Perceptions towards pronatalist policies in Singapore

Abstract

Fertility rates have been declining in most high-income countries. Singapore is at the forefront of developing pronatalist policies to increase birth rates. This study examines perceptions towards pronatalist policies among men and women in Singapore and compares which policies are perceived as the most important contributors to the conduciveness for childbearing. Using data from the Singapore Perceptions of the Marriage and Parenthood Package study (N = 2000), the results from dominance analysis highlight two important findings. First, paternity leave, shared parental leave, and the Baby Bonus are the top three contributors to the conduciveness to have children. Second, the combined positive effect of financial incentives and work–life policies is perceived to be favorable to fertility. The findings suggest that low-fertility countries may wish to consider adopting this basket of policies as they are like to be regarded as supportive of childbearing. Although previous research suggests that pronatalist policies may only have a modest effect on fertility, the findings raise further questions as to whether fertility may decline even further in the absence of these policies.

Introduction

Increasing birth rates in low-fertility countries is important for maintaining sustainable populations. This has become an important policy agenda in many countries with an aging society and workforce. In Singapore, the rapid demographic transition that occurred from the 1960–2000s has led to a precipitous decline in fertility, resulting in a shift from a relatively youthful population to an aging population that is increasingly dependent on immigration for population growth (Yap & Gee, 2015). Singapore’s total fertility rates have declined substantially from 5.76 to 1.12 children per woman between 1960 and 2021 (Singapore Department of Statistics, 2022a). The country’s low fertility imposes significant strains on the government and economy due to the negative consequences associated with a shrinking labor force and an aging population (Jones, 2012). To address these demographic and economic challenges, policies to increase fertility have become a priority for Singapore and many other low-fertility nations.

Since the 1980s, the Singaporean government has introduced a range of pronatalist policies to reduce the financial costs of parenthood and facilitate a more conducive work–family balance. However, these policies appear to have only modest effects on Singapore’s fertility rates (Saw, 2016). Recent studies point to a potential mistargeting of pronatalist policies as a reason for the lack of policy effectiveness in several advanced Asian societies, including Singapore, Hong Kong, Taiwan, Japan, and South Korea (Chen et al., 2018, 2020). The studies found that policies prioritizing higher order births in Singapore may not provide adequate support to women aged 30–34 to facilitate their transition to parenthood. Thus, it is suggested that the policy focus should shift towards supporting this group of women instead.

Despite the call for policy improvements, systematic research into the needs of potential policy beneficiaries has been very limited (Sun, 2012). Most studies on pronatalist policies tend to focus on analyses aimed at quantifying outcomes or attributing fertility change to existing policy (e.g., Drago et al., 2011; Son, 2018). The needs of childbearing couples may be overlooked due to a lack of research and data regarding what they think about the range of pronatalist policy measures and how conducive these policies are to their fertility choices. Consequently, little is known about whether pronatalist policies actually fit the needs of target populations and their circumstances.

The present study attempts to fill this gap by using a unique data set to examine the perceptions of married men and women towards a range of policy measures intended to raise fertility rates. Drawing on data from the Perception of Policies in Singapore (POPS) Survey 7: Perceptions of the Marriage and Parenthood Package, the study investigates the relative importance of pronatalist policies among married people and within different sociodemographic subgroups (i.e., by age, sex, and child parity). It examines two research questions. First, to what extent do pronatalist policies in Singapore contribute to a conducive environment in which married, heterosexual couples will choose to have children? Conduciveness refers to the extent to which the policies support and facilitate the likelihood of childbearing among couples. Second, how do public perceptions towards different policies differ by individual sociodemographic characteristics?

While this study is unable to directly address the cause and effect of pronatalist policies on fertility, it serves as a first step in investigating how the married population views the importance of these policies, which may support further policy discussions about whether to replicate, scale up or revise pronatalist policies, and how to target different population subgroups more effectively. The policies under investigation—including baby bonus payments; tax incentives; paternal, maternal, and shared parental leave; and childcare support—have been widely adopted by governments around the world (United Nations Population Division, 2017). Using Singapore as a case study, the study provides useful insights into the relevance and importance of policy in addressing the potential needs of married men and women in the reproductive age.

Pronatal family policies: a review

Financial incentives and work–family initiatives

The rational choice approach to pronatalist policy design posits that policies that lower the costs of having children and provide childcare support to parents are likely to positively impact fertility (Coleman, 1990; Schultz, 1990). Financial incentives provided to parents through cash payments, tax relief, and subsidies can alleviate the direct costs¹ of having and raising a child. On the other hand, the gender relations perspective posits that work–family policies, such as parental leave and childcare subsidies, may alleviate the indirect costs² of having children and offset the additional time spent on childbearing and child-raising (McDonald, 2006).

However, empirical evidence on the impact of financial incentives on fertility has been mixed (Gauthier, 2007). Some studies have found positive associations between financial incentives and fertility (Drago et al., 2011; Milligan, 2005), whereas other studies have found no association between the two (Deutscher & Breunig, 2018; Jones, 2019). A recent systematic review of quasi-experimental evaluations of fertility policies (Bergsvik et al., 2020) showed that universal transfers, childcare, and a reduction in the costs of health services may have a positive impact on fertility, but the effects varied by age, child parity and country context. Notwithstanding the variability in results, one of the most consistent findings is that the overall effect of financial incentives on fertility tends to be modest and temporary, as financial incentives only cover a small fraction of the total cost of raising a child (Thevenon & Gauthier, 2011).

Work–family initiatives that support parents in combining work and family responsibilities have been shown to reduce the opportunity cost of children and increase fertility in more gender-egalitarian societies (Duvander et al., 2020; Rindfuss et al., 2010; Tan, 2022a, b; Thevenon, 2011). However, in low-fertility Asian societies that are heavily influenced by Confucianism, working mothers still tend to shoulder a disproportionately larger share of childcare and domestic tasks (Singapore Ministry of Social & Family Development, 2017). In a comparison of parental leave and childcare support policies in Sweden and South Korea, Lee et al. (2016) found that the policies were less effective in South Korea due to women’s significantly higher contribution to household labor relative to that of men. Considering that Singapore is ranked 54th out of 156 countries on the Global Gender Gap Index 2021, lying approximately halfway between Sweden in fifth place and South Korea in 102nd place, work–family initiatives may provide opportunities for men to get involved in the family, and assist in creating a more conducive environment for couples to have children in Singapore (World Economic Forum, 2021).

Pronatal policy targeting

To understand why existing policies may have been less successful than anticipated in increasing fertility rates, recent studies have identified the potential mistargeting of policies as a possible reason for the limited impact of policy on fertility (Chen et al., 2018, 2020; Gauthier, 2016). In Japan, South Korea and Taiwan, Gauthier (2016) found a misalignment between the supply and demand of pronatalist policies. In particular, the high costs of children are perceived to be a major barrier to childbearing in the three East Asian societies, but governmental financial support remains inadequate in meeting the needs of families, especially in light of rising private education costs. In addition to financial costs, there is also a perceived incompatibility between work and family responsibilities that may not have been adequately addressed by policy. As women are often expected to take on a second shift after work and perform the role of a homemaker and caregiver, work–family conflicts hinder progression to higher parities as time and resource demands increase with each additional child (Chen & Yip, 2017; Torr & Short, 2004).

Some studies have emphasized the need for increased efforts to implement better targeted pronatalist policies. Chen and Yip (2017) stressed that the perceived challenges of parenthood tend to differ according to child parity. This is because the needs and considerations of parents become more complex as parity increases (Frejka et al., 2010). Policies are likely to be more conducive for couples making their first transition to parenthood, as the desire for the first child is generally considered intrinsically motivated; hence, policies tend to be viewed as facilitative or supportive of intended childbearing (Botev, 2015). Conversely, policies aimed at incentivizing higher order births could reduce the motivation to have additional children, as they may be perceived as insufficient, coercive, or restrictive of individual autonomy (Frey, 2012). Given that the motivation and needs of high-parity parents are unlikely to be met by extrinsic incentives, policies may be less conducive for those with high parity than those with low parity (Botev, 2015).

There is also a general age pattern of fertility that aligns with the fecundity (i.e., reproductive capacity) of each couple. Given that fecundability declines as people get older, responses to policy intervention may also wane with time. Previous research suggests that people are more likely to adjust their fertility intentions downwards as they age and, thus, pronatalist policies may be less conducive for older individuals compared to their younger counterparts (Chen & Yip, 2017; Liefbroer, 2009). There could also be gender differences in parenting responsibilities and expectations because men and women negotiate the demands of parenthood differently (Barnes, 2015). Given that women tend to bear the burden of childbearing and child-raising, there are two ways in which policies may be perceived. Policies may be perceived as conducive if women feel that the policies can improve gender equity in the division of housework and childcare (McDonald, 2013). However, if women feel that the unequal division of domestic labor is likely to persist, then the usefulness of policy may be weakened.

The Singaporean context

A contextual understanding of Singapore’s fertility trends and policy framework is important for highlighting ongoing demographic and policy shifts. Singapore’s total fertility rate of 1.12 children per woman in 2021 is one of the lowest in the world. Significant delays in childbearing can be observed by the shifting age-pattern of fertility in Fig. 1. The figure shows that increases in fertility at ages 30 and older did not make up for fertility declines in younger age groups, resulting in an overall decrease in fertility rates across cohorts.

Fig. 1

Source: Singapore Department of Statistics (2022a)

Cohort-age specific fertility rates, 1940–1994.

Figure 2 shows the declining cumulative cohort fertility rates for each successive cohort after the 1940–1944 cohort. The persistent decline in cohort fertility may lead to an older population age structure and create a momentum for future population decline (Lutz et al., 2006). It is thus a demographic imperative for Singapore to increase its fertility rates to ensure a sustainable population.

Fig. 2

Source: Singapore Department of Statistics (2022a)

Cumulative cohort fertility rates in 2020.

Singapore is known for its comprehensive and long-standing policies to encourage childbearing. Since 1987, the government has started promoting family formation, and by 1995 had more pronatalist policies in place than any other country. A comprehensive Marriage and Parenthood Package was introduced by the government in 2001 as part of the ongoing effort to address Singapore’s falling birth rates (National Population and Talent Division, 2012). A range of policy measures were implemented to “create a total environment conducive to raising a family” (National Archives of Singapore, 2000, para. 118).

Based on Heitlinger (1991) and McDonald’s (2002) policy classification framework, Singapore’s pronatalist policies can be grouped into two broad categories: financial incentives and work–family initiatives. Financial incentives include cash payments, tax relief, and housing subsidies. The Baby Bonus cash payments was introduced in 2001 to help families defray the costs of raising a child and offer financial support following the birth of a child. When it was first implemented, eligible couples received cash gifts for having a second (S$500³) or third child (S$1000). The amount has since increased to S$8000 for a first or second child and S$10,000 for a third or subsequent child (Made for Families, 2022a). The Working Mother’s Child Relief provides a tax deduction on a proportion of women’s earned income to encourage working mothers to have children and stay in the workforce. Working mothers may claim 15% of their earned income for their first child, 20% for their second child, and 25% for their third child and any subsequent children, with a maximum cap at 100% of their earned income (Inland Revenue Authority of Singapore, 2022). Housing schemes and grants were introduced to help couples purchase and finance their first home. Priority is given to married couples with or expecting a child and families with more than two children (Housing & Development Board, 2022). Eligible first-time home buyers who are married may qualify for a housing grant of up to S$80,000 to help with their flat purchase (Housing & Development Board, 2022). The government also assists with the costs of conception for Assisted Conception Procedures (ACPs), subsidizes pregnancy-related healthcare expenses, and provides a Medisave account (Singapore’s national medical savings account) for newborns that can be used for a range of healthcare expenses. Couples undergoing ACPs in public assisted reproduction centers can receive up to 75% in co-funding from the government (Singapore Ministry of Health, 2022). The maternity package allows parents to use their Medisave for medical care pre-delivery (e.g., pre-natal consultations, ultrasound scans, tests, medications) and during delivery (e.g., delivery procedure, hospital admission) (Made for Families, 2022b). A grant is also provided to set up a Medisave account to pay for newborn’s healthcare expenses. The grant amount was S$3000 in 2013–2014 and was subsequently increased to S$4000 for children born on or after 1 January 2015 (Singapore Ministry of Health, 2022).

Work–family initiatives include maternity leave, paternity leave, child-related leave, and childcare subsidies. Introduced in 2004, the government-paid maternity leave provides working mothers with 16 weeks of paid maternity leave to support their recovery from childbirth and encourage bonding with their newborns. Government-paid paternity leave was later introduced in 2013, entitling working fathers to 1 week of paid paternity leave and allowing them to share up to one week of their wife’s 16 weeks of maternity leave, subject to her agreement (Singapore Ministry of Social & Family Development, 2013). Since 2017, the paternity leave was extended to two weeks for eligible working fathers, including those who are self-employed. In addition, eligible fathers can take up to four weeks of shared parental leave (Singapore Ministry of Manpower, 2020). To further support parents with combining work and childcare responsibilities, parents of children enrolled at licensed childcare centers are given subsidies of up to S$600 per month for infant care and up to S$300 per month for daycare. Working parents are also allowed to take up to six days of childcare leave per year if their child is below the age of seven, and up to six days of unpaid infant care leave per year if their child is under the age of two.

Existing policy discussions suggest that the policies have not had a positive impact on fertility. Jones (2019) argues that financial incentives are ineffective as they only cover less than a third of the total costs of raising a child in Singapore. McDonald and Evans (2002) posit that cash incentives and subsidies are much less effective than initiatives geared towards mitigating the opportunity cost of having children. However, other than policy discussions (Jones, 2012, 2019), content analysis (Wong & Yeoh, 2003), aggregate research (Chen et al., 2018; Jones & Hamid, 2015), and qualitative studies (Teo, 2010; Williams, 2014), there is limited empirical evidence on the extent to which Singapore’s pronatalist policy measures contribute to a conducive environment in which couples will choose to have children. Even within the broader literature, little attention has been paid to understanding how intended beneficiaries perceive the utility of policy. Therefore, this study aims to understand the policy perceptions among couples and different sociodemographic subgroups to provide insights into the extent to which pronatalist policies are able to meet the needs of individuals for childbearing in a low-fertility context.

Data and methods

This study used data from the POPS Survey 7: Perceptions of the Marriage and Parenthood Package. Permission for the use of the data was obtained from the Singapore Institute of Policy Studies. The POPS Survey 7 is a nationally representative survey of 2000 married Singaporean citizens and permanent residents aged 21–49. The survey was undertaken to examine the attitudes of married, childbearing-age participants towards policies that support family formation. Single parents and individuals who are divorced, separated, or widowed were excluded from the survey. The data were collected between July and September 2014 via a door-to-door interview method. Participants were selected through a multistage cluster sampling method using a sampling frame obtained from the Singapore Department of Statistics. In line with the 2010 Census, quotas based on sex, ethnicity, and housing type were used to ensure a nationally representative sample. Households were first grouped into reticulate units with 200 households of the same housing type in each unit, then a random sample of 100 units was obtained. Twenty households were selected from the 100 units, and an eligible person from each household was interviewed. In cases where the selected household did not have an eligible participant or when a potential participant refused to participate, an eligible person from a matching dwelling was invited to complete the survey. The respondent profiles are generally representative of Singapore’s married resident population aged 21–49. A comparison of sociodemographic characteristics between the sample and the population can be found in Table 5 of the Appendix. The final sample included all 2000 Singaporean residents.

Dependent variable

The dependent variable is the overall conduciveness of policies for childbearing (“On the whole, has the most recent Marriage and Parenthood Package made it conducive for you and your spouse to have children?”), which was recorded as a binary variable (0 = no, 1 = yes).

Independent variables

Twelve policy measures were examined, covering both financial incentives and work–family initiatives. The policies include the Baby Bonus, housing schemes and grants, working mother’s child relief, the maternity package, the healthcare grant for newborns, co-funding for ACPs, maternity leave, paternity leave, shared parental leave, extended childcare leave, unpaid infant care leave, and subsidies for center-based infant and childcare (see Table 6 in the Appendix for the list of policies). Participants were asked whether each policy would influence them to have (more) children (0 = no, 1 = yes).

Control variables

Six key sociodemographic variables, including age, sex, ethnicity, educational attainment, number of children born, and employment status, were included in the analyses. Age was coded into three categories: below 30, 30–39, and above 39. Gender was coded as a binary variable (0 = man, 1 = woman). Ethnicity included four categories: Chinese (reference group), Malay, Indian, and other ethnicities. Educational attainment was categorized into secondary school education or lower (reference group), diploma and other professional qualifications, and university degree or higher. Number of children was grouped into no children (reference group), one child, two children, and three or more children. Employment status was coded as a binary variable (0 = unemployed, 1 = employed).

Analytic strategy

Dominance analysis was used to evaluate the relative importance of pronatalist policies in contributing to the overall conduciveness for childbearing at the population level and in stratified subgroups (i.e., by age, sex, and child parity). The analyses are based on a logistic regression model with overall conduciveness as the outcome and the 12 policy measures as predictors, adjusting for sociodemographic characteristics. Dominance analysis is a method of comparing the relative importance and ranking of predictors (i.e., dominance profiles) based on how much each predictor contributes to the total variance of the outcome in a model (Azen & Budescu, 2003). Dominance analysis considers both the unique contribution of a predictor and its contribution when combined with other predictors. It is an ensemble approach that estimates all possible regression models and subset models to compare the change in model fit (R²), quantifying the influence of a predictor when added to all possible subset models with a given set of predictors (Azen & Traxel, 2009). Specifically. the dominance analyses in this study consisted of 4095 (2¹²–1) regression models containing all possible combinations of predictors. Dominance analysis has been a popular method used by many researchers and practitioners in recent years to assess the relative contribution of a large set of predictors to a specific outcome (e.g., Gromping, 2007; Johnson & Lebreton, 2004; Mange et al., 2021; Peacock, 2021; Vize et al., 2019). Stata/SE v15.1 was used to prepare the data and conduct the analyses. Dominance analysis was performed using the community-contributed command domin (Luchman, 2021).

Results

Descriptive results

Overall, 40% of respondents reported that the policies were conducive. The majority of those who were aged under 30 (61.93%) were more likely to report that the policies were conducive for them compared to those aged between 30 and 39 (49.35%), and those aged above 39 (27.90%) (see Table 1). Men were more likely than women to view the policies as conducive. Approximately half of the proportion of ethnic Indians (50.59%) reported that the policy measures were conducive for them, compared to the ethnic Chinese (36.8%), ethnic Malay (45.11%), and respondents of other ethnicities (47.06%). Respondents who had no children (59.25%) were more likely to report that the policies were conducive for them compared to those with one child (47.44%), two children (32.62%), and three or more children (32.36%). Among parents, those who reported that the policy measures were conducive to parenthood had younger children than those who reported otherwise. On average, the youngest child in the family was eight years old for those who reported that the policies were conducive and 11 years old for those who reported that the policies were less conducive. There was no discernible difference in overall conduciveness across education groups and employment statuses, although there are some variations by occupation and monthly household income. Compared to other occupations, professionals (37.96%), technicians and associate professionals (16.62%), and service and sales workers (17.53%) made up a higher proportion of respondents who reported that the policies were conducive. Those with higher monthly household income (> S$6000) were less likely to view the policies as conducive than those in lower household income categories. In addition, about 41% of respondents in a dual-earner relationship reported that the policies were conducive to childbearing.

Table 1 Sociodemographic characteristics on overall conduciveness (N = 2000)

Main findings

There were three significant policy measures contributing to the conduciveness for childbearing (see Fig. 3). Financial incentives and work–family initiatives along with sociodemographic characteristics explained 24% of the variance in the overall conduciveness of policies (see Table 7 in the Appendix for details on the logistic models). The three policy measures explaining most of the variance in the overall conduciveness were paternity leave (2.43%), shared parental leave (2.18%), and Baby Bonus (1.59%) (Fig. 3).

Fig. 3

Adjusted dominance statistics for all respondents (N = 2000). Adjusted for age, sex, ethnicity, number of children, educational attainment, and employment status. Rank of policy measures based on average increase in total variance explained by the model (R²) when adding a variable to all possible subset models. *p < .05, **p < .01

Stratified analyses

Pronatalist policies were more likely to influence the conduciveness for younger Singaporeans to have children compared to their older counterparts (see Table 2). In the analyses stratified by age group, the predictors explained 35.04%, 21.96%, and 20.65% of the variance in overall policy conduciveness for those under 30, between 30 and 39, and above 39 respectively. For the younger age group (< 30 years), the most important policy measures were shared parental leave (6.21%), paternity leave (5.25%), and working mother’s child relief (3.26%). For the middle age group (30–39 years), the most relevant policy measures were the healthcare grant for newborns (2%), Baby Bonus (1.94%), and paternity leave (1.91%). For the older age group (> 39 years), the most important policy measures were paternity leave (2.99%), shared parental leave (2.95%), and extended childcare leave (1.75%).

Table 2 Unadjusted and adjusted dominance analyses stratified by age (N = 2000)

Men were more likely than women to have a positive perception of the policies (see Table 3). The predictors explained 28.37% and 21.42% of the variance in overall conduciveness to have children for men and women respectively. For men, the most important policy measures were paternity leave (3.82%), shared parental leave (3.04%), and extended childcare leave (2%). In contrast, Baby Bonus (1.75%), healthcare grant for newborns (1.71%), and paternity leave (1.55%) were the most important policy measures for women.

Table 3 Unadjusted and adjusted dominance analyses stratified by sex (N = 2000)

Individuals with one or no children were more likely to report that the policy measures were conducive for them compared to individuals with two or more children (see Table 4). The predictors explained 28.35% of the variance in overall conduciveness for those with no children, 27.21% for those with one child, 19.72% for those with two children, and 23.36% for those with three or more children. For those with no children, the most important policy measures were paternity leave (3.8%), shared parental leave (2.97%) and the maternity package (2.93%). For those with one child, the most important policy measures were shared parental leave (2.34%), Baby Bonus (2.31%), and infant and childcare subsidies (2.22%). For those with two children, the most important policy measures were paternity leave (2.22%), the healthcare grant for newborns (1.9%), and shared parental leave (1.83%). Lastly, for those with three or more children, the most important policy measures were paternity leave (2.76%), shared parental leave (2.35%), and the healthcare grant for newborns (1.9%).

Table 4 Unadjusted and adjusted dominance analyses stratified by parity (N = 2000)

Sensitivity analysis

Robustness checks were performed for the logistic regression models and ordering of relative importance among policy measures. The bootstrap resampling technique was used to assess the stability of the models and dominance results. The models were fitted repeatedly to 500 additional bootstrap datasets to calculate more accurate standard errors and assess the extent to which the dominance pattern is reproduced in the 500 bootstrap samples (i.e., internal replicability; Thompson, 1994). The standard errors and confidence intervals obtained for the bootstrap samples were comparable to the estimates of the final model and the dominance results were obtained in all bootstrap samples. In addition, it may be possible that the effect of sex on the conduciveness of policies could be moderated by age, where the conduciveness of policies may differ for older women reaching the end of their fecundity compared to men of similar ages. The effect of child parity on the conduciveness of policies may be moderated by age, as individuals with more children are likely to be older compared to those with fewer children. It is also plausible that the effect of education on the conduciveness of policies may differ for individuals born in different cohorts. Therefore, a series of two-way interactions were tested to assess the effect of sex by age, parity by age, and education level by age. The interaction terms between sex and age; parity and age; and education and age were not significant and were not included in the final model. Further alternative specifications were made by including other sociodemographic characteristics, such as religion, occupation, residential type, and monthly income. The alternative models yielded similar results and the inclusion of these variables did not improve the model fit; hence, they were not included in the final model.

Discussion and conclusion

This study investigated how married men and women perceived the extent to which a range of pronatalist policies in Singapore are conducive for childbearing. To better understand the needs and demands of married individuals at different life stages, the study also assessed whether the perception of policy conduciveness varied by age, sex, and child parity. To address the first research question, the main analysis showed that the top three policies that were viewed as most conducive to childbearing were paternity leave (2.43%), shared parental leave (2.18%), and the Baby Bonus (1.59%). This finding is in line with the rational choice theory (Coleman, 1990) and gender relations perspective (McDonald, 2006).

Consistent with the rational choice theory, pronatalist policies aimed at reducing the direct and indirect costs of children contribute positively to facilitate childbearing. While the desire to have children is often intrinsically motivated, financial incentives help to alleviate the costs of children and provide monetary support such that the net psychological benefits of having a child still outweigh its costs. On the other hand, leave provisions can enhance gender equity at home and reduce barriers to parenthood, which accords with the gender relations perspective. Paternity leave and shared parental leave are forms of work and family support that support men to be more engaged fathers and encourage them to contribute to caregiving and family responsibilities. Based on gender equity theories of fertility, men’s increased involvement in the family would reduce the burden on women and increase childbearing (Goldscheider et al., 2015; McDonald, 2006). Taken together, this study provides suggestive evidence that work–family policies, coupled with financial incentives such as the Baby Bonus, may help to address challenges faced by couples.

Although work–family initiatives (i.e., paternity leave and shared parental leave) ranked higher than the Baby Bonus incentive, they were all positively associated with the conduciveness for childbearing (p < 0.05). In fact, the combination of financial incentives and work–family initiatives (16.71%) explained the overall conduciveness to have children more than by individual characteristics (7.29%). These findings align with Jones’s (2019) suggestion that while Singapore’s pronatalist policies may not have been particularly successful in raising the country’s birth rates, it might be that fertility would have declined even further in the absence of these policies.

Speaking to previous findings by Gauthier (2016), which indicate that economic cost was the main concern for childbearing in Japan, Taiwan, and South Korea, the results of this study showed that work–family initiatives were perceived as more important than financial incentives in Singapore. This may be due to the different economic costs involved in children’s education for parents in the three East Asian societies compared to Singapore. In particular, parents in South Korea, Japan, and Taiwan tend to invest large amounts of money in private education and tutoring to help their children succeed in the education system and gain access to expensive, prestigious schools (Anderson & Kohler, 2013). Although parental expectations of children’s educational attainment were not examined in this study, qualitative evidence suggests that similar intensive parenting norms are present in Singapore (Göransson, 2022). However, prestigious schools in Singapore are mainly public schools subsidized by the government and the monthly average spending on private tutoring in Singapore is approximately USD$83 per child compared to USD$359 in Korea, USD$275 in Japan, and USD$253 in Taiwan (Gietel-Basten, 2019; Korean National Statistics Office, 2021; Singapore Department of Statistics, 2019; Tan, 2017). Accordingly, the economic burden of private education and tutoring may be less pronounced for parents in Singapore than in South Korea, Japan, and Taiwan. In addition, the lower priority given to housing grants as an incentive for childbearing may be due to the higher rate of homeownership among the married population, which reduces the need for such incentives. Nevertheless, housing grants may still be an important policy measure to encourage marriage and subsequent parenthood—particularly among the younger population.

Work–family balance may be particularly important in Singapore, as organizational culture and prevalent work structures continue to encourage the practice of long working hours and continuous full-time service, penalizing alternative career pacing or trajectories. In Singapore, about 67.7% of married women and 94.3% of married men with children participate in the labor market, working an average of 48 h per week with limited flexibility in work arrangements (Singapore Ministry of Social & Family Development, 2017). Recent evidence has shown that work-related stress and fatigue have led to the underachievement of ideal sexual frequency and family size among married Singaporean couples (Tan, 2021). Thus, the role of work–family initiatives may be perceived positively, as they could potentially alleviate the stress and exhaustion experienced by married couples and facilitate their childbearing ideals. While the results suggest that work–family initiatives such as paternity leave could have a relatively higher impact than financial incentives, it is important to note that the policies were implemented at different times and may have varying degrees of signaling effect. For example, the Baby Bonus (initiated in 2001) and housing schemes (initiated in 1994) are some of the earliest policies introduced, whereas government-paid paternity leave and shared parental leave were introduced more recently, in 2013. Respondents may thus have had greater awareness of the paternity leave than other support schemes during the period when the survey was administered. Notwithstanding the recency effect, official figures indicate that the take-up rate of paternity leave has more than doubled from 25% in 2013 to 55% in 2019 (Singapore Ministry of Social & Family Development, 2022). The Singaporean government is optimistic that greater workplace support and shifts towards a culture of father involvement in child-rearing will result in increased paternity leave uptake (Singapore Ministry of Social & Family Development, 2022). Evidence in Singapore also shows that paternity leave—especially taking leave for two weeks or longer—is associated with higher marital satisfaction, increased father involvement in raising children, and stronger father–child relationships (Yeung & Li, 2022). Thus, initiatives aimed at enhancing work–family balance may not only benefit family dynamics, but also children’s social and emotional outcomes (Yeung & Li, 2022).

Turning to the second research question on whether the influence of policy varied by sociodemographic characteristics, the findings from stratified analyses showed slightly varying dominance profiles where the policies were more conducive for younger individuals than older individuals, for men than women, and for individuals with one or no children than individuals with two or more children. These findings are consistent with previous research (Chen et al., 2020), which highlights the importance of recognizing the varying needs of different subgroups to tailor policies that respond to their needs and are relevant to their circumstances.

The findings suggest that the support needed for childbearing varies at different ages and life stages. The mean years of schooling have more than doubled over the past half century, increasing from about 5.6 years to 12.1 years for men, and about 3.7 years to 11.3 years for women between 1980 and 2022 (Singapore Department of Statistics, 2022b). The longer time frame for school completion may result in delays in subsequent adulthood transitions, including the entrance into the workforce, departure from the parental home, marriage, and parenthood (Furstenberg, 2010). This suggests that individuals wanting to get married and have children at younger ages (before age 30) may require additional time and financial support to manage the potential trade-off between work and childcare. For individuals aged 30–39, the transition to parenthood may be starting to become the norm and other financial incentives could further assist this transition. Those who have accumulated more socioeconomic resources at later ages (after 40) may prioritize investing more time in parenting. In summation, rather than a one-size-fits-all approach, the findings suggest that the prioritization and sequencing of policies may be better tailored to fulfill each family’s own economic and fertility aspirations at different life stages.

The sex-stratified models showed that men were more likely to have a favorable perception of the policies than women. This may be due to the differential opportunity cost of parenthood for men and women. In other words, the substantial burden accompanying motherhood may not be easily mitigated by policy. Increasing evidence has shown that working mothers tend to suffer a motherhood penalty, as they are likely to experience slower career advancement and earn lower wages than their male counterparts (Budig & England, 2001; Pepping & Maniam, 2020). The highest wage penalties are experienced by mothers who first return to work after birth (Anderson et al., 2003), which may adversely affect their career prospects and disincentivize women from taking time off to have children. While policies that encourage men’s involvement in the family should improve fertility by narrowing the gender gap in the division of household labor (Goldscheider et al., 2015), there are larger structural and systemic issues hindering childbearing that may not be resolved until the motherhood wage penalty diminishes and it becomes common for men to contribute to housework and childcare. This may be further supported by the additional findings showing that paternity leave and shared parental leave ranked highly across parities as the most important contributors to the overall conduciveness for childbearing. Overall, these policies may encourage a desirable work-life balance that is supportive of children and families.

The degree to which policy may influence childbearing choices appears to be patterned by one’s sociodemographic characteristics, which could also vary at different phases of adulthood. The observed age pattern suggests that different emphasis is placed on competing parenthood priorities across the life course. This difference may be attributable to the varying financial and emotional costs of raising children at different ages (McDonald, 2006). Prevailing social and gender norms could also influence policy perceptions as policies may not adequately address challenges pertaining to the rise in singlehood and slow shifts in gender norms (Jones & Yeung, 2014; Tan, 2022a, b). In addition to policy, grandparental assistance in childcare is highly valued in Singapore, especially among dual-income families (Low & Goh, 2015). While intergenerational support was not examined in this study, a holistic and intergenerational approach to understanding and supporting families could benefit future work. Importantly, personal and family circumstances are crucial to note when investigating policy perceptions and their influence on potential childbearing.

The results should be interpreted with caution. First, the data do not provide information on alternative perspectives beyond that of the target population (i.e., married, heterosexual couples). Only respondents who were married at the time of the survey were included. There is a lack of available data and an overall gap in the literature on policy perceptions among, and policy initiatives directed towards, diverse populations (e.g., non-heterosexual and unmarried groups) (Cahill & Tobias, 2007). Future research should explore policy initiatives targeted at diverse populations to gain a more encompassing perspective on the influence of policy in addressing low fertility. Second, small sample sizes for certain ethnic groups may limit the ability to estimate associations of interest with precision. In particular, the results relating to individuals of ethnicities other than Chinese, Malay or Indian (N = 68) should be interpreted with caution due to the small sample size. Third, the impact of pronatalist policies on fertility behavior cannot be directly tested. Given the data availability, this study focuses only on investigating the perception of married individuals towards the conduciveness of pronatalist policies rather than actually capturing the effects of these policies on fertility. Follow-up longitudinal, experimental study designs may address this less explored area. Lastly, fertility is influenced by both facilitating and constraining factors, but it was beyond the scope of this study to address constraining factors that are central to theoretical explanations of low fertility. Pronatalist policies may be perceived as a facilitator as well as a constraint on fertility because policies may have an unintended adverse effect on childbearing by undermining the intrinsic value of having a child and appearing coercive to intended policy beneficiaries (Botev, 2015). For example, the Singaporean government’s interference with the private affairs of marriage and procreation has brought criticisms of undue meddling in the intimate lives of citizens (Leong & Sriramesh, 2006). Therefore, more research is needed to understand how pronatalist measures may have the opposite effect on fertility than is intended by policy.

Despite these limitations, the present study serves as a provisional first step in understanding the perceptions towards the conduciveness of pronatalist policies among married men and women. The findings of this study suggest that adopting a combination of financial and work–life balance policies may help to lessen the financial and caregiving stress of parents who just had a new child and could potentially support individuals in realizing their ideal family size.

Appendix

See Tables 5, 6, 7.

Table 5 Comparison between the sample and the population

Table 6 List of policies

Table 7 Unadjusted and adjusted binary logistic models (N = 2000)