Pathways into childbearing delay of men and women in Australia

Author: Ester Lazzari1
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  • 1 Australian National University, , Australia
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Childbearing delay is a pervasive feature of Australian society, but little research has been conducted to examine how socio-economic factors are linked to childbearing timing among Australian men and women. This paper addresses this by analysing the timing of first childbirth for a large sample of Australian residents (N = 4,444). The findings indicate that childbearing delay is socially patterned and that life course experiences shape the risk of delaying childbearing across genders. Having a tertiary qualification delays the transition to parenthood, especially for women. An uninterrupted career prolongs time to parenthood for women but accelerates it for men. Low occupational prestige, being married and having been in only one co-residential union are associated with earlier parenthood for both men and women. For each increase in education level, not being married is associated with increasing levels of childlessness. Clear-cut gender differences are found in the relationship between childlessness and childbearing delay.

Abstract

Childbearing delay is a pervasive feature of Australian society, but little research has been conducted to examine how socio-economic factors are linked to childbearing timing among Australian men and women. This paper addresses this by analysing the timing of first childbirth for a large sample of Australian residents (N = 4,444). The findings indicate that childbearing delay is socially patterned and that life course experiences shape the risk of delaying childbearing across genders. Having a tertiary qualification delays the transition to parenthood, especially for women. An uninterrupted career prolongs time to parenthood for women but accelerates it for men. Low occupational prestige, being married and having been in only one co-residential union are associated with earlier parenthood for both men and women. For each increase in education level, not being married is associated with increasing levels of childlessness. Clear-cut gender differences are found in the relationship between childlessness and childbearing delay.

Key messages

  • Life-course experiences shape the risk of delaying childbearing.

  • Tertiary-educated women are more than twice as likely to delay childbearing compared to their male counterparts.

  • Marriage is a salient predictor for early entry into parenthood, despite of educational attainment.

  • Clear-cut gender differences exist in the relationship between childlessness and childbearing delay.

Introduction

Changes in the family formation processes across the post-industrialised world involve the delay of childbearing to later ages (Frejka and Sardon, 2006; Sobotka, 2017), a phenomenon often referred to as postponement transition (Kohler et al, 2002). In Australia, the trend towards later parenthood started in the early 1970s, reversing the shift towards earlier first births observed during the post-war years (ABS, 2001). Since then, the age at parenthood has been rising relentlessly among both men and women, as a consequence of the deferment of first births to more advanced reproductive ages (Carmichael, 2013). Recently, the median age at birth has surpassed 31 for women and 33 for men (ABS, 2017), without showing signs of reversing. According to the most recent Australian Bureau of Statistics (ABS) data (2019), 24% of Australian births were registered among women aged 35 years old and above, a large increase on the 5% recorded in the mid-1970s. Childbearing at advanced ages tends to be even more pronounced among men. In 2018, 39% of births were registered among men aged 35 and above, compared to 15% in 1975 (ABS, 2019). These trends have been highlighted also by analyses of cohort fertility, which show that fertility under age 30 has been steadily declining among Australian women born after the mid-1940s (Lesthaeghe and Moors, 2000; Kippen, 2006). The term postponement suggests that childbearing will be recuperated at older ages; however a complete recuperation later in reproductive life is unlikely (Kohler et al, 2002). In Australia, the declines in fertility at younger ages have not been fully compensated by increases in fertility at older ages, leading to a long-term decline in completed cohort fertility (Kippen, 2006), especially for cohorts born from 1980 onwards (McDonald, 2020), and to an increase in the proportion of those remaining permanently childless (Lazzari, forthcoming; Rowland, 2007), which also tends to be more pronounced among men than among women (Gray, 2002).

Increasing childbearing age represents a risk for the successful realisation of fertility plans (Schmidt et al, 2012), as fecundity naturally declines with age. From the observation of natural populations with no use of contraception, female fecundity starts declining in the mid-20s (Eijkermans et al, 2014), with the decline accelerating from age 32 (Johnson and Tough, 2012). Male fecundity is also likely to deteriorate with advancing age, especially after 40 (Johnson and Tough, 2012), although literature in this regard has provided contrasting results (Chen et al, 2008). The delay in childbearing is considered to be one of the main reasons why an increasing number of couples is seeking assisted reproductive treatment (ART). Utilisation of this technology in Australia is among the highest in the world (Adamson et al, 2018), partly due to a relatively supportive policy environment for ART, which is subsidised through the public health insurance scheme, Medicare. From one perspective, this is an enlightened policy that has increased the chances of infertile couples to achieve their reproductive goals. However, despite the conventional wisdom among lay men and women that ART is able to remediate age-related fertility decline (Peterson et al, 2012; Eriksson et al, 2013; Bodin et al, 2017), there is currently no ART treatment strategy that can fully compensate for it (Leridon, 2004; 2017).

Physiological limits to reproduction are not the only reason why childbearing delay is associated with lower completed family size, but social and cultural reasons can also play an important role. Repeated postponement can eventually lead to the abandonment of the fertility desires because individuals may get in the habit of a childless lifestyle and become reluctant to change it (Carmichael and Whittaker, 2007), or they may revise their desires downwards if they perceive they are not likely to be fulfilled (Gray et al, 2013). Additionally, the existence of social age deadlines to childbearing, according to which it might not be socially acceptable to have a child at an advanced reproductive age, even though below the biological limit, may discourage people from trying (Settersten and Hagestad, 1996; Billari et al, 2010).

Despite childbearing delay being a pervasive feature of Australian society, very little research investigates the factors associated with changes in childbearing timing among Australian men and women. Previous research is limited to a descriptive typology among women (Miranti et al, 2009; Lazzari, 2019) and to analyses of the early lifecourse variables and socio-economic predictors of childlessness (Parr, 2005; 2010). Understanding the factors associated with childbearing delay is important because it can facilitate the provision of appropriate policy schemes to support childbearing at younger ages. Policies could have two main effects: (1) decreasing the probability of women experiencing adverse pregnancy outcomes associated with advanced maternal age, and (2) influencing fertility levels by shifting the timing of fertility to lower ages (Lutz and Skirbekk, 2005). Furthermore, the success rate of ART could be largely improved if women take advantage of it earlier rather than later in life (Kocourkova et al, 2014), providing an extra point of leverage to affect fertility.

Using a parametric survival model of the time to first childbirth, this paper explains the socio-economic factors associated with childbearing delay and permanent childlessness by analysing the timing of entry into parenthood for a large sample of Australian residents. Two key questions are addressed:

  1. Do educational, employment and relationship life course experiences affect the likelihood of delaying childbearing and of remaining permanently childless in Australia?

  2. Does the impact of educational, employment and relationship life course experiences on delaying childbearing and on remaining permanently childless vary by gender?

Time of entry into parenthood is separately modelled for men and women in order to investigate gendered effects of childbirth. Most empirical studies do not include men, because of technical reasons. However, the few studies that analyse factors associated with entry into parenthood for men and women reveal clear gendered pathways (Keizer et al, 2008).

Pathways into childbearing delay

Education and employment

Factors traditionally associated with the decision to delay parenthood mostly emphasise the rational aspects of having children. According to the New Home Economics theory (Becker, 1965; 1981), childbearing is a voluntary choice, based on the evaluation of the costs and rewards of becoming parents. Compared to less-educated people, highly educated individuals have a greater earning potential and, therefore, they face higher opportunity costs on becoming parents, as they would forgo a greater amount of income when taking time out for children. Although Becker’s theory is not explicitly a model of how education and work trajectories lead to childbearing delay, higher education can be seen as an incentive to delay childbearing because highly educated individuals experience higher opportunity cost at the beginning rather than later in their careers (Liefbroer and Corijn, 1999; Joshi, 2002). Another way that educational attainment may lead to later childbearing is by triggering the delay of subsequent major life course events (Hagestad and Call, 2007). The completion of education is an important marker in the transition to adulthood and it usually precedes family formation (Hoem, 1986), as it is socially expected that young people will enter into marriage or parenthood once they have completed school (Blossfeld and Huinink, 1991; Ní Bhrolcháin and Beaujouan, 2012). Since higher educated individuals have longer enrolment periods, the delaying effect of education tends to be longer at higher educational levels (Kneale and Joshi, 2008; Neels and De Wachter, 2010; Nisén et al, 2014; Rybińska, 2014; Berrington et al, 2015). After the completion of education, further delays in childbearing may be experienced as people build careers or financial security (Kravdal, 1994; Martin, 2000).

At the same time, the higher average income of better-educated people makes children more affordable, leading to a positive relationship between childbearing and education. In Becker’s analysis, the income effect is important for men, while the opportunity-cost argument is important for women. The relationship between education and fertility is different for men and women because of the specialisation of tasks within the household, with women specialising in homemaking activities and men specialising in breadwinning. Becker argues that marriages gain from such specialisation of tasks, where each partner brings something different into the household that has value for the other partner. In this approach, entry into parenthood hardly interferes with men’s roles in the household. By contrast, their higher earning potential makes them attractive in the marriage market, as they can better provide financial support to their families. For women, the combination of mother and worker roles is more problematic, as they play the main part in rearing children. The opportunity cost of leaving the labour force is particularly high for those who are better educated and at the start of their careers, which implies that it is a rational response for them to avoid childbearing when young.

Becker’s specialisation model has been criticised for being inadequate in explaining the modern division of household tasks in the family and for paying only limited attention to men (Oppenheimer, 1994). The model is based on the assumption that women face a great imbalance between family and career. However, the incompatibility between employment and family is weakening, because of a more egalitarian division of tasks between partners within the household and because of the implementation of family policies favourable to the combination of parenting and working (McDonald, 2000; 2013; Esping-Andersen and Billari, 2015; Goldscheider et al, 2015). In Australia, traditional gender roles expectations have not fully disappeared, despite the progress made towards a more gender-equal society. This would explain why, despite the increase in women’s education and labour-force participation, women are still more involved in homemaking activities than men are (Baxter, 2002), especially when there are children involved (Craig, 2005; Baxter et al, 2008; Chesters et al, 2009). The enduring gender gap in the time spent on housework has been described as a manifestation of the existence of gender structures in society (Bernhardt, 1993), which are psychologically ingrained social constructs that guide individual action. In sociology and gender studies, the doing gender approach (West and Zimmerman, 1987) emphasises that members of a society are judged by and held accountable for virtually every activity they engage in based on their gender. The normative conceptions regarding what is considered appropriate male and female behaviour may evolve over time and in different contexts, but gender roles persist and are generally slow to change. Hence, within a household, the division of labour between men and women is based on their gender role, which, traditionally, has involved opposing activities. Discrepancies between traditional standards and the actual division of labour can increase tension as a consequence of not meeting the social expectations associated with one’s gender. Childbearing delay may correspond to an attempt of better-educated women to reconcile work participation with family formation by focusing on career first and childbearing after, once they will be in a better position to fulfil their gender role’s expectations.

Relationships

The arguments presented have predominantly considered childbearing delay as a voluntary choice, based on the evaluation of the costs and rewards of becoming parent. Another strand of literature exploring factors influencing individuals’ decisions to become parents has emphasised the importance of life circumstances that are beyond people’s control, such as being with the right partner (Testa, 2007; Cooke et al, 2012). In an examination of women’s reasons for childlessness in Australia, Graham et al (2013) found that having never been in the “right” relationship accounted for almost half of the reasons for being childless, while being in a relationship where the partner did not want to have children accounted for an extra third. These results are also reflected in Carmichael and Whittaker’s (2007) finding that the difficulty in forming stable relationships with partners is one of the main reasons for being childless among Australian women.

Studies employing sequence analysis techniques have shown that partnership histories significantly affect the likelihood of ending up childless (Mynarska et al, 2015; Mikolai, 2017; Jalovaara and Fasang, 2017; Raab and Struffolino, 2019; Saarela and Skirbekk, 2020). Although cohabitation has become increasingly common in Australia, the majority of childbearing still happens within marriage (ABS, 2017). Persistent differences remain between the two union types: cohabitation is often seen as a way to test the relationship, before the ideal and longer commitment of marriage (Carmichael and Whittaker, 2007; Perelli-Harris et al, 2014). Therefore, while cohabitation may be considered as a first step towards marriage and, hence, childbearing, at the same time it may lead to its delay, especially if it does not end in marriage. The literature presents mixed views regarding the impact of the entry into multiple relationships on the likelihood of becoming parent (Keizer et al, 2008; Saarela and Skirbekk, 2020). On one side, they might contribute to delay fertility and increase the risk of remaining permanently childless. On the other, multiple partners represent more chances for having children. In Australia, marriage is the transition most commonly and clearly associated with entry into parenthood by age 35, while multiple relationships are linked with a higher probability of delaying childbearing (McDonald and Reimondos, 2013).

Hypothesis

In line with the theoretical and empirical framework already presented, the following three hypotheses regarding the influence of life course experiences on the timing of childbearing are formed:

  1. H1Having a high educational attainment will be associated with later entry into parenthood for both men and women.
  2. H2Being employed in high-prestige occupations and having an uninterrupted career will be associated to a later transition into motherhood but not into fatherhood.
  3. H3Entering marriage and having been in only one co-residential union will be associated with a shorter time to first childbirth for both men and women.

Data and methods

Given that the aim of this study is to analyse the relationship between life course pathways and first childbirth, the life course perspective (Elder, 1994) is adopted as the overall conceptual and methodological framework. The life course perspective states that life transitions – such as the birth of a child – are part of social trajectories that give them meaning and form. As a consequence, this study avoids using current statuses to analyse the factors associated with the timing of childbearing. By contrast, the aim is to capture the educational, employment and relationship experiences of individuals over their entire life course.

Data

Data for this study are from the Household, Income and Labour Dynamics in Australia (HILDA) survey, a nationally representative panel study that surveyed over 13,000 individuals aged 15 years and over in the first wave (see Watson and Wooden (2012) for further details). Data were collected from each person using face-to-face interviews and self-completed questionnaires. Initial interviews were conducted in 2001, with annual subsequent interviews (2018 is the most recent year available). In some aspects, the HILDA sample differs from the Australian population. Specifically, individuals born in a non-English-speaking country, of Aboriginal or Torres Strait Islander descendent, unmarried, and unemployed or working in low-skilled occupations tend to be under-represented (Watson, 2012). Most notably, a group that has been particularly under-represented is that of immigrants arriving in Australia after the original sample was selected (Watson and Wooden, 2010). The addition of a general population-wide top-up of the sample in wave 11 has helped to alleviate biases in the estimates (Watson and Wooden, 2013). For the most part, estimates of the population characteristics are comparable with the ABS estimates (Summerfield et al, 2019: 113–21), and weights have been used in all summary statistics to adjust for the small discrepancies. A detailed description of the weighting methodology can be found in Watson (2012).

Analytic sample

In order to achieve an adequate sample size, respondents from all surveyed years aged 45 at the time of data collection were combined in one sample. A small number of cases were excluded due to data quality associated with fertility information (12 observations), or missing information on one or more variables (352 observations). This resulted in a sample of 4,444 respondents (47% males and 53% females), born between 1956, if they were selected in wave 1, and 1973, if they were selected in wave 18.

Primary independent variables

The aim of this study is to examine the effects of three variables on the timing of first birth: educational attainment, employment activities and relationship histories. Retrospective information is used to allocate events over the life course of the respondents or to make a summary of their life course experience. Current statuses are not considered, as they can mask the importance of previous experiences. An exception is occupational prestige, which was measured at age 45. The educational level of each respondent has been categorised in three groups:1 low (0), for Year 11 or below qualifications; medium (1), for Year 12 qualifications and for degrees obtained through vocational education and training institutions; and high (2), for any tertiary degree obtained through university.

Occupational prestige was grouped in three categories, based on the Australian Standard Classification of Occupations (ASCO). These comprise: high-prestige occupations (0), for managers, administrators and professionals; medium-prestige occupations (1), for associate professionals, tradespersons and related workers, clerical, sales and service workers; and low-prestige occupations (2), for blue collar jobs and elementary clerical, sales and service workers. The low-prestige occupations category also includes 797 individuals currently not in the labour force, either because they were unemployed (n = 136), or not working (n = 661). In order to better capture the life course experience of the respondents, the time spent outside of the work force was also included, measured as the percentage of time out of the working life spent not working (unemployed or out of the labour force). A person’s working life was set to start when full-time education was left for the first time.

Relationship histories include marital and cohabitation experiences. For marital status, a dummy variable was constructed, including ever married for currently married, separated, divorced or widowed individuals (0) and never married (1). For relationship histories, the total number of co-residential unions (either marriage or cohabitation) experienced until the age of 45 was used. In this case, the aim was to capture a life course experience rather than investigating a causality relationship. These are the variables included in Model 1 and their effect on the time to first birth represents the primary interest of this study.

Controls

Several controls are included for factors that have been found to be strongly associated with fertility behaviour. Consistent with previous Australian research showing that early life course variables have a significant effect on the probability of entry into parenthood among both men and women (Parr, 2005; 2010), four family background measures were included. The first is a dummy variable for the number of siblings a respondent has, including no siblings (0), and one or more siblings (1). The second is a categorical measure for the mother’s occupational prestige, including never worked (0), employed in a low-prestige occupation (1), employed in a medium-prestige occupation (2), and employed in a high-prestige occupation (3). The third variable indicates whether the respondent is Aboriginal or Torres Strait Islander (= 0). The fourth variable regards the region of origin and indicates whether the respondent is born in Australia (0), in a main English-speaking overseas country (1) or in another overseas country (2). A variable of the age when the respondent moved out of home was also included, as the process of leaving the parental home is considered an important milestone in the transition to adulthood. In the past, marriage was traditionally the primary reason for leaving home; however, the decision to leave has become increasingly independent from the decision to form a family (Goldscheider and DaVanzo, 1989). In Australia, the percentage of young adults living at home sharply decreases after the age of 17 (Baxter, 2016), suggesting that the process of leaving home easily precedes that of becoming a parent. Evans (2013) shows that less than 15% of Australians move out of home and directly enter into relationships, and, the relationships are much more likely to be cohabitations rather than marriage.

There is also a marked geographic variation in fertility in Australia (Gray and Evans, 2017), so a measure indicating whether the respondent lived in a major urban area (0), or in remote and very remote Australia (1) was also included. The year of birth is grouped into three 5-year cohorts, and is included in the full model in order to capture the effect of historical context. These variables are not the focus of this research and, therefore, their association with the outcome variable will not be discussed extensively. However, as they are significantly associated with fertility behaviour, it is of interest to test the significance of the main explanatory variables after their effect has been removed.

Despite the relationship between marriage and entry into parenthood having increasingly weakened, the majority of childbearing still happens within a union. Hence, the decision to have a child is generally made by a couple, and it is therefore related to both partners’ characteristics. Education and employment situations affect people’s intention to have a child, which in turn can have a strong influence on their partners’ probability of becoming parents. Previous research has shown that both partners need to intend to have a child for the couple to do so, especially for first births (Duvander et al, 2020). Due to the retrospective nature of this study and to the inclusion of both partnered and unpartnered individuals, it was unfortunately not possible to include these key partner’s characteristics in the analysis.

Analytic strategy

The likelihood of having a first birth is analysed using discrete time event history analysis (Allison, 1982). The analysis focuses on men and women who are at the end or at an advanced stage of their reproductive life, and assesses how educational, employment and relationship histories contribute to the probability of delaying first childbirth and of remaining (permanently) childless. Another less complex approach could have been to model childlessness as a logistic regression outcome. However, adopting a survival analysis approach is a better strategy for the purposes of this study because the outcome of interest of this analysis is not only if the respondents were childless at the end of their reproductive years, but also when they entered parenthood. Survival analysis methods provide an analysis of the timing of occurrence and generate predicted times to event for different categories at risk of experiencing the event of interest.

The likelihood of having a first birth is modelled separately for men and women from the onset of the reproductive life (considered to be at age 15 for both sexes). This allows the understanding of gendered effects on birth timing. The observation time for each individual ends with whichever of the following events occur first: birth of the first child or 45th birthday if they have not had a child (censored). Time is measured in years and first-birth rates are assumed to be piecewise constant over a one-year interval.

For women, the end of the observation period approximately corresponds to the end of the reproductive span; this is not the case for men, who have different reproductive limits compared to women. Despite being statistically rare, some men do become first-time fathers after the age of 45. Therefore, while right censoring is unlikely for the female sample, it cannot be excluded for the male sample, with the consequence that childlessness may be slightly overestimated among men.

For the analysis, the parametric log-logistic regression model was used. In its linearised form, the model can be written as
(1)
Where is the time until the birth of a first child, is a vector of covariates and is the error term, which follows a logistic distribution. The hazard of having a first birth in each interval , given that the event has not yet occurred, is expressed as
(2)

where is a scale factor and is a shape parameter.

Parametric models make distributional assumptions about the hazard rate. In the case of the log-logistic distribution, the assumption is that the hazard rate is nonmonotonic, which means that it increases and decreases at different intervals. From empirical evidence, it is known that the hazard rate of having a first birth follows an inverted U-shaped pattern: it monotonically increases at younger ages, it reaches a peak and then it monotonically declines. Therefore, the nonmonotonic assumption is suitable for modelling first-birth rates as well as other household formation processes following an inverted U-shaped pattern (Billari, 2001; Tavares, 2016). Figure 1 plots the estimated probabilities of having a first birth for the men and women in the analytical sample. The figure clearly shows that for the HILDA respondents, the hazard of having a birth monotonically increases until the late 20s and monotonically declines thereafter.

In the graph, the horizontal axis is scaled from 15 to 45 in increments of 5 units and the vertical axis is scaled from 0 to 8 in increments of 2 units. The graph shows the following first birth percentages for men and women and of different ages. Men: 15, 0.3%; 20, 1.8%; 25, 6%; 30, 7.5%; 35, 4%; 40, 1.4%; 45, 0.5%. Women: 15, 0.3%; 20, 5%; 25, 6%; 30, 5%; 35, 2.4%; 40, 1%; 45, 0.3%. All values are estimated.
Figure 1:

First-birth distribution by age and sex, unweighted

Citation: Longitudinal and Life Course Studies 13, 2; 10.1332/175795921X16197735939121

Source: Author’s calculations using data from the HILDA survey, waves 1–18, release 18.

Apart from the plausibility of the shape of the hazard function, the model specification was based on the comparison of the Akaike information criterion (AIC) of the log-logistic and of another plausible parametric model, the log-normal distribution. The possibility of using the semiparametric Cox proportional hazard model, which is more commonly used in medical research to investigate the survival time of patients, was also considered. Although results were similar to those obtained from the parametric models, the proportionality hazard assumption was violated. In other words, the ratio of the hazards for any two individuals was not found to be constant over time. Therefore, the Cox model was not adequate to model the survival time of the respondents. Furthermore, estimators for semiparametric models are generally less efficient than maximum likelihood estimators for a correctly specified parametric model (Powell, 1986).

Results

Descriptive analysis

In the sample, 18% of men and 14% of women did not have a child by the end of their observation period (Table 1). From the comparison in the share of childless individuals across genders it can be noticed that socio-economic status variables are associated with childlessness in opposite ways for men and women. For instance, men who are low educated (21%) and unemployed or in low-status occupations (21%) have a higher probability of being childless compared to men with tertiary degrees (17%) and employed in high-status occupations (17%). By contrast, women with Year 11 qualifications or below (8%) and who are unemployed or in low-status occupations (11%) have the highest chance of having a child, while higher education (22%) and employment (19%) is associated with remaining childless. Among the married respondents, only 8% are childless, while among those that never married being childless is considerably more common. For women, having been in one or two co-residential unions is associated with a slightly lower probability of being childless (10%) compared to having been in three or more unions (15%). For men, the number of unions appears to have an inconsistent relationship with the probability of remaining childless.

Table 1:

Descriptive statistics of childlessness by sex, unweighted percentages

Childless (%)
Men (N = 2,066)Women (N = 2,378)
Total sample18.313.8
Socio-economic status
Educational attainment
Year 11 or below21.28.3
Year 1217.612.3
Tertiary17.221.7
Occupational prestige
Unemployed/Low20.710.7
Medium16.212.0
High16.919.1
Time spent out of work
Never out of work13.029.8
Out of work21.112.0
Relationship histories
Marital status:
 Ever married8.37.9
 Never married61.050.6
No. of unions:
 094.884.3
 114.89.8
 213.810.2
 3+15.015.0
Demographic characteristics
Country of birth:
 Australia18.014.5
 Main English-speaking country22.015.5
 Other16.59.0
Aboriginal status:
 Not Aboriginal18.413.9
 Aboriginal or Torres Islander11.111.1
Birth cohorts:
 1956–6117.113.6
 1962–6719.713.4
 1967–7318.114.4
Background
Age left home:
 Still at home85.766.7
 efore 2116.411.9
 21 or after20.117.2
Mother’s occupational prestige:
 Never worked18.611.1
 Low17.312.4
 Medium19.315.1
 High17.015.2
No. of siblings:
 Only child25.414.5
 1 or more siblings18.113.8
Remoteness area:
 Urban20.215.9
 Rural15.010.5

Source: Author’s calculations using data from the HILDA survey, waves 1–18, release 18.

Figure 2 presents the interquartile ranges (IQRs) of ages at first childbirth of men and women across different social groups. On average, men and women with higher qualifications have their first child three and five years later than those with lower education. Around a quarter of highly educated women have their first child at an advanced reproductive age (after 32 years), suggesting that a higher proportion of them is likely to experience infertility compared to women in lower education groups. For men, despite a delay in childbearing among the higher educational categories, first births are still largely occurring within the most fertile age range. The IQRs are narrower for women with Year 11 and Year 12 qualifications compared to those who are tertiary-educated. The opposite trend is observed for men, where low education categories show more age-heterogeneous patterns compared to those with a tertiary degree.

In graph (A), the horizontal axis has three markers, namely year 11, year 12, and tertiary and the vertical axis is scaled from 20 to 40 in increments of 10 units. The graph shows that the medians for men and women with year 11 education are 27 and 23, respectively, year 12 education are 28 and 26, respectively, and tertiary education are 33 and 30, respectively. In graph (B), the horizontal axis has three markers, namely low, medium, and high and the vertical axis is scaled from 20 to 40 in increments of 10 units. The graph shows that the medians for men and women with low occupational prestige are 28 and 25, respectively, medium occupational prestige are 30 and 27, respectively, and high occupational prestige are 30 and 28, respectively. In graph (C), the horizontal axis has two markers, namely ever married and never married and the vertical axis is scaled from 20 to 40 in increments of 10 units. The graph shows that the medians for men and women who were ever married are 28 and 27, respectively, and who were never married are 30 and 27.5, respectively. All values are estimated.
Figure 2:

Boxplot of fathers and mothers age at first birth, Australian cohorts born 1956–1973

Citation: Longitudinal and Life Course Studies 13, 2; 10.1332/175795921X16197735939121

Note: The boxplots represent the distribution of births by age of parents with different socio-economic characteristics. The median age corresponds to the vertical dark thickened band near the middle in the boxplot. The boxes show the interquartile ranges, which correspond to the middle 50% of scores, while the whiskers show values below the 25th percentile and above the 75th percentile. The dots located outside of the whiskers show observations that are numerically distant from the rest of the data (outliers).

Looking at the occupational status of respondents, men and women in high-prestige occupations show two and four years higher mean ages at first childbirth compared to those employed in low-prestige occupations or unemployed, respectively. The IQRs tend to be wider among women in low-status occupations, whereas the distribution of age at first birth for those employed in more prestigious occupations is less dispersed. Having been married is clearly associated with younger ages at first birth for both genders. On average, married men and women have their first child two and four years younger than those who never married, indicating that marriage is associated with a pattern of earlier entry into parenthood. For every analysed variable, men show later mean ages at first birth compared to women. This has a biological explanation in that women have a shorter reproductive life compared to men. Therefore, while factors such as education might lead to delayed childbearing among both genders, women have a shorter period of time to catch up. This also has a social explanation in that men tend to partner with women slightly younger than themselves.

Analytical results

The maximum likelihood estimates of the log-logistic model are shown in Table 2. Model 1 shows the estimated coefficients of the main explanatory variables, namely: educational attainment, employment activities and relationship histories. Model 2 includes all the control variables. According to the AIC and BIC criteria, Model 2 constitutes a better-fit model. Columns 3 and 6 indicate whether gender differences are statistically significant. These differences are tested by looking at the significance level of the gender interaction term in an interaction model (not shown). As many of the variables used in the analysis are potentially highly correlated, sensitivity tests were run to identify collinearity. These were not statistically significant (not shown). For women, there is a clear educational gradient in the time of entry into motherhood, with tertiary-educated women expected to become mothers later compared to those with lower qualifications. Having a tertiary degree increases the time of entry into motherhood of 60%,2 or 6.7 years. For men, the effect of educational attainment on the time of entry into parenthood is also positive, but not nearly as strong as it is for women. The estimates show that men with a tertiary degree are expected to make the latest entry into fatherhood, with an increase of time to first birth of 25%, or 3.1 years compared to the reference category. Having a Year 12 qualification is associated with a shorter delay of 9%, or 1.2 years.

Table 2:

Maximum likelihood estimates from the log-logistic model of time to first childbirth, cohorts of Australian men and women born between 1956 and 1973

Model 1Model 2
MenWomenGender differenceMenWomenGender difference
Socio-economic status
Educational attainment:Year 11 or below (ref.)
Year 120.089** (0.029)0.203*** (0.031)**0.066* (0.029)0.166*** (0.029)*
Tertiary0.226*** (0.035)0.473*** (0.036)***0.189*** (0.036)0.394*** (0.036)***
Occupational prestige:Unemployed/Low (ref.)
Medium0.109*** (0.027)0.081* (0.031)0.096*** (0.027)0.057 (0.029)
High0.091** (0.029)0.095* (0.037)0.077* (0.028)0.076* (0.035)
Time spent out of work:Never out of work (ref.)
Out of work0.032 (0.023)−0.205*** (0.041)***0.041* (0.022)−0.189*** (0.039)***
Relationship histories
Marital status:Ever married (ref.)
Never marriedNever married0.602*** (0.034)0.487*** (0.044)*0.605*** (0.034)0.514*** (0.043)
No. of unions00.961*** (0.132)0.866*** (0.115) 0.936*** (0.132)0.781*** (0.111)
1 (ref.)
20.075* (0.026)0.067** (0.029)0.099*** (0.026)0.120*** (0.029)
3+0.046 (0.027)0.068* (0.030)0.095** (0.028)0.150*** (0.031)
Demographic characteristics
Country of birth:Australia (ref.)
Main English-speaking country0.081** (0.033)0.033 (0.039)
Other0.013 (0.034)−0.073* (0.035)
Aboriginal status:Not Aboriginal (ref.)
Aboriginal or Torres Islander−0.162 (0.095)−0.516*** (0.078)**
Birth cohorts:1956–61 (ref.)
1962–67−0.035 (0.026)−0.008 (0.028)-
1967–73−0.048 (0.026)0.013 (0.029)-
Background
Age left home:Before 21 (ref.)
Age 21 or older0.145*** (0.023)0.265*** (0.026)***
Still at home0.200 (0.232)0.726** (0.244)
Mother’s occupational prestige:Low/Never worked (ref.)
Medium0.042 (0.024)0.065* (0.026)
High0.016 (0.030)0.096** (0.032)
No. of siblings:Only child (ref.)
1 or more siblings1 or more siblings−0.080 (0.058)0.010 (0.067)
Remoteness area:Urban (ref.)
RuralRural−0.073** (0.023)−0.146*** (0.024)
Constant2.519*** (0.035)2.406*** (0.053)2.561*** (0.071)2.327*** (0.089)
Observations2,0662,3782,0662,378
AIC2,9674,3502,9134,143
BIC3,0294,4133,0374,270

Note: Standard errors in parentheses. * p < .05, ** p < .01, *** p < .001.

Source: Author’s calculations using data from the HILDA survey, waves 1–18, release 18.

Occupational prestige is also associated with later entry into motherhood: being employed in a high-status occupation prolongs the entry into motherhood of 10%, or 1.1 years, compared to being employed in a low-status occupation or to being unemployed. Similar to women, occupational prestige prolongs the time to parenthood for men, although the relationship is not linear. Being employed in medium- or high-status occupations is associated with a delay of 11% and 9%, or 1.4 and 1.2 years, respectively. Women with continuous employment are more likely to delay childbearing compared to those taking some time out of work, which was estimated to reduce the time to parenthood of 18%, or 2 years. The opposite effect is observed for men, who are associated with a delay of 4% or half a year if they have spent time out of work.

Being single, as opposed to being married, shows the strongest positive impact on the hazard of having a first child for both, with the effect being significantly stronger for men than for women. Having been in one or more unions reduces the hazard of entry into parenthood compared to having never entered a union, although the relationship is not monotonic. Having been in only one union is associated with the earliest entry into parenthood, while multiple co-residential relationships have a delaying effect on first childbirth.

When all the control variables are added (Model 2), the association between educational attainment and timing of first birth weakens especially among men, with Year 12 qualification showing the biggest proportional change. For women, a strong relationship between educational attainment and timing of first birth persists, especially at the tertiary level. High occupational prestige remains significantly associated with later entry into parenthood, although the coefficients decrease compared to Model 1, suggesting that part of the association was due to background and context variables. Marital and union histories remain strongly associated with the estimated hazard of having a child.

In summary, partial support was found for hypothesis H1. Although highly educated men and women are both more likely to postpone parenthood, the effect of educational attainment on childbearing delay is not the same. Among women, education leads to a significantly longer delay of first childbirth, which was estimated to be more than twice that of men. Consistent with hypothesis H2, the delay in childbearing is also more common among women employed in high-status occupations and those that have never taken time out from work. Occupational status also has a slightly delaying effect for men, while having had an uninterrupted career trajectory reduces the time to fatherhood, which is not fully consistent with the hypothesis H2. Evidence in support of hypothesis H3 found that partnership histories are strongly associated with the time of first childbirth and that they have a similar effect for men and women. Married respondents were the most likely to become parents at a younger age, as well as those who entered only one co-residential union. By contrast, multiple unions were found to prolong the time to first childbirth.

Regarding the control variables, it was found that, in comparison to the baseline category, women from non-English-speaking countries were more likely to have their first child earlier, while men born overseas in English-speaking countries were significantly associated with a later entry into fatherhood. Being Aboriginal or Torres Strait Islander was associated with having an earlier first birth among women only. No significant difference was observed in the outcome variable based on year of birth. Leaving the parental home after age 21 compared to moving out at a younger age was associated with a significantly lower hazard of having a child, particularly so among women. The mother’s occupational prestige was positively associated to later entry into motherhood, but no significant effect was found for men. The number of siblings did not show a significant association with time to first childbirth. Coherently with previous Australian research (Gray and Evans, 2017), it was found that women living in a remote or very remote area were more likely to have a first birth compared to those living in a urban area. This study confirms that this is also the case among men, for whom a strong negative relationship between living in a rural area and having a first birth was found.

An examination of the differences in time of entry into parenthood across cohorts revealed that the increase in mean age at first birth has been growing at a faster pace among better-educated women than among better-educated men, and that, overall, there has been an increase in the gap between lower- and better-educated women regarding the age of entry into motherhood (see Appendix A for further details).

To examine potential marital status-dependent effects, a different model was fitted testing interactions between marital status and each educational category. Model 3 shows estimates of a model identical to the full model (Model 2) except that it also includes the interaction terms (Table 3). The results reveal that the effect of education on the timing of first childbirth depends on the marital status. The postponement effect of higher educational attainment is maximum when the respondent is not married and highly educated. Conversely, being married is a strong predictor of entry into parenthood, despite educational attainment. These relationships are summarised in Figures 3a and 3b. Respondents with higher qualifications delay first childbirth longer than those with lower education. At the same time, marital status is a fundamental factor in determining the transition to parenthood. For each educational category, having never been married decreases the chance of having a birth dramatically and especially for men.

Table 3:

Maximum likelihood estimates from the log-logistic model of time to first childbirth with interactions effects, cohorts of Australian men and women born between 1956 and 1973

Model 3
MenWomen
Socio-economic status
Educational attainment: Year 11 or below (ref.)
 Year 120.031 (0.031)0.148*** (0.030)
 Tertiary0.159*** (0.038)0.343*** (0.037)
Occupational prestige: Unemployed/Low (ref.)
 Medium0.093*** (0.027)0.053 (0.029)
 High0.075** (0.028)0.073 (0.035)
Time spent out of work: Never out of work (ref.)
 Out of work0.041* (0.023)−0.186*** (0.040)
Relationship histories
Marital status: Ever married (ref.)
 Never married0.456*** (0.064)0.189* (0.089)
No. of unions: 0 0.960*** (0.134)0.791*** (0.116)
 1 (ref.)
 20.094*** (0.026)0.121*** (0.029)
 3+0.089** (0.028)0.150*** (0.031)
Demographic characteristics
Country of birth: Australia (ref.)
 Main English-speaking country0.082** (0.033)0.037 (0.039)
 Other−0.011 (0.034)−0.070* (0.035)
Aboriginal status: Not Aboriginal (ref.)
 Aboriginal or Torres Islander−0.157 (0.094)−0.472*** (0.078)
Birth cohorts: 1956–61 (ref.)
 1962–67−0.032 (0.026)−0.004 (0.028)
 1967–73−0.046 (0.026)0.019 (0.029)
Background
Age left home: Before 21 (ref.)
 Age 21 or older0.144*** (0.023)0.270*** (0.026)
 Still at home0.206 (0.230)0.806*** (0.238)
Mother’s occupational prestige: Never worked/Low (ref.)
 Medium0.043 (0.024)0.067* (0.026)
 High0.014 (0.030)0.099** (0.032)
No. of siblings: Only child (ref.)
 1 or more siblings−0.085 (0.058)0.014 (0.068)
Remoteness area: Urban (ref.)
 Rural−0.072* (0.023)−0.149*** (0.024)
Interactions
Not married × Year 11 or below (ref.)
 Not married × Year 120.211** (0.077)0.262** (0.106)
 Not Married × Tertiary0.182 (0.099)0.590*** (0.113)
Constant2.597*** (0.072)2.340*** (0.089)
Observations2,0662,378
AIC2,9094,117
BIC3,0454,256

Note: Standard errors in parentheses.* p<0.05, ** p<0.01, *** p<0.001.

Source: Author’s calculations using data from the HILDA survey, waves 1–18, release 18.

In the graph, the horizontal axis is scaled from 15 to 45 in increments of 5 units and the vertical axis is scaled from 0.00 to 0.25 in increments of 0.05 unit. The graph shows the following data. In the graph, the horizontal axis is scaled from 15 to 45 in increments of 5 units and the vertical axis is scaled from 0.00 to 0.25 in increments of 0.05 unit. The graph shows the following data. Year 11, married: 15, 0.00; 20, 0.10; 25, 0.15; 30, 0.14; 35, 0.12; 40, 0.10; 45, 0.08. Year 11, never married 15, 0.00; 20, 0.001; 25, 0.04; 30, 0.06; 35, 0.07; 40, 0.065; 45, 0.06. Year 12, married 15, 0.00; 20, 0.05; 25, 0.11; 30, 0.12; 35, 0.12; 40, 0.095; 45, 0.08. Year 12, never married 15, 0.00; 20, 0.0007; 25, 0.03; 30, 0.04; 35, 0.045; 40, 0.05; 45, 0.055. Tertiary, married 15, 0.3; 20, 0.03; 25, 0.05; 30, 0.08; 35, 0.08; 40, 0.075; 45, 0.07. Tertiary, never married 15, 0.00; 20, 0.0005; 25, 0.02; 30, 0.03; 35, 0.035; 40, 0.04; 45, 0.045. All values are estimated.
Figure 3a:

Estimated hazard of first birth by educational attainment and marital status, cohorts of Australian women born between 1956 and 1973

Citation: Longitudinal and Life Course Studies 13, 2; 10.1332/175795921X16197735939121

In the graph, the horizontal axis is scaled from 15 to 45 in increments of 5 units and the vertical axis is scaled from 0.00 to 0.25 in increments of 0.05 unit. The graph shows the following data. Year 11, married: 15, 0.00; 20, 0.035; 25, 0.10; 30, 0.14; 35, 0.135; 40, 0.12; 45, 0.11. Year 11, never married 15, 0.00; 20, 0.00; 25, 0.0005; 30, 0.02; 35, 0.04; 40, 0.05; 45, 0.55. Year 12, married 15, 0.00; 20, 0.03; 25, 0.8; 30, 0.12; 35, 0.13; 40, 0.11; 45, 0.10. Year 12, never married 15, 0.00; 20, 0.00; 25, 0.0002; 30, 0.015; 35, 0.035; 40, 0.045; 45, 0.05. Tertiary, married 15, 0.3; 20, 0.025; 25, 0.04; 30, 0.08; 35, 0.10; 40, 0.095; 45, 0.090. Tertiary, never married 15, 0.00; 20, 0.00; 25, 0.0001; 30, 0.01; 35, 0.02; 40, 0.03; 45, 0.045. All values are estimated.
Figure 3b:

Estimated hazard of first birth by educational attainment and marital status, cohorts of Australian men born between 1956 and 1973

Citation: Longitudinal and Life Course Studies 13, 2; 10.1332/175795921X16197735939121

Source: Author’s calculations using data from the HILDA survey, waves 1–18, release 18.

Discussion and conclusion

Previous research has provided evidence of the influence of educational, employment and relationship life course experiences on the transition to parenthood, especially among women. This paper has attempted to make progress in this direction by adopting a life course perspective and by quantifying how these factors come together to influence timing at first childbirth and the probability of remaining permanently childless. It was hypothesised that the pathways into later childbearing are potentially very different between men and women, due to their gender-asymmetric roles across the life course (West and Zimmerman, 1987). Hence, time to first childbirth was separately modelled for men and women, so that gendered pathways into childbearing delay could be examined.

It was found that not all socio-economic groups have delayed childbearing to the same extent: better-educated segments of the population, employed in high-status occupations as managers, administrators and professionals, have played an essential role in this process. A monotonic relationship between education and time of first childbirth was observed for both genders, although tertiary-educated women were more than twice as likely to delay childbearing compared to their male counterparts. These results are consistent with some of the conclusions reached by other investigators about the relationship between education and childbearing timing (Kneale and Joshi, 2008; Neels and De Wachter, 2010; Nisén et al, 2014; Rybińska, 2014; Berrington et al, 2015). In accordance with other studies (Liefbroer and Corijn, 1999; Andersson, 2000; Keizer et al, 2008), the results also revealed a positive association between economic inactivity and entry into motherhood, while the opposite relationship was found for men. Not surprisingly and consistently with previous findings (Heaton et al, 1999), having been married was associated with higher hazards of first childbirth. This relationship was particularly pronounced for men, which might reflect a data-quality issue. Indeed, it has been found that men tend to report the occurrence and dates of births with more errors compared to women, especially for births that happened outside of wedlock (Rendall et al, 1999). Interestingly, marriage and having been in only one co-residential union were strongly associated with a pattern of earlier entry into parenthood. This result supports the idea that a history of multiple partnerships may lead to childbearing delay (Mills et al, 2011), as it indicates an increase in union instability and in the time spent looking for a suitable partner to form a family with. It may also indicate that people who partner early are selective of those wanting to have children at a young age.

The cross-sectional analysis suggests that clear gender differences exist in the relationship between childlessness and childbearing delay. It is apparent that men and women who had similar life experiences have disparate chances of delaying childbearing and of becoming parents. For instance, among women, the probability of being childless was lowest among women who were low educated and in low-status occupations. These were also the categories of women more likely to have children at a younger age. By contrast, among men, childbearing delay and childlessness stemmed from different factors. Those with better education and higher-status occupations were the most likely to delay childbearing but at the same time they were also associated with a lower probability of remaining childless compared to those with low educational attainment and low occupational status. The only exception to these gender-specific trends was marital status, which was negatively associated with childbearing delay and childlessness for both genders. The strong association between childbearing delay and childlessness among women but not among men is consistent with the finding that increasing childbearing age represents a risk for the successful realisation of the fertility plans only among women (Beaujouan et al, 2019), who are subject to a more rapid decline in fertility with age.

The rising age at first birth, observed especially among better-educated women, may indicate the reinforcement over time of a social structure that supports staying childless for longer. Since the vast majority of women intend to have children (Holton et al, 2011), it is likely that an increasing number of them will remain involuntarily childless. Hence, a better understanding of the factors associated with childbearing delay is key to understanding ultimate levels of childlessness and to informing effective policies about how fertility timing can be shifted to lower ages. This research concludes that education, career and relationship histories do have an impact on the timing of first childbirth, but that their effect tends to be gender-specific and to be related in different ways to childlessness among men and women.

Notes

1

The Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were used as selection criteria for grouping variables.

2

This result is obtained from the exponentiated coefficients, or the so-called time ratios. Time ratios can be interpreted as the factor by which the expected time-to-failure, in this case first birth, is multiplied as a result of a one-unit increase in the corresponding covariate (Cleves et al, 2010).

Acknowledgements

I would like to offer my special thanks to Bernard Baffour for help with the methods, Edith Gray for providing valuable suggestions and two anonymous reviewers for their helpful comments.

Conflict of interest

The author declares that there is no conflict of interest.

References

  • ABS (Australian Bureau of Statistics) (2001) Australian Social Trends, 2001. Catalogue no. 4102.0, Canberra: ABS.

  • ABS (Australian Bureau of Statistics) (2017) Births, Australia, 2016. Catalogue no. 3301.0, Canberra: ABS.

  • ABS (Australian Bureau of Statistics) (2019) Births, Australia, 2018. Catalogue no. 3301.0, Canberra: ABS.

  • Adamson, G.D., de Mouzon, J., Chambers, G.M., Zegers-Hochschild, F., Mansour, R., Ishihara, O., Banker, M. and Dyer, S. (2018) International committee for monitoring assisted reproductive technology: world report on assisted reproductive technology, 2011, Fertility and Sterility, 110(6): 106780. doi: 10.1016/j.fertnstert.2018.06.039

    • Search Google Scholar
    • Export Citation
  • Allison, P.D. (1982) Discrete-time methods for the analysis of event histories, Sociological Methodology, 13: 6198.  doi: 10.2307/270718

    • Search Google Scholar
    • Export Citation
  • Andersson, G. (2000) The impact of labour-force participation on childbearing behaviour: pro-cyclical fertility in Sweden during the 1980s and the 1990s, European Journal of Population, 16(4): 293333. doi: 10.1023/A:1006454909642

    • Search Google Scholar
    • Export Citation
  • Baxter, J. (2002) Patterns of change and stability in the gender division of household labour in Australia, 1986–1997, Journal of Sociology, 38(4): 399424. doi: 10.1177/144078302128756750

    • Search Google Scholar
    • Export Citation
  • Baxter, J. (2016) The Modern Australian Family, Melbourne: Australian Institute of Family Studies.

  • Baxter, J., Hewitt, B. and Haynes, M. (2008) Life course transitions and housework: marriage, parenthood, and time on housework, Journal of Marriage and Family, 70(2): 25972. doi: 10.1111/j.1741-3737.2008.00479.x

    • Search Google Scholar
    • Export Citation
  • Beaujouan, É., Reimondos, A., Gray, E., Evans, A. and Sobotka, T. (2019) Declining realisation of reproductive intentions with age, Human Reproduction, 34(10): 190614. doi: 10.1093/humrep/dez150

    • Search Google Scholar
    • Export Citation
  • Becker, G.S. (1965) A theory of the allocation of time, The Economic Journal, 75(299): 493517. doi: 10.2307/2228949

  • Becker, G.S. (1981) A Treatise on the Family, Cambridge, MA: Harvard University Press.

  • Bernhardt, E.M. (1993) Fertility and employment, European Sociological Review, 9(1): 2542. doi: 10.1093/oxfordjournals.esr.a036659

  • Berrington, A., Stone, J. and Beaujouan, E. (2015) Educational differences in timing and quantum of childbearing in Britain: a study of cohorts born 1940–1969, Demographic Research, 33(art 26): 73364. doi: 10.4054/DemRes.2015.33.26

    • Search Google Scholar
    • Export Citation
  • Billari, F.C. (2001) A log-logistic regression model for a transition rate with a starting threshold, Population Studies, 55(1): 1524. doi: 10.1080/00324720127680

    • Search Google Scholar
    • Export Citation
  • Billari, F.C., Goisis, A., Liefbroer, A.C., Settersten, R.A., Aassve, A., Hagestad, G. and Spéder, Z. (2010) Social age deadlines for the childbearing of women and men, Human Reproduction, 26(3): 616622. doi: 10.1093/humrep/deq360

    • Search Google Scholar
    • Export Citation
  • Blossfeld, H.P. and Huinink, J. (1991) Human capital investments or norms of role transition? How women’s schooling and career affect the process of family formation, American Journal of Sociology, 97(1): 14368. doi: 10.1086/229743

    • Search Google Scholar
    • Export Citation
  • Bodin, M., Käll, L., Tydén, T., Stern, J., Drevin, J. and Larsson, M. (2017) Exploring men’s pregnancy-planning behaviour and fertility knowledge: a survey among fathers in Sweden, Upsala Journal of Medical Sciences, 122(2): 12735. doi: 10.1080/03009734.2017.1316531

    • Search Google Scholar
    • Export Citation
  • Carmichael, G.A. (2013) Estimating paternity in Australia 1976–2010, Fathering, 11(3): 25679. doi: 10.3149/fth.1103.256

  • Carmichael, G.A. and Whittaker, A. (2007) Choice and circumstance: qualitative insights into contemporary childlessness in Australia, European Journal of Population, 23(2): 11143. doi: 10.1007/s10680-006-9112-4

    • Search Google Scholar
    • Export Citation
  • Chen, X.K., Wen, S.W., Krewski, D., Fleming, N., Yang, Q. and Walker, M.C. (2008) Paternal age and adverse birth outcomes: teenager or 40+, who is at risk?, Human Reproduction, 23(6): 129096. doi: 10.1093/humrep/dem403

    • Search Google Scholar
    • Export Citation
  • Chesters, J., Baxter, J. and Western, M. (2009) Paid and unpaid work in Australian households: trends in the gender division of labour, 1986–2005, Australian Journal of Labour Economics, 12(1): 89108.

    • Search Google Scholar
    • Export Citation
  • Cleves, M., Gutierrez, R., Gould, W. and Marchenko, Y. (2010) An Introduction to Survival Analysis Using STATA, 3rd edn, College Station, TX: STATA Press.

    • Search Google Scholar
    • Export Citation
  • Cooke, A., Mills, T.A. and Lavender, T. (2012) Advanced maternal age: delayed childbearing is rarely a conscious choice: a qualitative study of women’s views and experiences, International Journal of Nursing Studies, 49(1): 309. doi: 10.1016/j.ijnurstu.2011.07.013

    • Search Google Scholar
    • Export Citation
  • Craig, L. (2005) The money or the care: a comparison of couple and sole parent households’ time allocation to work and children, Australian Journal of Social Issues, 40(4): 52140.

    • Search Google Scholar
    • Export Citation
  • Duvander, A.Z., Fahlén, S., Brandén, M. and Ohlsson-Wijk, S. (2020) Who makes the decision to have children? Couples’ childbearing intentions and actual childbearing, Advances in Life Course Research, 43: art 100286, doi: 10.1016/j.alcr.2019.04.016. 

    • Search Google Scholar
    • Export Citation
  • Eijkermans, M.J.C., van Poppel, F.W.A., Habbema, J.D.F., Smith, K.R., Leridon, H. and te Velde, E.R. (2014) Too old to have children? Lessons from natural fertility populations, Human Reproduction, 29(6): 130412. doi: 10.1093/humrep/deu056

    • Search Google Scholar
    • Export Citation
  • Elder, G.H. Jr (1994) Time, human agency, and social change: perspectives on the life course, Social Psychology Quarterly, 57(1): 415. doi: 10.2307/2786971

    • Search Google Scholar
    • Export Citation
  • Eriksson, C., Larsson, M., Skoog Svanberg, A. and Tydén, T. (2013) Reflections on fertility and postponed parenthood – interviews with highly educated women and men without children in Sweden, Upsala Journal of Medical Sciences, 118(2): 1229. doi: 10.3109/03009734.2012.762074

    • Search Google Scholar
    • Export Citation
  • Esping-Andersen, G. and Billari, F. (2015) Re-theorizing family demographics, Population and Development Review, 41(1): 131. doi: 10.1111/j.1728-4457.2015.00024.x

    • Search Google Scholar
    • Export Citation
  • Evans, A. (2013) Generational change in leaving the parental home, in A. Evans and J. Baxter (eds) Negotiating the Life Course: Stability and Change in Life Pathways, Dordrecht: Springer, pp 5468.

    • Search Google Scholar
    • Export Citation
  • Frejka, T. and Sardon, J.P. (2006) First birth trends in developed countries: persisting parenthood postponement, Demographic Research, 15(art 6): 14780. doi: 10.4054/DemRes.2006.15.6

    • Search Google Scholar
    • Export Citation
  • Goldscheider, F. and DaVanzo, J. (1989) Pathways to independent living in early adulthood: marriage, semiautonomy, and premarital residential independence, Demography, 26(4): 597614. doi: 10.2307/2061260

    • Search Google Scholar
    • Export Citation
  • Goldscheider, F., Bernhardt, E. and Lappegård, T. (2015) The gender revolution: a framework for understanding changing family and demographic behavior, Population and Development Review, 41(2): 20739. doi: 10.1111/j.1728-4457.2015.00045.x

    • Search Google Scholar
    • Export Citation
  • Graham, M., Hill, E., Shelly, J. and Taket, A. (2013) Why are childless women childless? Findings from an exploratory study of childless women in Victoria, Australia, Journal of Social Inclusion, 4(1): 7089. doi: 10.36251/josi.63

    • Search Google Scholar
    • Export Citation
  • Gray, E. (2002) What do we know about men’s fertility levels in Australia?, People and Place, 10(4): 110.

  • Gray, E. and Evans, A. (2017) Geographic variation in parity progression in Australia, Population, Space and Place, 24(2): art e2080, https://doi.org/10.1002/psp.2080.

    • Search Google Scholar
    • Export Citation
  • Gray, E., Evans, A. and Reimondos, A. (2013) Childbearing desires of childless men and women: when are goals adjusted?, Advances in Life Course Research, 18(2): 1419. doi: 10.1016/j.alcr.2012.09.003

    • Search Google Scholar
    • Export Citation
  • Hagestad, G.O. and Call, V.R.A. (2007) Pathways to childlessness. a life course perspective, Journal of Family Issues, 28(10): 133861. doi: 10.1177/0192513X07303836

    • Search Google Scholar
    • Export Citation
  • Heaton, T.B., Cardell, K.J. and Holland, K. (1999) Persistence and change in decisions to remain childless, Journal of Marriage and Family, 61(2): 5319. doi: 10.2307/353767

    • Search Google Scholar
    • Export Citation
  • Hoem, J.M. (1986) The impact of education on modern family-union initiation, European Journal of Population, 2(2): 11333. doi: 10.1007/BF01796886

    • Search Google Scholar
    • Export Citation
  • Holton, S., Fisher, J. and Rowe, H. (2011) To have or not to have? Australian women’s childbearing desires, expectations and outcomes, Journal of Population Research, 28(4): 35379. doi: 10.1007/s12546-011-9072-3

    • Search Google Scholar
    • Export Citation
  • Jalovaara, M. and Fasang, A. (2017) From never partnered to serial cohabiters: union trajectories to childlessness, Demographic Research, 36(art 55): 170320. doi: 10.4054/DemRes.2017.36.55

    • Search Google Scholar
    • Export Citation
  • Johnson, J.A. and Tough, S. (2012) Delayed child-bearing, Journal of Obstetrics and Gynaecology Canada, 34(1): 8093. doi: 10.1016/S1701-2163(16)35138-6

    • Search Google Scholar
    • Export Citation
  • Joshi, H. (2002) Production, reproduction, and education: women, children, and work in a British perspective, Population and Development Review, 28(3): 44574. doi: 10.1111/j.1728-4457.2002.00445.x

    • Search Google Scholar
    • Export Citation
  • Keizer, R., Dykstra, P.A. and Jansen, M.D. (2008) Pathways into childlessness: evidence of gendered life course dynamics, Journal of Biosocial Science, 40(6): 86378. doi: 10.1017/S0021932007002660

    • Search Google Scholar
    • Export Citation
  • Kippen, R. (2006) The rise of the older mother, People and Place, 14(3): 111.

  • Kneale, D. and Joshi, H. (2008) Postponement and childlessness: evidence from two British cohorts, Demographic Research, 19(58): 193568 , doi: 10.4054/DemRes.2008.19.58

    • Search Google Scholar
    • Export Citation
  • Kocourkova, J., Burcin, B. and Kucera, T. (2014) Demographic relevancy of increased use of assisted reproductive technology in European countries, Reproductive Health, 11(37), doi: 10.1186/1742-4755-11-37

    • Search Google Scholar
    • Export Citation
  • Kohler, H.P., Billari, F.C. and Ortega, J.A. (2002) The emergence of lowest-low fertility in Europe during the 1990s, Population and Development Review, 28(4): 64180. doi: 10.1111/j.1728-4457.2002.00641.x

    • Search Google Scholar
    • Export Citation
  • Kravdal, Ø. (1994) The importance of economic activity, economic potential and economic resources for the timing of first births in Norway, Population Studies, 48(2): 24967. doi: 10.1080/0032472031000147786

    • Search Google Scholar
    • Export Citation
  • Lazzari, E. (2019) Socio-economic changes in the age-patterns of childbearing in Australia, Australian Population Studies, 3(2): 346. doi: 10.37970/aps.v3i2.52

    • Search Google Scholar
    • Export Citation
  • Lazzari, E. (forthcoming) Changing trends between education, childlessness and completed fertility: a cohort analysis of Australian women born in 1952–1971, Journal of Population Research. 

    • Search Google Scholar
    • Export Citation
  • Leridon, H. (2004) Can assisted reproductive technology compensate for the natural decline in fertility with age? A model assessment, Human Reproduction, 7(19): 154853. doi: 10.1093/humrep/deh304

    • Search Google Scholar
    • Export Citation
  • Leridon, H. (2017) Biological effects of first birth postponement and assisted reproductive technology on complete fertility, Population, 72(3): 44572. doi: 10.3917/popu.1703.0463

    • Search Google Scholar
    • Export Citation
  • Lesthaeghe, R. and Moors, G. (2000) Recent trends in fertility and household formation in the industrialized world, Review of Population and Social Policy, 9(1): 12170.

    • Search Google Scholar
    • Export Citation
  • Liefbroer, A. and Corijn, M. (1999) Who, what, where, and when? Specifying the impact of educational attainment and labour force participation on family formation, European Journal of Population, 15(1): 4575. doi: 10.1023/A:1006137104191

    • Search Google Scholar
    • Export Citation
  • Lutz, W. and Skirbekk, V. (2005) Policies addressing the tempo effect in low-fertility countries, Population and Development Review, 31(4): 699720.  doi: 10.1111/j.1728-4457.2005.00094.x

    • Search Google Scholar
    • Export Citation
  • Martin, S.P. (2000) Diverging fertility among U.S. women who delay childbearing past age 30, Demography, 37(4): 52333. doi: 10.1353/dem.2000.0007

    • Search Google Scholar
    • Export Citation
  • McDonald, P. (2000) Gender equity, social institutions and the future of fertility, Journal of Population Research, 17(1): 116. doi: 10.1007/BF03029445

    • Search Google Scholar
    • Export Citation
  • McDonald, P. (2013) Societal foundation for explaining low fertility: gender equity, Demographic Research, 28(art 34): 98194. doi: 10.4054/DemRes.2013.28.34

    • Search Google Scholar
    • Export Citation
  • McDonald, P. and Reimondos, A. (2013) Relationship pathways and first birth in Australia, in A. Evans and J. Baxter (eds) Negotiating the Life Course: Stability and Change in Life Pathways, Dordrecht: Springer, pp 6998.

    • Search Google Scholar
    • Export Citation
  • McDonald, P. (2020) A Projection of Australia’s Future Fertility Rates, Centre for Population Research Paper, Canberra: The Australian Government.

  • Mikolai, J. (2017) Partnership histories and the transition to motherhood in later reproductive ages in Europe, Population, 72(1): 12354. doi: 10.3917/popu.1701.0127

    • Search Google Scholar
    • Export Citation
  • Mills, M., Rindfuss, R.R., McDonald, P. and te Velde, E. (2011) Why do people postpone parenthood? Reasons and social policy incentives, Human Reproduction Update, 17(6): 84860. doi: 10.1093/humupd/dmr026

    • Search Google Scholar
    • Export Citation
  • Miranti, R., McNamara, J., Tanton, R. and Yap, M. (2009) A narrowing gap? Trends in childlessness of professional women in Australia 1986–2006, Journal of Population Research, 26(4): 35979. doi: 10.1007/s12546-009-9022-5

    • Search Google Scholar
    • Export Citation
  • Mynarska, M., Matysiak, A., Rybińska, A., Tocchioni, V. and Vignoli, D. (2015) Diverse paths into childlessness over the life course, Advances in Life Course Research, 25: 3548.  doi: 10.1016/j.alcr.2015.05.003

    • Search Google Scholar
    • Export Citation
  • Neels, K. and De Wachter, D. (2010) Postponement and recuperation of Belgian fertility: how are they related to rising female educational attainment?, Vienna Yearbook of Population Research, 8(1): 77106.  doi: 10.1553/populationyearbook2010s77

    • Search Google Scholar
    • Export Citation
  • Ní Bhrolcháin, M. and Beaujouan, É. (2012) Fertility postponement is largely due to rising educational enrolment, Population Studies, 66(3): 31127.

    • Search Google Scholar
    • Export Citation
  • Nisén, J., Martikainen, P., Silventoinen, K. and Myrskylä, M. (2014) Age-specific fertility by educational level in the Finnish male cohort born 1940–1950, Demographic Research, 31(art 5): 11936.

    • Search Google Scholar
    • Export Citation
  • Oppenheimer, V.K. (1994) Women’s rising employment and the future of family in industrial societies, Population and Development Review, 20(2): 293342. doi: 10.2307/2137521

    • Search Google Scholar
    • Export Citation
  • Parr, N. (2005) Family background, schooling and childlessness in Australia, Journal of Biosocial Science, 37(2): 22943. doi: 10.1017/S0021932004006546

    • Search Google Scholar
    • Export Citation
  • Parr, N. (2010) Childlessness among men in Australia, Population Research and Policy Review, 29(3): 31938. doi: 10.1007/s11113-009-9142-9

    • Search Google Scholar
    • Export Citation
  • Perelli-Harris, B., Mynarska, M., Berrington, A., Berghammer, C., Evans, A., Isupova, O., Keizer, R., Klärner, A., Lappegård, T. and Vignoli, D. (2014) Towards a deeper understanding of cohabitation: insights from focus group research across Europe and Australia, Demographic Research, 31(art 34): 104378. doi: 10.4054/DemRes.2014.31.34

    • Search Google Scholar
    • Export Citation
  • Peterson, B.D., Pirritano, M., Tucker, L. and Lampic, C. (2012) Fertility awareness and parenting attitudes among American male and female undergraduate university students, Human Reproduction, 27(5): 1375382. doi: 10.1093/humrep/des011

    • Search Google Scholar
    • Export Citation
  • Powell, J.L. (1986) Estimation of semiparametric models, in R.F. Engle and D.L. McFadden (eds) Handbook of Econometrics Volume 4, Amsterdam: Elsevier, pp 2443521.

    • Search Google Scholar
    • Export Citation
  • Raab, M. and Struffolino, E. (2019) The heterogeneity of partnership trajectories to childlessness in Germany, European Journal of Population, 36(1): 5370. doi: 10.1007/s10680-019-09519-y

    • Search Google Scholar
    • Export Citation
  • Rendall, M.S., Clarke, L., Peters, H.E., Ranjit, N. and Verropoulou, G. (1999) Incomplete reporting of men's fertility in the United States and Britain: a research note, Demography, 36(1): 13544. doi: 10.2307/2648139

    • Search Google Scholar
    • Export Citation
  • Rowland, D.T. (2007) Historical trends in childlessness, Journal of Family Issues, 28(10): 131137. doi: 10.1177/0192513X07303823

  • Rybińska, A. (2014) Motherhood after the age of 35 in Poland, Studia Demograficzne, 1(165): 728.

  • Saarela, J. and Skirbekk, V. (2020) Childlessness and union histories: evidence from Finnish population register data, Journal of Biosocial Science, 52(1): 7896. doi: 10.1017/S0021932019000257

    • Search Google Scholar
    • Export Citation
  • Schmidt, L., Sobotka, T., Bentzen, J.B., Nyboe Andersen, A. and ESHRE Reproduction and Society Task Force (2012) Demographic and medical consequences of the postponement of parenthood, Human Reproduction Update, 18(1): 2943. doi: 10.1093/humupd/dmr040

    • Search Google Scholar
    • Export Citation
  • Settersten, R.A. and Hagestad, G. (1996) What’s the latest? Cultural age deadlines for family transitions, Gerontologist, 36: 178188. doi: 10.1093/geront/36.2.178

    • Search Google Scholar
    • Export Citation
  • Sobotka, T. (2017) Post-transitional fertility: the role of childbearing postponement in fuelling the shift to low and unstable fertility levels, Journal of Biosocial Science, 49(S1): S2045. doi: 10.1017/S0021932017000323

    • Search Google Scholar
    • Export Citation
  • Summerfield, M., Bright, S., Hahn, M., La, N., Macalalad, N., Watson, N., Wilkins, R. and Wooden, M. (2019) HILDA User Manual – Release 18, Melbourne: University of Melbourne, Melbourne Institute of Applied Economic and Social Research.

    • Search Google Scholar
    • Export Citation
  • Tavares, L.P. (2016) Who delays childbearing? The association between time to first birth, personality traits and education, European Journal of Population, 32(4): 57597. doi: 10.1007/s10680-016-9393-1

    • Search Google Scholar
    • Export Citation
  • Testa, M.R. (2007) Childbearing preferences and family issues in Europe: evidence from the Eurobarometer 2006 survey, Vienna Yearbook of Population Research, 5(1): 35779. doi: 10.1553/populationyearbook2007s357

    • Search Google Scholar
    • Export Citation
  • Watson, N. (2012) Longitudinal and Cross-sectional weighting methodology for the HILDA survey, HILDA project technical paper series No. 2/12, Melbourne: University of Melbourne, Melbourne Institute of Applied Economic and Social Research.

    • Search Google Scholar
    • Export Citation
  • Watson, N. and Wooden, M. (2010) The HILDA survey: progress and future developments, Australian Economic Review, 43(3): 32636. doi: 10.1111/j.1467-8462.2010.00604.x

    • Search Google Scholar
    • Export Citation
  • Watson, N. and Wooden, M. (2012) The HILDA survey: a case study in the design and development of a successful household panel study, Longitudinal and Life Course Studies, 3(3): 36981.

    • Search Google Scholar
    • Export Citation
  • Watson, N. and Wooden, M. (2013) Adding a top-up sample to the HILDA survey, Australian Economic Review, 46(4): 48998. doi: 10.1111/1467-8462.12027

    • Search Google Scholar
    • Export Citation
  • West, C. and Zimmerman, D.H. (1987) Doing gender, Gender and Society, 1(2): 12551. doi: 10.1177/0891243287001002002

Appendix A

Table A1 presents the mean age at first childbirth of fathers and mothers across different social groups. Men and women with higher qualifications have their first child later, with the gap between those with tertiary degrees and those with Year 11 or below qualifications being more pronounced for women than for men. Additionally, among women, the difference in age at first birth across educational groups has been increasing between the oldest and most recent cohort. For instance, in the 1956–61 birth cohort, the gap in mean age at childbearing between highest and lowest educated women was 4.5 years, while it increased to 6.5 years in the 1968–73 birth cohort. By contrast, the gap in age at first birth across educational groups for men remained almost unchanged (showing only a modest increase of 0.3 years). A similar pattern can be identified when looking at the occupational status of respondents, with men and women in high-prestige occupations showing later ages at first birth compared to those employed in low-prestige occupations or unemployed. Again, among women the gap in mean age at first childbirth across occupational categories tends to be wider than for men. Among the oldest cohort, having been married is clearly associated with younger ages at first birth for both men and women. However, as we move towards the most recent cohort, the gap in the age at childbearing between the ever married and the never married groups significantly declines.

Table A1

: Mean age at first childbirth of fathers and mothers by educational attainment, occupational prestige, marital status and year of birth, Australia, weighted average

1956–61*1962–67*1968–73*
Women Educational attainment:
Year 11 or below23.7 (0.33)25.5 (0.58)24.1 (0.62)
Year 1226.6 (0.42)25.9 (0.36)26.8 (0.50)
Tertiary28.2 (0.46)29.2 (0.47)30.6 (0.39)
Occupational prestige:
Unemployed/Low25.0 (0.48)25.6 (0.58)26.9 (0.61)
Medium24.5 (0.32)26.1 (0.38)26.6 (0.53)
High27.0 (0.48)28.7 (0.48)29.6 (0.55)
Marital status:
Ever married25.6 (0.24)26.5 (0.28)27.6 (0.35)
Never married28.0 (1.93)27.7 (1.59)27.5 (0.86)
Men Educational attainment:
Year 11 or below27.6 (0.55)27.9 (0.65)27.7 (0.89)
Year 1228.7 (0.38)28.3 (0.48)29.2 (0.38)
Tertiary30.7 (0.48)31.5 (0.65)31.1 (0.75)
Occupational prestige:
Unemployed/Low28.1 (0.43)27.7 (0.54)27.8 (0.52)
Medium29.8 (0.59)29.0 (0.52)31.7 (0.59)
High29.3 (0.44)30.9 (0.48)30.4 (0.37)
Marital status:
28.7 (0.28)28.8 (0.36)29.5 (0.34)
Never married31.6 (1.30)30.6 (1.13)31.3 (1.02)

Note: * Standard deviation in parenthesis.

Source: Author’s calculations using data from the HILDA survey, waves 1-18, release 18.

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    First-birth distribution by age and sex, unweighted

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    Boxplot of fathers and mothers age at first birth, Australian cohorts born 1956–1973

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    Estimated hazard of first birth by educational attainment and marital status, cohorts of Australian women born between 1956 and 1973

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    Estimated hazard of first birth by educational attainment and marital status, cohorts of Australian men born between 1956 and 1973

  • ABS (Australian Bureau of Statistics) (2001) Australian Social Trends, 2001. Catalogue no. 4102.0, Canberra: ABS.

  • ABS (Australian Bureau of Statistics) (2017) Births, Australia, 2016. Catalogue no. 3301.0, Canberra: ABS.

  • ABS (Australian Bureau of Statistics) (2019) Births, Australia, 2018. Catalogue no. 3301.0, Canberra: ABS.

  • Adamson, G.D., de Mouzon, J., Chambers, G.M., Zegers-Hochschild, F., Mansour, R., Ishihara, O., Banker, M. and Dyer, S. (2018) International committee for monitoring assisted reproductive technology: world report on assisted reproductive technology, 2011, Fertility and Sterility, 110(6): 106780. doi: 10.1016/j.fertnstert.2018.06.039

    • Search Google Scholar
    • Export Citation
  • Allison, P.D. (1982) Discrete-time methods for the analysis of event histories, Sociological Methodology, 13: 6198.  doi: 10.2307/270718

    • Search Google Scholar
    • Export Citation
  • Andersson, G. (2000) The impact of labour-force participation on childbearing behaviour: pro-cyclical fertility in Sweden during the 1980s and the 1990s, European Journal of Population, 16(4): 293333. doi: 10.1023/A:1006454909642

    • Search Google Scholar
    • Export Citation
  • Baxter, J. (2002) Patterns of change and stability in the gender division of household labour in Australia, 1986–1997, Journal of Sociology, 38(4): 399424. doi: 10.1177/144078302128756750

    • Search Google Scholar
    • Export Citation
  • Baxter, J. (2016) The Modern Australian Family, Melbourne: Australian Institute of Family Studies.

  • Baxter, J., Hewitt, B. and Haynes, M. (2008) Life course transitions and housework: marriage, parenthood, and time on housework, Journal of Marriage and Family, 70(2): 25972. doi: 10.1111/j.1741-3737.2008.00479.x

    • Search Google Scholar
    • Export Citation
  • Beaujouan, É., Reimondos, A., Gray, E., Evans, A. and Sobotka, T. (2019) Declining realisation of reproductive intentions with age, Human Reproduction, 34(10): 190614. doi: 10.1093/humrep/dez150

    • Search Google Scholar
    • Export Citation
  • Becker, G.S. (1965) A theory of the allocation of time, The Economic Journal, 75(299): 493517. doi: 10.2307/2228949

  • Becker, G.S. (1981) A Treatise on the Family, Cambridge, MA: Harvard University Press.

  • Bernhardt, E.M. (1993) Fertility and employment, European Sociological Review, 9(1): 2542. doi: 10.1093/oxfordjournals.esr.a036659

  • Berrington, A., Stone, J. and Beaujouan, E. (2015) Educational differences in timing and quantum of childbearing in Britain: a study of cohorts born 1940–1969, Demographic Research, 33(art 26): 73364. doi: 10.4054/DemRes.2015.33.26

    • Search Google Scholar
    • Export Citation
  • Billari, F.C. (2001) A log-logistic regression model for a transition rate with a starting threshold, Population Studies, 55(1): 1524. doi: 10.1080/00324720127680

    • Search Google Scholar
    • Export Citation
  • Billari, F.C., Goisis, A., Liefbroer, A.C., Settersten, R.A., Aassve, A., Hagestad, G. and Spéder, Z. (2010) Social age deadlines for the childbearing of women and men, Human Reproduction, 26(3): 616622. doi: 10.1093/humrep/deq360

    • Search Google Scholar
    • Export Citation
  • Blossfeld, H.P. and Huinink, J. (1991) Human capital investments or norms of role transition? How women’s schooling and career affect the process of family formation, American Journal of Sociology, 97(1): 14368. doi: 10.1086/229743

    • Search Google Scholar
    • Export Citation
  • Bodin, M., Käll, L., Tydén, T., Stern, J., Drevin, J. and Larsson, M. (2017) Exploring men’s pregnancy-planning behaviour and fertility knowledge: a survey among fathers in Sweden, Upsala Journal of Medical Sciences, 122(2): 12735. doi: 10.1080/03009734.2017.1316531

    • Search Google Scholar
    • Export Citation
  • Carmichael, G.A. (2013) Estimating paternity in Australia 1976–2010, Fathering, 11(3): 25679. doi: 10.3149/fth.1103.256

  • Carmichael, G.A. and Whittaker, A. (2007) Choice and circumstance: qualitative insights into contemporary childlessness in Australia, European Journal of Population, 23(2): 11143. doi: 10.1007/s10680-006-9112-4

    • Search Google Scholar
    • Export Citation
  • Chen, X.K., Wen, S.W., Krewski, D., Fleming, N., Yang, Q. and Walker, M.C. (2008) Paternal age and adverse birth outcomes: teenager or 40+, who is at risk?, Human Reproduction, 23(6): 129096. doi: 10.1093/humrep/dem403

    • Search Google Scholar
    • Export Citation
  • Chesters, J., Baxter, J. and Western, M. (2009) Paid and unpaid work in Australian households: trends in the gender division of labour, 1986–2005, Australian Journal of Labour Economics, 12(1): 89108.

    • Search Google Scholar
    • Export Citation
  • Cleves, M., Gutierrez, R., Gould, W. and Marchenko, Y. (2010) An Introduction to Survival Analysis Using STATA, 3rd edn, College Station, TX: STATA Press.

    • Search Google Scholar
    • Export Citation
  • Cooke, A., Mills, T.A. and Lavender, T. (2012) Advanced maternal age: delayed childbearing is rarely a conscious choice: a qualitative study of women’s views and experiences, International Journal of Nursing Studies, 49(1): 309. doi: 10.1016/j.ijnurstu.2011.07.013

    • Search Google Scholar
    • Export Citation
  • Craig, L. (2005) The money or the care: a comparison of couple and sole parent households’ time allocation to work and children, Australian Journal of Social Issues, 40(4): 52140.

    • Search Google Scholar
    • Export Citation
  • Duvander, A.Z., Fahlén, S., Brandén, M. and Ohlsson-Wijk, S. (2020) Who makes the decision to have children? Couples’ childbearing intentions and actual childbearing, Advances in Life Course Research, 43: art 100286, doi: 10.1016/j.alcr.2019.04.016. 

    • Search Google Scholar
    • Export Citation
  • Eijkermans, M.J.C., van Poppel, F.W.A., Habbema, J.D.F., Smith, K.R., Leridon, H. and te Velde, E.R. (2014) Too old to have children? Lessons from natural fertility populations, Human Reproduction, 29(6): 130412. doi: 10.1093/humrep/deu056

    • Search Google Scholar
    • Export Citation
  • Elder, G.H. Jr (1994) Time, human agency, and social change: perspectives on the life course, Social Psychology Quarterly, 57(1): 415. doi: 10.2307/2786971

    • Search Google Scholar
    • Export Citation
  • Eriksson, C., Larsson, M., Skoog Svanberg, A. and Tydén, T. (2013) Reflections on fertility and postponed parenthood – interviews with highly educated women and men without children in Sweden, Upsala Journal of Medical Sciences, 118(2): 1229. doi: 10.3109/03009734.2012.762074

    • Search Google Scholar
    • Export Citation
  • Esping-Andersen, G. and Billari, F. (2015) Re-theorizing family demographics, Population and Development Review, 41(1): 131. doi: 10.1111/j.1728-4457.2015.00024.x

    • Search Google Scholar
    • Export Citation
  • Evans, A. (2013) Generational change in leaving the parental home, in A. Evans and J. Baxter (eds) Negotiating the Life Course: Stability and Change in Life Pathways, Dordrecht: Springer, pp 5468.

    • Search Google Scholar
    • Export Citation
  • Frejka, T. and Sardon, J.P. (2006) First birth trends in developed countries: persisting parenthood postponement, Demographic Research, 15(art 6): 14780. doi: 10.4054/DemRes.2006.15.6

    • Search Google Scholar
    • Export Citation
  • Goldscheider, F. and DaVanzo, J. (1989) Pathways to independent living in early adulthood: marriage, semiautonomy, and premarital residential independence, Demography, 26(4): 597614. doi: 10.2307/2061260

    • Search Google Scholar
    • Export Citation
  • Goldscheider, F., Bernhardt, E. and Lappegård, T. (2015) The gender revolution: a framework for understanding changing family and demographic behavior, Population and Development Review, 41(2): 20739. doi: 10.1111/j.1728-4457.2015.00045.x

    • Search Google Scholar
    • Export Citation
  • Graham, M., Hill, E., Shelly, J. and Taket, A. (2013) Why are childless women childless? Findings from an exploratory study of childless women in Victoria, Australia, Journal of Social Inclusion, 4(1): 7089. doi: 10.36251/josi.63

    • Search Google Scholar
    • Export Citation
  • Gray, E. (2002) What do we know about men’s fertility levels in Australia?, People and Place, 10(4): 110.

  • Gray, E. and Evans, A. (2017) Geographic variation in parity progression in Australia, Population, Space and Place, 24(2): art e2080, https://doi.org/10.1002/psp.2080.

    • Search Google Scholar
    • Export Citation
  • Gray, E., Evans, A. and Reimondos, A. (2013) Childbearing desires of childless men and women: when are goals adjusted?, Advances in Life Course Research, 18(2): 1419. doi: 10.1016/j.alcr.2012.09.003

    • Search Google Scholar
    • Export Citation
  • Hagestad, G.O. and Call, V.R.A. (2007) Pathways to childlessness. a life course perspective, Journal of Family Issues, 28(10): 133861. doi: 10.1177/0192513X07303836

    • Search Google Scholar
    • Export Citation
  • Heaton, T.B., Cardell, K.J. and Holland, K. (1999) Persistence and change in decisions to remain childless, Journal of Marriage and Family, 61(2): 5319. doi: 10.2307/353767

    • Search Google Scholar
    • Export Citation
  • Hoem, J.M. (1986) The impact of education on modern family-union initiation, European Journal of Population, 2(2): 11333. doi: 10.1007/BF01796886

    • Search Google Scholar
    • Export Citation
  • Holton, S., Fisher, J. and Rowe, H. (2011) To have or not to have? Australian women’s childbearing desires, expectations and outcomes, Journal of Population Research, 28(4): 35379. doi: 10.1007/s12546-011-9072-3

    • Search Google Scholar
    • Export Citation
  • Jalovaara, M. and Fasang, A. (2017) From never partnered to serial cohabiters: union trajectories to childlessness, Demographic Research, 36(art 55): 170320. doi: 10.4054/DemRes.2017.36.55

    • Search Google Scholar
    • Export Citation
  • Johnson, J.A. and Tough, S. (2012) Delayed child-bearing, Journal of Obstetrics and Gynaecology Canada, 34(1): 8093. doi: 10.1016/S1701-2163(16)35138-6

    • Search Google Scholar
    • Export Citation
  • Joshi, H. (2002) Production, reproduction, and education: women, children, and work in a British perspective, Population and Development Review, 28(3): 44574. doi: 10.1111/j.1728-4457.2002.00445.x

    • Search Google Scholar
    • Export Citation
  • Keizer, R., Dykstra, P.A. and Jansen, M.D. (2008) Pathways into childlessness: evidence of gendered life course dynamics, Journal of Biosocial Science, 40(6): 86378. doi: 10.1017/S0021932007002660

    • Search Google Scholar
    • Export Citation
  • Kippen, R. (2006) The rise of the older mother, People and Place, 14(3): 111.

  • Kneale, D. and Joshi, H. (2008) Postponement and childlessness: evidence from two British cohorts, Demographic Research, 19(58): 193568 , doi: 10.4054/DemRes.2008.19.58

    • Search Google Scholar
    • Export Citation
  • Kocourkova, J., Burcin, B. and Kucera, T. (2014) Demographic relevancy of increased use of assisted reproductive technology in European countries, Reproductive Health, 11(37), doi: 10.1186/1742-4755-11-37

    • Search Google Scholar
    • Export Citation
  • Kohler, H.P., Billari, F.C. and Ortega, J.A. (2002) The emergence of lowest-low fertility in Europe during the 1990s, Population and Development Review, 28(4): 64180. doi: 10.1111/j.1728-4457.2002.00641.x

    • Search Google Scholar
    • Export Citation
  • Kravdal, Ø. (1994) The importance of economic activity, economic potential and economic resources for the timing of first births in Norway, Population Studies, 48(2): 24967. doi: 10.1080/0032472031000147786

    • Search Google Scholar
    • Export Citation
  • Lazzari, E. (2019) Socio-economic changes in the age-patterns of childbearing in Australia, Australian Population Studies, 3(2): 346. doi: 10.37970/aps.v3i2.52

    • Search Google Scholar
    • Export Citation
  • Lazzari, E. (forthcoming) Changing trends between education, childlessness and completed fertility: a cohort analysis of Australian women born in 1952–1971, Journal of Population Research. 

    • Search Google Scholar
    • Export Citation
  • Leridon, H. (2004) Can assisted reproductive technology compensate for the natural decline in fertility with age? A model assessment, Human Reproduction, 7(19): 154853. doi: 10.1093/humrep/deh304

    • Search Google Scholar
    • Export Citation
  • Leridon, H. (2017) Biological effects of first birth postponement and assisted reproductive technology on complete fertility, Population, 72(3): 44572. doi: 10.3917/popu.1703.0463

    • Search Google Scholar
    • Export Citation
  • Lesthaeghe, R. and Moors, G. (2000) Recent trends in fertility and household formation in the industrialized world, Review of Population and Social Policy, 9(1): 12170.

    • Search Google Scholar
    • Export Citation
  • Liefbroer, A. and Corijn, M. (1999) Who, what, where, and when? Specifying the impact of educational attainment and labour force participation on family formation, European Journal of Population, 15(1): 4575. doi: 10.1023/A:1006137104191

    • Search Google Scholar
    • Export Citation
  • Lutz, W. and Skirbekk, V. (2005) Policies addressing the tempo effect in low-fertility countries, Population and Development Review, 31(4): 699720.  doi: 10.1111/j.1728-4457.2005.00094.x

    • Search Google Scholar
    • Export Citation
  • Martin, S.P. (2000) Diverging fertility among U.S. women who delay childbearing past age 30, Demography, 37(4): 52333. doi: 10.1353/dem.2000.0007

    • Search Google Scholar
    • Export Citation
  • McDonald, P. (2000) Gender equity, social institutions and the future of fertility, Journal of Population Research, 17(1): 116. doi: 10.1007/BF03029445

    • Search Google Scholar
    • Export Citation
  • McDonald, P. (2013) Societal foundation for explaining low fertility: gender equity, Demographic Research, 28(art 34): 98194. doi: 10.4054/DemRes.2013.28.34

    • Search Google Scholar
    • Export Citation
  • McDonald, P. and Reimondos, A. (2013) Relationship pathways and first birth in Australia, in A. Evans and J. Baxter (eds) Negotiating the Life Course: Stability and Change in Life Pathways, Dordrecht: Springer, pp 6998.

    • Search Google Scholar
    • Export Citation
  • McDonald, P. (2020) A Projection of Australia’s Future Fertility Rates, Centre for Population Research Paper, Canberra: The Australian Government.

  • Mikolai, J. (2017) Partnership histories and the transition to motherhood in later reproductive ages in Europe, Population, 72(1): 12354. doi: 10.3917/popu.1701.0127

    • Search Google Scholar
    • Export Citation
  • Mills, M., Rindfuss, R.R., McDonald, P. and te Velde, E. (2011) Why do people postpone parenthood? Reasons and social policy incentives, Human Reproduction Update, 17(6): 84860. doi: 10.1093/humupd/dmr026

    • Search Google Scholar
    • Export Citation
  • Miranti, R., McNamara, J., Tanton, R. and Yap, M. (2009) A narrowing gap? Trends in childlessness of professional women in Australia 1986–2006, Journal of Population Research, 26(4): 35979. doi: 10.1007/s12546-009-9022-5

    • Search Google Scholar
    • Export Citation
  • Mynarska, M., Matysiak, A., Rybińska, A., Tocchioni, V. and Vignoli, D. (2015) Diverse paths into childlessness over the life course, Advances in Life Course Research, 25: 3548.  doi: 10.1016/j.alcr.2015.05.003

    • Search Google Scholar
    • Export Citation
  • Neels, K. and De Wachter, D. (2010) Postponement and recuperation of Belgian fertility: how are they related to rising female educational attainment?, Vienna Yearbook of Population Research, 8(1): 77106.  doi: 10.1553/populationyearbook2010s77

    • Search Google Scholar
    • Export Citation
  • Ní Bhrolcháin, M. and Beaujouan, É. (2012) Fertility postponement is largely due to rising educational enrolment, Population Studies, 66(3): 31127.

    • Search Google Scholar
    • Export Citation
  • Nisén, J., Martikainen, P., Silventoinen, K. and Myrskylä, M. (2014) Age-specific fertility by educational level in the Finnish male cohort born 1940–1950, Demographic Research, 31(art 5): 11936.

    • Search Google Scholar
    • Export Citation
  • Oppenheimer, V.K. (1994) Women’s rising employment and the future of family in industrial societies, Population and Development Review, 20(2): 293342. doi: 10.2307/2137521

    • Search Google Scholar
    • Export Citation
  • Parr, N. (2005) Family background, schooling and childlessness in Australia, Journal of Biosocial Science, 37(2): 22943. doi: 10.1017/S0021932004006546

    • Search Google Scholar
    • Export Citation
  • Parr, N. (2010) Childlessness among men in Australia, Population Research and Policy Review, 29(3): 31938. doi: 10.1007/s11113-009-9142-9

    • Search Google Scholar
    • Export Citation
  • Perelli-Harris, B., Mynarska, M., Berrington, A., Berghammer, C., Evans, A., Isupova, O., Keizer, R., Klärner, A., Lappegård, T. and Vignoli, D. (2014) Towards a deeper understanding of cohabitation: insights from focus group research across Europe and Australia, Demographic Research, 31(art 34): 104378. doi: 10.4054/DemRes.2014.31.34

    • Search Google Scholar
    • Export Citation
  • Peterson, B.D., Pirritano, M., Tucker, L. and Lampic, C. (2012) Fertility awareness and parenting attitudes among American male and female undergraduate university students, Human Reproduction, 27(5): 1375382. doi: 10.1093/humrep/des011

    • Search Google Scholar
    • Export Citation
  • Powell, J.L. (1986) Estimation of semiparametric models, in R.F. Engle and D.L. McFadden (eds) Handbook of Econometrics Volume 4, Amsterdam: Elsevier, pp 2443521.

    • Search Google Scholar
    • Export Citation
  • Raab, M. and Struffolino, E. (2019) The heterogeneity of partnership trajectories to childlessness in Germany, European Journal of Population, 36(1): 5370. doi: 10.1007/s10680-019-09519-y

    • Search Google Scholar
    • Export Citation
  • Rendall, M.S., Clarke, L., Peters, H.E., Ranjit, N. and Verropoulou, G. (1999) Incomplete reporting of men's fertility in the United States and Britain: a research note, Demography, 36(1): 13544. doi: 10.2307/2648139

    • Search Google Scholar
    • Export Citation
  • Rowland, D.T. (2007) Historical trends in childlessness, Journal of Family Issues, 28(10): 131137. doi: 10.1177/0192513X07303823

  • Rybińska, A. (2014) Motherhood after the age of 35 in Poland, Studia Demograficzne, 1(165): 728.

  • Saarela, J. and Skirbekk, V. (2020) Childlessness and union histories: evidence from Finnish population register data, Journal of Biosocial Science, 52(1): 7896. doi: 10.1017/S0021932019000257

    • Search Google Scholar
    • Export Citation
  • Schmidt, L., Sobotka, T., Bentzen, J.B., Nyboe Andersen, A. and ESHRE Reproduction and Society Task Force (2012) Demographic and medical consequences of the postponement of parenthood, Human Reproduction Update, 18(1): 2943. doi: 10.1093/humupd/dmr040

    • Search Google Scholar
    • Export Citation
  • Settersten, R.A. and Hagestad, G. (1996) What’s the latest? Cultural age deadlines for family transitions, Gerontologist, 36: 178188. doi: 10.1093/geront/36.2.178

    • Search Google Scholar
    • Export Citation
  • Sobotka, T. (2017) Post-transitional fertility: the role of childbearing postponement in fuelling the shift to low and unstable fertility levels, Journal of Biosocial Science, 49(S1): S2045. doi: 10.1017/S0021932017000323

    • Search Google Scholar
    • Export Citation
  • Summerfield, M., Bright, S., Hahn, M., La, N., Macalalad, N., Watson, N., Wilkins, R. and Wooden, M. (2019) HILDA User Manual – Release 18, Melbourne: University of Melbourne, Melbourne Institute of Applied Economic and Social Research.

    • Search Google Scholar
    • Export Citation
  • Tavares, L.P. (2016) Who delays childbearing? The association between time to first birth, personality traits and education, European Journal of Population, 32(4): 57597. doi: 10.1007/s10680-016-9393-1

    • Search Google Scholar
    • Export Citation
  • Testa, M.R. (2007) Childbearing preferences and family issues in Europe: evidence from the Eurobarometer 2006 survey, Vienna Yearbook of Population Research, 5(1): 35779. doi: 10.1553/populationyearbook2007s357

    • Search Google Scholar
    • Export Citation
  • Watson, N. (2012) Longitudinal and Cross-sectional weighting methodology for the HILDA survey, HILDA project technical paper series No. 2/12, Melbourne: University of Melbourne, Melbourne Institute of Applied Economic and Social Research.

    • Search Google Scholar
    • Export Citation
  • Watson, N. and Wooden, M. (2010) The HILDA survey: progress and future developments, Australian Economic Review, 43(3): 32636. doi: 10.1111/j.1467-8462.2010.00604.x

    • Search Google Scholar
    • Export Citation
  • Watson, N. and Wooden, M. (2012) The HILDA survey: a case study in the design and development of a successful household panel study, Longitudinal and Life Course Studies, 3(3): 36981.

    • Search Google Scholar
    • Export Citation
  • Watson, N. and Wooden, M. (2013) Adding a top-up sample to the HILDA survey, Australian Economic Review, 46(4): 48998. doi: 10.1111/1467-8462.12027

    • Search Google Scholar
    • Export Citation
  • West, C. and Zimmerman, D.H. (1987) Doing gender, Gender and Society, 1(2): 12551. doi: 10.1177/0891243287001002002

  • 1 Australian National University, , Australia

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