At the most fundamental level, a life course approach means understanding that outcomes for individuals and groups are best explained when we take account of the experiences of previous events and the transitions and pathways followed through life to arrive at a particular point. This is intuitively straightforward. If we are to explain why one child attains high grades and achieves well at school for example, but another does not, it is useful to know something about the life history of each child, their family background and the life events that have potentially shaped their learning outcomes. But a life course approach is much more than simply knowing about pathways and life events. It also means understanding how context and circumstances have shaped the types of pathways available to individuals, the role of important others in opening or blocking pathways, how institutional and organisational settings shape experiences and the importance of timing and sequencing of events and transitions experienced along that pathway (Elder & Giele, 2009; Mayer, 2009). A life course approach therefore seeks to understand the actions, behaviour and experiences of individuals by combining insights about the individual as well as the broader social forces surrounding them.

Compared to some other approaches that either only focus on individual level drivers of outcomes, as is common in some psychological theories, or institutional level factors, as is common in some economic theories, a life course approach is a comprehensive and powerful framework for addressing both individual and societal outcomes and the connections between them (Alwin, 2012). Of course, to effectively undertake a life course approach for understanding social outcomes requires collecting, or otherwise accessing, large amounts of information about individuals, families, places, policies, institutions and historical contexts. This approach will often be time consuming and expensive and potentially beyond the scope of researchers. Nevertheless, life course approaches have become very popular amongst researchers and policy-makers, gained currency across disciplines, and developed alongside increased availability of longitudinal panel and administrative data (Mayer, 2009). Such data sources allow us to investigate how lives unfold over time and identify key milestones, transitions, and outcomes across a wide range of areas. A range of disciplines, including epidemiology, criminology, sociology, economics and psychology, have increasingly adopted life course approaches, or some variation, as part of their conceptual toolbox to explain various outcomes (Alwin, 2012).

This chapter provides an overview of the key elements of a life course approach, explains some of the key differences across disciplines and the strengths and weaknesses of a life course approach for understanding the role of families in the transmission of (dis)advantage. We discuss how a life course approach may help to explain intergenerational disadvantage in Australia including in the early years, during adolescence and adulthood and present recent evidence on intergenerational inequality in Australia. In doing so, we outline some of the conceptual and substantive issues guiding the analyses presented in later chapters on the early years, education, labour markets, marriage, parenthood and ageing, as well as explain how a life course approach might assist to understand outcomes for specific social groups such as migrants and refugees, Indigenous children and LGBTQ+ groups.

What Is a Life Course Approach?

What Is the Life Course and Why Should We Study It?

The life course perspective focuses on understanding life-long human development as embedded in historical social context (Elder et al., 2003). Focusing on “changing lives in changing contexts” (Elder & Shanahan, 2006, p. 667), the life course describes the trajectories of a human life from birth to death, structured and shaped by age-graded social roles, and historical and interpersonal contexts (Katz et al., 2012). In life course research, event trajectories are compared across individuals or groups on the basis of timing, duration, and rates of change (Giele & Elder, 1998). The perspective is widely referenced in multiple disciplines because it unites individual and institutional factors, guiding lines of inquiry that are appropriate to studying increasingly diverse populations, in times of substantial social change (Alwin, 2012; Elder et al., 2003).

The Origins of the Life Course Perspective

The life course perspective is presented by Elder and Giele (2009) as a research paradigm originating from theoretical developments in the 1960s and growing to great influence in social science over the ensuing half-century. Following a turn in the 1950s towards ‘contextualisation’ of research findings through social history, this theoretical work sought to investigate connections between the significant social changes occurring at the time and life patterns under study, considering historical events and cohort differences. At the same time, as populations aged in the United States and Europe, more academic attention was directed towards later life stages, with theories moving toward understanding ageing as a life-long developmental process (Alwin, 2012; Elder et al., 2003). Work on ageing by Bernice Neugarten in the 1950s and 1960s, and Matilda Riley and colleagues in the early 1970s, has been credited with connecting life course research with temporality, by discussing age-defined social roles and the normative dimension of transitions and timing, and the importance of birth cohort to life chances, respectively (Elder & Giele, 2009; Elder et al., 2003). This focus on time and temporal organisation provides the common foundation for cross-disciplinary collaboration and the accumulation of a body of knowledge, which has contributed to the emergence of the paradigm in social research (Giele & Elder, 1998). This research depends on longitudinal methodologies capable of tracking individuals over time. From the early 1970s onwards, the life course perspective became the model for developing national surveys and quantitative social research (Elder & Giele, 2009).

Differing Definitions in the Life Course Literature

Any review of the literature shows a broad glossary of ‘life’ concepts complicated by overlapping and conflicting definitions for key terminology. Among the terminology which require defining are life stages, life cycles, and the life span. The term life stage is underpinned by a conceptualisation that across the life course, individuals age sequentially through a series of roles or states (Alwin, 2012). These life stages, understood to be biologically- and socially defined phases, such as infancy, childhood, adolescence and adulthood, help explain the timing, duration and transitions between age-graded social roles within the life course. Life stages do not have defined boundaries and may vary in quantity and duration according to life circumstances and historical and geographical contexts.

The life cycle, using terminology drawn from the biological sciences, describes the complete sequence of life stages between birth and death (Alwin, 2012). The concept is widely regarded to have limited analytical utility in the social sciences, because it arguably implies that this sequence is universal and fixed, failing to reflect the socially-defined nature of life stage transitions and the increased prevalence of divergent life course trajectories, such as in reproductive decisions (Alwin, 2012). However, Hogan (2001) suggests that because the life cycle describes the framework for age-graded social roles, it sets the standard which then gives meaning to life course studies of transitions and timings. The life cycle concept is also suggested to be useful for understanding intergenerational processes of socialisation, and processes of societal change as cohorts successively replace each other over time (Alwin, 2012; Elder & Giele, 2009).

Life span is used in general terms to refer to the extent of a life, which for life course research sets the scope for inquiry, in which the life course is nested as the life trajectory of transitions and timings (Elder et al., 2003). However, in psychology, the life span theory of human development defines aging as a life-long process of within-person change over time, adapting to individual and environmental contexts (Alwin, 2012; Oris et al., 2009). This definition bears strong similarities with the considerations of life course research. Interdisciplinary work in the early 2000s by scholars from life course sociology and life span psychology initially aimed to link the two concepts, but has since moved into identifying where they diverge, as the life span developmental perspective is primarily interested in changes to functional capacities and behavioural adaptation, looking at the resources available to individuals, and self-regulatory strategies, whereas life course sociology is interested in institutional influences on diverging life course trajectories (Alwin, 2012; Oris et al., 2009; Mayer, 2009). In Elder’s theorisation about the life course, he integrates life span by emphasizing that human development and aging are life-long, continuous processes.

Paradigmatic Principles

Elder outlines four elements to the life course paradigm, which can be understood in a ‘hierarchy of generality’—location, linked lives, human agency, and timing. The first, historical and geographical location, highlights that social and historical events affect lives through providing specific opportunities and constraints. This is typically provided by studying birth cohorts, which use a historical definition of age by birth year (Elder & Giele, 2009). The second element, linked lives, underscores how lives are lived in relation to other people and influenced by them, and that these relationships, particularly kinship ties, can be enduring across historical events (Katz et al., 2012). Significant new relationships, such as formed through long-term partnering or marriage, can cause shifts in the composition of social ties. The third element is human agency, which accounts for the variations in life courses within given constraints, as humans ‘planfully’ construct their own lives. Elder and Giele (2009) describe the discrepancies between individual lives and the age-graded life course as a ‘loose-coupling’. Finally, the fourth element is the timing and sequence of life events that influence the life course. The antecedents and consequences of a life transition will be different depending on the event’s timing (Heinz & Marshall, 2003). The impacts of the sequence of events in a life course will also depend upon social and normative expectations and the decisions that individuals make in response.

Life Course Approaches and Intergenerational Inequality in Australia

A life course approach is particularly useful for understanding the intergenerational transmission of inequality. Within social science there is a long and strong tradition of research examining intergenerational transmission of opportunities and outcomes showing that disadvantage accrues over generations and that family background plays a key part in shaping outcomes for individuals (Blau & Duncan, 1967; Bowles et al., 2005; Duncan & Brooks-Gunn, 1997). While debates continue about how much intergenerational inequality exists in different countries, how to measure it and whether more unequal societies have higher or lower levels of social mobility (Corak, 2006, 2013), there is general agreement that family background is important for understanding social disadvantage, including across multiple generations (Bowles et al., 2005).

In Australia, there is strong evidence of intergenerational transmission of inequality. For instance, Huang et al. (2016, p. 373) using panel data from the Households, Income and Longitudinal Dynamics in Australia study (HILDA) found intergenerational earnings elasticity, a measure of the extent to which parental earnings determine their children’s earnings, of approximately 24–28%. This broadly accords with earlier studies, although depending on the methodological approach and the data used, measures of earnings elasticity in Australia vary between about 20% and 35% (Leigh, 2013; Mendolia & Siminski, 2016). In recent work, Deutscher and Mazumder (2019) estimate intergenerational mobility using income tax data from 1991 to 2015. They report an elasticity measure of around 18%, significantly lower than estimates based on survey data. Importantly they also show meaningful variations across geographical locations both across the country and within cities.

Intergenerational inequality is not only transmitted via earnings. Other work in Australia has focused on intergenerational transmission of welfare receipt with a systematic review in 2014 identifying about 30 empirical studies on this topic in Australia, substantially fewer than undertaken in many other western countries (Perales et al. 2014). The most recent work in this area shows that children of parents who receive welfare payments are almost twice as likely to be on welfare payments when they are adults compared to their counterparts (Cobb-Clark, 2019; Cobb-Clark et al., 2017). Moreover, there is evidence that children of welfare recipients need more intensive support and for longer time periods. The intergenerational correlation was particularly strong for those on disability payments, payments for those with caring responsibilities, and parenting payments for single parents. Overall, this suggests that parental disadvantage may be more harmful to children’s later life outcomes if it is more strongly driven by circumstances rather than personal choice. In later work Bubonya and Cobb-Clark (2021) unpack some of the mechanisms linking parental and offspring welfare receipt correlations. They argue that the primary mechanism is the failure to complete high school. Adolescents in welfare-reliant families experience more disruptions in their schooling and less financial support from their families leading to lower educational attainment. Risk-taking behaviour is also identified as a key mechanism underpinning intergenerational welfare reliance.

Other research has focused on the transmission of educational (dis)advantage from grandparents and parents to children (Hancock et al., 2018), the transmission of health outcomes across generations (Huang, 2020; James et al., 2020), the transmission of attitudes (Perales et al., 2021), joblessness (Curry et al., 2019), and the transmission of wealth (Lersch & Baxter, 2020). In sum, there is clear evidence of intergenerational associations which show that the playing field is not level for all children and that if we are to fully understand and address social and economic disadvantage in Australia, we need to understand not only the life course journeys of individuals, but also their family background.

Family Background and Intergenerational Inequality

Families can reproduce advantage and disadvantage by directly transferring genetic, social, economic, and cultural resources between parents and children, as well as by indirectly influencing life choices and pathways through shaping opportunities, experiences and orientations. While advantages and disadvantages can be passed from parents to children, the intergenerational inheritance of disadvantage also has particular consequences for communities, and governments. Over time, it contributes to enduring differences between population sub-groups, and the entrenchment of deep and persistent disadvantage. In this section we consider how family dynamics are associated with the transmission of inequality focusing specifically on family type, parenting time, parent employment characteristics (Lam et al., 2018), transmission of norms, values, orientations and resources (Salimiha et al., 2018). We present some recent findings from Australian research on intergenerational transmission of inequality in Australia. The research underscores how families matter in terms of children’s outcomes over the life course.

Family Type

In Australia, non-traditional families are on the rise with an increase in the proportion of children in shared residence arrangements (Nielsen, 2014). Therefore, understanding the implications of varying family types on children’s outcomes is of growing importance as children in non-traditional families, such as one-parent, blended, and step-families, show a higher prevalence of mental disorders, lower levels of cognitive ability, and lower academic outcomes than children in original families (Carlson & Cocoran, 2001; Lucas et al., 2013; Perales et al., 2016, 2017). The causal direction of this relationship is debated. Specifically, there is debate about whether family type has an independent effect on children’s socioemotional and behavioural outcomes (Carlson & Corcoran, 2001; Fomby & Cherlin, 2007; Pearce et al., 2013) or whether the socioemotional and behavioural challenges often associated with mental health disorders lead to parental stress and family breakdown (Wymbs et al., 2008).

Regardless of the causal pathways, family type remains an important consideration in understanding intergenerational inequality as adults continue to experience these effects of family type growing up. To illustrate, Bernardi et al. (2019a) and Lersch and Baxter (2020) found that individuals whose parents separate during childhood had less economic wealth as adults. Adult children whose parents separated during childhood had reduced education and earning capacities, unstable family structures, and a lower financial planning horizon in adulthood. Additionally, Bernardi et al. (2019a) found that adult children who did not live with their birth parents from ages 0 to 18 experienced a “wealth penalty” throughout their adult lives. A wealth gap started around their early 30s and grew over time. In sum, this body of work shows that childhood family structure continues to shape the outcomes of adult children over their life course. Overall, there is strong evidence that parental separation or divorce is negatively associated with children’s skills, education, wages, wellbeing, and own family behaviour as adults (Lam, 2020).

Parenting Time

Child development is intimately tied to the quantity of resources provided by parents, such as parental time with children, which provides opportunities for children to establish safe and secure relationships with parents. (Lam et al., 2018). In general, parenting time can refer to the time spent parenting by mothers, fathers, or both parents (Amato & Rivera, 1999; Cano et al., 2019; Lam et al., 2018). There are mixed findings on the effects of parental time on children’s outcomes (Cano et al., 2019; Milkie et al., 2015) because mothers and fathers provide different kinds of contributions to children’s development (Amato & Rivera, 1999), though it remains unclear whether fathers’ and mothers’ parenting are conceptually different (Fagan et al., 2014). Nonetheless, we draw on Fagan et al.’s (2014) argument and conceptualization of a more general model of parenting rather than on emphasizing separate conceptualizations of mother’s and father’s parenting behaviour. Thus, our review will focus broadly on parenting time, without much differentiation across mothers and fathers.

How parents spend time with their children is positively associated with children’s socioemotional and behavioural, competencies and non-cognitive skills. Parents are particularly crucial because young children develop a secure attachment with them. Likewise, parents represent a key source for children’s acquisition of these traits and skills. For instance, fathers’ time with children, often in the form of leisure and play, provides children with important social skills (Paquette, 2004). Additionally, parenting time has important consequences for children’s academic outcomes (Philipps, 2011). How parents spend time with their children is not the same and time spent doing educational activities are more important for children’s cognitive outcomes than other activities (O’Flaherty & Baxter, 2019; Cano et al., 2019).

Parent Employment

Parent’s employment is another important factor shaping children’s long-term outcomes. However, the effects of parental employment on children’s outcomes varies. On one hand, working parents have greater household income (Coley & Lombardi, 2013), better maternal mental health (Roxburgh, 2012), and expose children to formal child care (Gialamas et al., 2014), all of which can improve children’s socioemotional outcomes. On the other hand, too much time in employment can have adverse effects such as causing strain on the family in terms of work-family balance and conflict (Hsin & Felfe, 2014; Kelly et al., 2014) especially if mothers are working long hours. There is evidence that maternal employment has resulted in increased participation of fathers in child care (Gottfried et al., 2002). Nonetheless, parental employment can also negatively affect children’s behaviour by limiting parents’ time with children. These factors may negatively affect children’s socioemotional outcomes.

In general, Australian studies have shown evidence that maternal employment is associated with children’s improved socioemotional outcomes, though the studies vary in their findings about the magnitude of the effect (Huerta et al., 2011; Lombardi & Coley, 2017; Salimiha et al., 2018). For instance, Hadzic et al. (2013) found that mothers engaged in long work hours showed worse child behaviour, such as higher hyperactivity and inattention, though they found no effect of paternal employment on children’s behaviour.

Likewise, there is evidence of an association between parents who work longer hours or have lower job security and poorer child behavioural patterns (Lam et al., 2018). Again however, the evidence is mixed. Lombardi and Coley (2017) focused on maternal employment and found a neutral effect on children’s skills, while Huerta found a negative effect on children’s cognitive development (Huerta et al., 2011). Lam et al. (2018) found that maternal time but not paternal time was a more important factor in children’s behaviour. Father’s longer work hours was associated with better child behaviour but children of mothers who worked long hours has poorer behaviours (Lam et al., 2018). One possible reason is that mother’s work hours is associated with fewer opportunities for mother-child interactions and mother-child bonding. While mothers are more likely to protect their childcare time than fathers (Bianchi, 2007), the number of hours mothers work will still affect how much time they can spend with their children.

Transmission of Norms, Values, and Resources

The intergenerational transmission of disadvantage and advantage can occur through the transmission of norms, values, and resources. Parents may transfer socioeconomic resources, such as wealth to their children. This may occur via parents’ educational attainment, income, mental health, and occupation for example. Parents’ socioeconomic resources may be transmitted to children by shaping children’s wellbeing outcomes. There is evidence that children whose parents have lower work hours and earnings during early childhood, are more likely to experience early-adult disease, such as hypertension, arthritis, and limitations on daily activities. Raising the average income by $5000 over 4-year period would reduce the risk of adult arthritis and hypertension. Overall, this suggests that early low SES environments are associated with immune changes in human children (Ziol-Guest et al., 2012).

In addition to resources, family background can shape children’s outcomes via norms and attitudes. For instance, parents who experience periods of unemployment or joblessness can inadvertently yet negatively affect children’s attitudes toward work and education (Curry et al., 2019). Children may internalize parents’ inconsistent employment patterns, which may subsequently shape their own perceptions about continuous labour market participation or future aspirations. Another instance may be locus of control or the belief that there is a causal relationship between one’s own behaviours and the consequences for their lives (Baron & Cobb Clark, 2010). Cobb Clark et al. (2019) found a correlation between parents’ self-control and their children, indicating that children who exhibit higher levels of social control also have parents who report higher levels of social control. Additionally, parents transmit gender ideologies to their children, which could contribute to the reproduction of gender inequalities (Perales et al., 2021). In sum, this suggests the importance of looking beyond economic and financial resources in the intergenerational transmission of inequality to norms and values that may also determine important life outcomes.

Social Groups and Intergenerational Inequality

In this section, we examine intergenerational inequality in relation to specific disadvantaged communities and marginalized social groups. Social disadvantage tends to be concentrated in low-income communities and other disadvantaged social groups, including Indigenous Australians, non-English Speaking Background (NESB) migrants, humanitarian migrants, and single parent households. Below, we review intergenerational inequality across these four groups.

Indigenous Australians

In general, relative to non-Indigenous populations, Indigenous populations in Australia show large disparities in health outcomes, educational attainment, and other life chance measures (Salmon et al., 2019; Walter et al., 2017). Nonetheless, most Indigenous children show good or excellent health (Anderson et al., 2017). Given the history of colonialism, European settlement, dispossession of lands and discriminatory treatment of Indigenous people in Australia, intergenerational transmission may have less to do with parents and more to do with the trauma and inequities imposed by these broader circumstances. Furthermore, non-Indigenous and Indigenous children differ in several ways, which may affect their outcomes and the role of parental characteristics on these outcomes. For instance, Indigenous children tend to live in larger households (Biddle & Yap, 2010) with more kin and family members. Additionally, around 75% of Indigenous children live in a household that is either a single-parent household, contains adults with lower than Year 12 education, and no employment (Biddle & Yap, 2010). Around 21% of Indigenous children live in a household that shares all three characteristics compared with 5% of non-Indigenous children (Biddle, 2011). Indigenous children also tend to live in households belonging to the lowest income quintiles (Katz & Redmond, 2010) and socioeconomic disadvantage affects early childhood education attendance (Biddle, 2011).

Given these household characteristics, understanding intergenerational changes may require us to look beyond parents. To illustrate, De Bortoli and Thomson (2010) and Trudgett et al. (2017) found that parental SES may not work the same way as it does for non-Indigenous children’s schooling outcomes. Therefore, to understand mechanisms that positively shape Indigenous children’s schooling outcomes, we may need to look beyond those that are positively associated with non-Indigenous children (Trudgett et al., 2017). These issues are further explored in Chap. 4 where cultural identity and connection is identified as one of the key protective factors in shaping outcomes for Indigenous children.

Overall, the Indigenous population in Australia is relatively young so understanding their outcomes can further our knowledge about this population and how to successfully transition to adulthood (Biddle, 2011). We acknowledge that while parents play a role, the outcomes of Indigenous children are shaped by various outcomes, including geography, connection to cultural background, and racial discrimination (Lovett, 2017; Thurber et al., 2015). A life course perspective in particular is useful for understanding the intergenerational transmission of inequality among Indigenous children. More broadly, a life course approach that takes a holistic view across time, lives, generations and relationships has been argued to be a useful framework for improving health and social outcomes of other Indigenous communities (Theodore et al., 2019).

Migrant Background Populations

The effects of migrant background on social outcomes in Australia are typically understood via high-income or English-Speaking Background (ESB) countries or middle- and low-income countries or non-English Speaking Background (NESB) countries. While immigrants from ESB countries typically have outcomes that are on-par or better than the host population, immigrants from NESB countries tend to show greater disadvantages. For instance, NESB migrants tend to show lower levels of labour market outcomes, such as lower incomes (Katz & Redmond, 2010) and lower labour market participation relative to native-born Australians and immigrants from ESB countries (Wilkins, 2008).

There are mixed findings about whether these differences among immigrant adults are observed among their children. In general, children from NESB immigrant families in Australia still face challenges in their integration with some of this stemming from racial discrimination in school or growing up in a new context away from their connections in their origin country (Katz & Redmond, 2010). To illustrate, children from NESB immigrant households belong to households with lower incomes (Katz & Redmond, 2010) than their ESB counterparts and the overall Australian population. Nonetheless, it is also possible that this is concentrated in certain national origin groups, such as Vietnam and Lebanon, that tend to experience greater poverty and material deprivation. Likewise, children of NESB migrants tend to show lower levels of wellbeing (physical and mental health) and higher rates of obesity than the general population. These are related to lower SES and neighborhood location though these factors do not completely account for these disparities (Katz & Redmond, 2010; Zulfiqar et al., 2018).

In contrast, Cobb-Clark and Nguyen (2012) found that children of NESB show educational advantages over their ESB and native-born Australian peers. Additionally, Washbrook et al. (2012) did not find any significant differences in the development of young children of foreign-born and Australian-born families. In part, this may be explained by the fact that although parents may experience challenges in the labour market, many are still highly educated or arrive from higher-income origin countries (Washbrook et al., 2012). Overall, this may suggest a relatively optimistic outlook for immigrants’ children, even those with parents from NESB backgrounds who face more challenges.

Refugees

Unlike other groups of immigrants, refugees are a particularly vulnerable group. Refugees show low levels of labour market participation and income, limited English proficiency, poor mental health, and poor housing conditions (Colic-Peisker & Tilbury, 2007; Fozdar & Hartley, 2014; Hugo, 2014). Like other migrants these patterns tend to vary in relation to country of origin and gender (Perales et al., 2021). Refugee women are particularly disadvantaged and show low rates of paid employment and higher rates of psychological distress (Delaporte & Piracha, 2018; Jarallah & Baxter, 2019). Refugee children face multiple challenges related to family instability, lower health outcomes, and educational attainment. They have been identified as a high-risk group for poor mental health (Lau et al., 2018; McMichael et al., 2011) and not completing secondary school (Correa-Velez et al., 2017). For instance, Correa-Velez et al. (2017) found that nearly a decade after settlement, nearly 38% of refugee youth in their study had left school prematurely. Likewise, many still continue to experience long-term effects of social exclusion related to discrimination (Correa-Velez et al., 2015).

Nonetheless, much work has noted that refugee youth are still making strides relative to their parents’ human capital and socioeconomic characteristics, which may indicate intergenerational progress (Daniel et al., 2020; Zhou & Bankston, 1998). Similarly, despite their challenges, they appear to make improvement with time in Australia. For instance, Ziaian et al. (2013) found large improvements in the socioemotional wellbeing of refugee children and adolescents within a few years of resettlement. Overall, while refugee children still face challenges in their integration, understanding their starting points is an important reference point. More work and longitudinal data are needed to understand their outcomes as they transition to adulthood to assess the extent to which refugee youth are making progress relative to their parents.

Single Parent Households

Individuals in single parent households experience high rates of mental illness, shorter lifespan, poorer physical health, and food insufficiency (see review in Jovanovski & Cook, 2020). There is also evidence that the financial situations of single-parent households are becoming more dire with increases in relative poverty rates. In 2016, 15% of single-parent households were in poverty compared with 25% in 2018 (Broadway & Vera-Toscano, 2020).

Single parent households are showing decreases in their use of formal child care. In 2016, 52% of single-parent households used formal care compared with only 35% in 2018 (Broadway & Vera-Toscano, 2020). Although the exact mechanism is unclear, single parent households may stop using child care due to their lower income and high cost of child care. For many single parents in low-income employment, the take home income after child care does not justify employment. However, this may constrain their labour market opportunities if they do not have reliable child care.

New Developments in Life Course Theory

Life course theory is useful for explaining the intergenerational patterns reviewed above. The origins of life course theory date back several decades, but commentators have noted a growth in references to the term life course in academic papers throughout the 1980s and 1990 and a surge in the 2000s and 2010s (Bernardi et al., 2019b). Furthermore, recent growth in academic journals and research centres with the term life course in their title has also been remarked upon (Mayer, 2009; Bernardi et al., 2019b). In a 2006 Science paper, Butz and Torrey identify longitudinal surveys as the “Hubble telescope” of the social sciences arguing that the “fundamental challenge in the social sciences is moving from complicated correlations to useful prediction” (2006, p. 1898), Longitudinal surveys enabling consideration of life events and transitions provides a major step forward in moving social science from description to prediction.

While few would dispute the wealth of important new information provided by longitudinal surveys, other accounts of the potential of life course and longitudinal approaches are more measured (Macmillan & Hannan, 2020; Mayer, 2009). Ulrich Mayer, one of the founding fathers of life course theory, argues that the field has been highly successful in several areas—instilling a life course approach and new data and methods across disciplines, examining cross-national variations in institutional contexts on life courses, assessing the impact of sudden societal change on life courses and investigating the relationship between health and life courses (2009). But he also identifies areas where important progress in life course research is yet to be made, including identifying causal linkages across human lives, the interaction of psychological processes of development and socially embedded life courses and the development of an integrated overarching life course theory as opposed to a set of concepts and heuristics (Mayer, 2009).

In a related vein, Macmillan and Hannan (2020) argue that life course research has failed to make the most of opportunities to exploit natural experiments to develop causal explanations. They argue that by identifying important moments of historical change, variations in social structures, or policy changes it is possible for life course research to credibly develop causal arguments about social experience and human development. The assumption of such work is that groups of people are indistinguishable prior to a naturally occurring event or social change, that they are randomly affected by the event and sorted into identifiable treatment and control groups enabling identification of mechanisms of cause and effect. Macmillan and Hannan urge life course researchers to take up opportunities for these kinds of natural field experiments and to pursue causal theories and evidence.

Arguably one of the most innovative developments in life course theory in recent years is the work of Bernardi et al. (2019b) who have taken up the challenge of developing an overarching integrated life course theory. They define the life course as a multifaceted process of individual behaviour and develop a theory aimed at explaining the nonlinear dynamics of individual behaviour over time and across multiple dimensions. These dimensions are defined as inner-individual (e.g., genetics, biology, physiology), individual (e.g., education, social status, gender, citizenship), and supra-individual (e.g., socio-cultural environment ranging from networks and relationships to country institutional features). Importantly life course theory must be dynamic they argue, recognising the agency of individuals who make bounded or constrained choices based on their beliefs, experience and expectations of their actions.

They use the heuristic device of a life course cube to outline the complex interdependencies across these dimensions that explain contemporary life courses. The core axes of the cube are time, domains and levels. Time refers to the history of a life course, current experiences and future outcomes. Domains cover areas such as work, family, education, leisure that are interdependent and overlapping. Levels denotes the interdependence that connects individual agency with the life courses of other people, the external societal structures and the inner-individual dispositions and orientations. They argue that the life course cube offers a parsimonious heuristic device for integrating various approaches to life course research across disciplines. They recognise that not all life course research will address all elements of the cube, but that it serves as a reminder of the full complexity of interdependencies, levels, domains and dimensions that underly life course processes and outcomes.

In more recent work Sanchez-Mira and Bernardi (2021) have further argued for a more developed theoretical conceptualisation of time in life course research that goes beyond notions of time as absolute (linear, chronological and uniform) and incorporates understanding of relative time. Time has been a central concept in life course approaches but is often understood as linear and unidirectional following a chronological clock and calendar at a uniform pace. In contrast, Sanchez-Mira and Bernardi (2021) argue for a concept of relative time that is multidirectional with the remembered past and anticipated future influencing agency and decision-making in various ways, telescopic with individuals acting on the basis of differing time horizons where they zoom in and out of past and future events in ways that shape their actions, and elastic where individuals do not experience time as continuous, uniform or linear, but rather at different tempos and paces and distorted in various ways through subjective perceptions. Time is thus relative to individuals rather than absolute and an integral part of understanding agency as opposed to an objective measure of cohort, period or ageing.

Overall, this brief review shows the power of life course theory to explain social disadvantage over the life course and across generations. But it also highlights the need for further new developments in life course scholarship to move beyond a set of related concepts to an integrated overarching theoretical framework. There is lively and constructive debate occurring in the literature about these new ideas with scholars pushing the life course framework forward in useful ways (Mayer, 2009, Bernardi et al., 2019b). Importantly these new directions are aimed at informing and aiding more powerful empirical studies with implications for study designs, measurement, methodology and interpretation. And there are continuing moves to collect, access and analyse longitudinal data that enables a life course approach to understanding a wide range of social outcomes and to effectively inform policy directions.