to
benefit the middle and higher income groups in society (Förster and Verbist 2012; Ghysels
and Van Lancker 2011; Hufkens et al. 2020; Van Lancker and Ghysels 2012). All in all, the
empirical evidence is unequivocal: the Matthew effect in childcare use is the norm rather
than the exception.
Figure 3. Inequality ratio (high/low incomes) of FTE childcare use, 2005 and 2015
19
18
17
16
15
Inequality ratio (IR)
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
IE PL UK GR LT PT AT FR LU FI HU NL CZ LV NO ES BE SE IT DE IS SK DK SI EE
2005
Source: own calculations on the basis of EU-SILC, waves 2005 and 2015. Inequality ratios are based
on the mean FTE childcare use amongst children under three living in the highest income households
to the mean FTE childcare use amongst children under three living in the lowest income households.
Household income is defined as net equivalized disposable household income, using the OECD
modified equivalence scale (Hagenaars et al. 1994).
The Matthew effect in childcare participation means that the children who would benefit
most from being integrated into high-quality childcare are the ones currently most likely to
be excluded. This not only jeopardizes its potential to reduce inequalities in early life, it
might even fuel Matthew effects over the life-course. I mentioned above how Matthew
effects often take root at birth, and that transitions from one institution to the other, e.g.
from education to labour market, tend to reproduce or reinforce inequalities. Children being
born in lower income families already start at a disadvantage in terms of resources, living
conditions, and parental care. They grow up in an environment that is less conducive to
learning, having parents who are less able to facilitate their children’s school readiness
than their higher-income and higher-skilled counterparts (Augustine et al. 2009; Ermish
2008). If these children have no or less access to high-quality childcare while advantaged
children do, this pattern of accumulation of disadvantage is reinforced. Better-off children
are able to enhance their existing advantage through the benefits of high quality childcare
in terms of school readiness and parental employment, while the children who stand to gain
the most are excluded. And low income families who do find a place in childcare, often find
themselves in a service of poor quality. This is particularly the case in market-based
childcare systems, such as in the United Kingdom (Lloyd and Penn 2012).
Given the explicit social investment goals to foster childcare participation amongst the
poorest children, the Matthew effect in childcare is an unintended consequence of
deliberate policy action. Governments usually don’t mean to exclude low-income children,
under the social investment paradigm the opposite is true. The Matthew effect in childcare
16 | THE MATTHEW EFFECT IN CHILDCARE SERVICESis also a dysfunction, because it prevents the childcare policy goals to be attained. In terms
of contemporary family polices, the Matthew effect is a bug, not a feature.
4.4 Composition and policy design effects
How can the Matthew effect in childcare participation be explained? Here too it is relevant
to examine both composition effects and policy effects. One of the key reasons why
childcare service provision is riddled with Matthew effects is that there is a structural
shortage in the number of high-quality and affordable childcare places available in the
majority of European countries (Pavolini and Van Lancker 2018). In countries with higher
levels of childcare supply, inequalities in participation are lower (Van Lancker and Ghysels
2017). Abrassart and Bonoli (2015) find in a Swiss canton that disadvantaged children are
more likely to attend formal childcare when fees are lower (Abrassart and Bonoli 2015).
Such a policy design effect is discernible in the descriptive data presented in this paper as
well. Since in the majority of European countries demand for childcare exceeds supply, the
full-time equivalent measure of childcare participation used in this paper is a good
approximation of the number of places available. In countries where childcare participation
rates are higher, and thus more places are available, inequality ratios are lower (correlation
is -0.44 in 2005 and -0.49 in 2015). The change in childcare participation between 2005
and 2015 is also negatively correlated with changes in inequalities (r = -0.39). An increase
in the number of places tends to be associated with decreases in inequalities in its use.
This constitutes a key lesson: to remedy the Matthew effect in childcare, countries will need
to expand the availability of places across the income distribution.
The underlying distribution of social risks matters too. Labour market opportunities are not
evenly distributed across families, with vast differences in employment by educational level.
Where childcare places are rationed, disadvantaged families with only a weak labour
market attachment are often unable to secure a place in formal childcare services.
Childcare providers generally prioritize working parents with stable occupations, and those
situations are more prevalent among middle and upper class families (Verhoef et al. 2016).
For a number of Italian municipalities, for instance, Del Boca et al. (2016) demonstrate that
prioritizing disadvantaged children in a context of shortage could reduce inequality in
participation. In contrast, in private childcare markets, providers tend to follow demand and
establish themselves in better-off neighbourhoods, which means that disadvantaged
families have fewer opportunities to secure a childcare place of sufficient quality (Noailly
and Visser 2009; Warner and Gradus 2011). In sum, like the Matthew effect observed in
other social and family policies, the Matthew effect in childcare emerges due to the
interaction between underlying inequalities between intended beneficiaries (composition
effect) and the structure and implementation of policies (design effect).
THE MATTHEW EFFECT IN CHILDCARE SERVICES | 175 Conclusion The analytical approach to the study of the Matthew effect in social and family policies follows three logical, sequential steps. First, the distribution of public spending or participation is studied to observe whether a Matthew effect is present or not. Second, the role of the composition of the population and the design of policies is examined in order to explain the distribution of resources. Third, this allows us to gauge to what extent the Matthew effect is a function or a dysfunction, in relation to the intended objectives of the policy under study. In terms of childcare participation, the literature shows that participation is biased against low income families and disadvantaged children. This is related to both composition effects, such as inequalities in employment and inequalities in early childhood, and design effects, such as rationing and the fee structure. Given the potential beneficial effects of bestowing high-quality childcare upon children in terms of school readiness in the short term and labour market attainment in the longer term, the Matthew effect risks setting in motion a pernicious feedback loop of cumulated advantage. In a functionalist, Mertonian fashion, the Matthew effect in this sense is a way to evaluate the objectives, or functions, of policies. While the Matthew effect in spending on social insurance programmes is unintended but functional to garner public support, the Matthew effect in childcare is unintended but dysfunctional, and it should be remedied in order for a social investment strategy to bear fruit. However, the Matthew effect in social and family policies has been studied in a somewhat different way than it was, and still is, studied in sociology. Analyses are usually more static, drawing on cross-sectional data, paying less attention to the dynamic aspects of feedback loops and compounding inequalities. Also family policy analysis is usually limited to macro- level analyses, starting from the distribution of public resources, instead of focusing on the individual life-course aspect. The argument that the Matthew effect in childcare services will widen the gap between the haves and the have-nots, for instance, is inferred but not yet empirically measured to its fullest extent. To date we lack empirical studies in which the process of cumulative advantage, from unequal participation in childcare services over schooling inequalities to inequalities in the labour market and beyond, has been measured properly. This requires longitudinal data of good quality in which proper measures of incomes, living standards, childcare use and participating in the educational system and the labour market are included. While it is a complex and demanding endeavour to measure the individual life-course consequences of a skewed distribution of public resources, here lies a clear gap and opportunity for further research into the Matthew effect in family policy and its consequences. This would connect the literature on the Matthew effect in the social policy literature to the Matthew effect as it is more broadly conceived. Given the unintended and potential pervasive consequences of the Matthew effect in family policies, more advanced studies into its causes, mechanisms and consequences must therefore remain high on the academic agenda in the decades to come. 18 | CONCLUSION
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