Society at a Glance: Asia/Pacific 2025

1. Fertility trends in the Asia/Pacific region: Underlying drivers and what role for policy?

Introduction and main findings

Over the 1950 to 2021 period the global total fertility rate more than halved, from close to 5 children per woman in 1950 to just over 2 children per woman in in 2021 (Bhattacharjee et al., 2024[1]). The reasons for the decline are many, and differ across societies, but include increased access to contraceptive measures, women’s empowerment and improved educational attainment, economic factors, such as the cost of raising children and the cost of housing, as well as changing societal attitudes. Low levels of fertility in combination with increased life expectancy will lead to declining working-age populations and growing numbers of older people, with implications for healthcare and social protection systems.

Across global regions fertility trends differ, as they do across the Asia/Pacific region and the OECD area. In general, however, fertility rates first declined in higher-income countries before they fell in medium- and low-income countries. By 2022, Total Fertility Rates (TFRs) in OECD countries had fallen to 1.5 children per woman, on average, while rates across the Asia/Pacific region had fallen to just over 2 children per woman and TFRs in East Asia had fallen to around 1 child per woman. This decline will change the face of societies, communities and families and potentially has large effects on economic growth and prosperity. Therefore, policy makers are seeking to understand what drives these changes, why adults have fewer children, or none at all, and what can be done to support adults to have the number of children they would like to have, at the time of their choosing.

Personal choices on having a child depend on a wide range of factors, such as, individual preferences, social norms, medical conditions, but also economic aspects such as financial and labour market security, the cost of raising children – also in time, and the family policy environment.

Becker’s economic approach towards fertility trends postulates that an increase in income or a decline in the cost of children would affect both the quantity and quality (expense) of children, usually increasing both, while an increase in contraceptive knowledge would also affect both but would increase quality while decreasing quantity (Becker, 1960[2]). Indeed, since Becker’s seminal work, many studies have demonstrated that key economic variables, such as household income, how it is split between parents, and the cost of childcare, education and housing, all can affect whether people decide to have children, when to have them, and how many children to have.

Over the past decades, key societal, policy and economic changes have taken place, including increased educational attainment – particularly among women, increased access to effective contraceptive measures, a growing predominance of dual-earner households, and a strengthening of public policies (such as paid leave and formal early childhood education and care (ECEC) services) that help parents find a balance between work and family responsibilities and thus reduce the opportunity cost of having children. All these changes affect the choices women and their partners make with respect to having a(nother) child.

In addition, changes in attitudes towards parenthood may provide another explanation for changes in fertility rates. The Second Demographic Transition theory has emerged as a central theory to explain changes in family formation over the course of the 2000s and 2010s in many OECD countries (Sobotka, 2008[3]). It postulates that as societies reach a certain level of economic advancement, non-materialist values such as self-fulfilment become more important to people. As both men and women more often find meaning to life outside of parenthood, they might more often postpone or renounce having children to pursue other life goals, including career advancement and self-actualisation (i.e. the highest form of psychological development, where individual potential is fully realised (Maslow, 1943[4])). However, the theory does not fully apply to East Asia, where attitudes towards marriage and having children have been slow to change, and as childbirth outside marriage remains uncommon, the decline in marriage rates has contributed to an increase in the number of “childless singles” and a decline in fertility rates.

This chapter looks at the decline in the Total Fertility Rate (TFR) observed in many Asian/Pacific and OECD countries. It discusses fertility trends in the region, population projections and changing national contexts as well as policy development and public family supports across the region. It draws from OECD wide regressions on the impact on fertility trends of public family policy, labour market factors, societal attitudes and household costs items, such as housing and education (Fluchtmann, van Veen and Adema, 2023[5]), and it accounts for the international literature with a particular view to the Asia/Pacific region. The chapter ends with summary remarks on policy implications.

Main findings

Fertility trends differ across countries in the Asia/Pacific region and the OECD area. In general, fertility rates declined in higher-income countries before they fell in many medium- and/or low-income countries. By 1970, the average Total Fertility Rate across OECD countries had already fallen to 2.8 children per woman. By contrast, in all countries of the Asia/Pacific region other than Japan, TFRs were at the time still above the approximate “replacement level” of 2.1 children per woman (a level at which, a country’s population will remain stable while abstracting from migration): the average TFR across the Asia/Pacific region stood at 5.2 children per woman in 1970. Growing autonomy and agency in family planning explains part of the fertility decline since then. However, major social and economic developments that have changed the conditions for family formation and parenthood, have also had an impact.

By 2022, the TFR across Asia/Pacific had fallen to replacement level. At almost 4 children per woman the TFR remains highest in Samoa, while the TFR stood at 3.0 and over in Kazakhstan, Pakistan, Papua New Guinea, Tajikistan, Timor-Leste, Tonga and Uzbekistan. In Indonesia the TFR had fallen to 2.2 children per woman, and in India it stood at 2 children per woman. The TFRs in Australia and New Zealand were 1.63 and 1.66 respectively in 2022, just above the OECD average which had fallen to an all-time low of 1.5 children per woman (OECD, 2024[6]). In Thailand the TFR stood at 1.33, in Japan at 1.26, in China at 1.18 children, while in Hong Kong (China) and Korea it had fallen to about 0.7 children per woman. By contrast, Mongolia and countries in Central Asia – Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan, have experienced increases in the TFR since the mid‑2000s. This increase coincided with strong economic growth over the past 30 years in these countries.

The main findings of this chapter include:

• The mean age at which mothers have their first child on average across the OECD has increased by 3 years to 29.4 years of age over the 2000‑21 and is highest in Korea at 33 years of age. Across the Asia/Pacific region on average, the mean age at first childbirth is almost five years below the OECD average. Across Oceania – the area with the highest fertility rates in the Asia/Pacific region, fertility rates remain highest among women in the 20‑24 age‑group.

• The trend towards postponement of births across the OECD and in many Asian countries potentially has negative consequences for overall fertility. As young people wait longer to have children, they may shift family formation to a point where fecundity problems – that is the ability to have children – could interfere with the realisation of desired fertility. Advances in reproductive medicine can, at least in part, allow women to have children at older ages, and in Japan, Korea and Singapore public support is available towards such interventions.

• The fall in TFRs is related to women having fewer children and/or none at all. Comprehensive data for the Asia/Pacific countries on childlessness and birth order is not available, but in Japan 28% of women born in 1975 were childless – the highest incidence of childlessness among OECD countries. In Singapore, 28% of women born in 1975‑80 were childless in 2020 and in Hong Kong (China) it concerned 30% of the women born in 1979.

• Adolescent fertility rates have been falling but remain considerable on average across the Asia/Pacific region. In 2021, adolescent fertility rates ranged from as low as 0.4 births per 1 000 girls aged 15‑19 in Korea to 82.4 births per 1 000 girls aged 15‑19 in Lao PDR. Adolescent fertility rates are also substantial among Pacific Island countries and territories (51 births per 1 000 girls).

• Over the past decades, women have increased their educational attainment, from on average 7.5 years of completed education in 2005 to 9.1 years in 2022 across the Asia/Pacific region. This has strengthened women’s labour market participation and earnings, thus increasing their opportunity cost of having (more) children (OECD, 2023[7]). However, if women are able to combine work and family life and participate in economic life on an equal footing with men, then this leads to better economic outcomes and higher fertility rates.

• Results from OECD-wide regressions found positive associations between TFRs, employment of men and women, public spending on parental leave and ECEC, and to a lesser extent financial support to households, which underlines the importance of supporting households with their challenges to combine work and family commitments.

• Indeed, across the OECD, but also in many countries in the Asia/Pacific region, policy has become more focused on supporting the reconciliation of parental work and family commitments as this reduces the costs of children to parents and sustains family incomes, which theory predicts will support fertility rates (Becker, 1960[2]). In 2022, public social protection expenditure on children amounted to 0.9% of GDP across the Asia/Pacific region on average, compared to 2.1% of GDP across the OECD. Australia, Japan and New Zealand spent about 1.9 to 2.5% of GDP on family benefits while this in Korea this was 1.6% of GDP. Public spending on family benefits was highest in Mongolia at 4.6% of GDP with 2.6% of GDP spent on the universal cash benefit – “Child Money Program” and an estimated 1.4% of GDP on ECEC in 2022.

• Without accompanying measures, Baby Bonuses and child allowances frequently only have a transitory and/or small effect on fertility rates, and the effect is likely to be largest those with low-income. The introduction in 2005 and reintroduction in 2012 of the comprehensive Child Money Program reduced child poverty rates in Mongolia, contributed to an upswing in the fertility rate until in 2015 to 3 children per women, though the TFR had fallen to 2.7 by 2022. Cash programmes in OECD countries – generally more affluent than Mongolia, often generate no discernible effects on fertility trends. For example, the universal Australian Baby Bonus that existed between 2004 and 2014 had a small but statistically significant impact on the fertility rate, and were with the biggest effects among immigrant women of low educational attainment.

• If women must choose between work and family, then some will choose (more) children and thus limit their labour force participation while others will choose paid work and thus limit fertility rates. In the absence of work-life balance options, increased female labour participation then leads to declining fertility rates. To some extent this is playing out in East Asia. Japan and Korea are increasing their investment in work/life balance policies, but workplace cultures continue to impose barriers to having children.

• Direct costs of children are also important, and the OECD-wide regressions also found a clear negative association between TFRs and housing costs, and the unemployment rate as an indicator of labour market conditions. Concerns about the cost of housing have come to the fore as a barrier to having (more) children, as the increase in housing cost since the late 1990s has been considerable in most OECD countries (OECD, 2023[8]), but is also a concern in, for example, China. Private education costs can also establish a barrier to having (more) children – as in Korea.

• The OECD-wide regressions also found that much of the variation in fertility trends is not explained by employment participation, policy factors and direct housing costs. This result could point to a growing role of perceived insecurity, as well as societal attitudes and norms. For example, 60% of Koreans, 70% of Australians and 80% of Japanese survey respondents think that their children will be financially worse off than their parents. Climate concerns are considerable in the south-west pacific region where amongst other issues, rising sea-levels threaten complete island populations. However, it is unclear, whether these concerns have exerted downward pressure on fertility rates in the past.

• Attitudes towards parenthood appear to be changing, albeit more slowly than across the OECD. Endorsement of conventional family patterns and gender roles has declined, but they remain more prevalent than in most other OECD countries. For example, having children outside marriage remains uncommon in East Asia, but there is an increasing number of young people who support gender-egalitarian values, especially among those with high levels of educational attainment.

• At the same time, the normative demands on what it means to be a “good” parent have grown in importance, and the changing balance in costs and benefits of having a child in for example, urban China, Japan and Korea – both financial and non-financial, affects the choice to have children and how many. As the reconciliation of work and family life is so hard to achieve, many young people in East Asia have fewer, if any, children today than in the past.

• Past population trends and projections on future outcomes suggest that the face of future societies will change considerably, although the degree of change is subject to cross-national variation. In Australia and New Zealand, the number of children is projected to be rather similar in 2060 compared to 2020, but in many other countries, the proportion of children is projected to decline. In all countries the share of the elderly population will increase from now to 2060. In Japan, the size of all 5‑year age‑groups is projected to decline expect for those over 79 years of age, and China, Korea and Thailand are not far behind in terms of ageing dynamics. Mongolia is projected to remain a “young country” for many years to come.

• Persistently low fertility rates and population ageing have fuelled the debate about a more pro-natalist stance of family policy in some OECD and Asian countries. Policy stances have changed from “population control” to “overcoming low fertility”. At present India and Indonesia can be said to have policies that aim to control the population size, while in China, Japan and Korea policy aims to increase fertility rates. Mongolia is remarkable in having a TFR well above replacement level and policy aims to increase this to 3.5 children per woman by 2050.

• The best approach for countries that are concerned about fertility rates remains to promote more gender equality and fairer sharing of work and childrearing. This involves providing family policies that help the reconciliation of work and family life, but policy must also have a greater focus on the costs of children, especially housing costs.

• Countries, especially in East Asia, would also be prudent to consider how to adapt for a “lower-fertility future”, if only because any increase in fertility rates today will only result in a larger working-age population 20 years down the line. Such a policy – that goes beyond family policy and the scope of this Chapter, could involve immigration, bringing more under-represented groups into the labour force (e.g. women, youth, older workers) and taking measures to enhance their productivity to allay the economic and fiscal implications of a potentially shrinking workforce.

Fewer and later births in almost all countries across the Asia/Pacific region

Declining fertility rates across the Asia/Pacific region over the past five decades

Across both the Asia/Pacific region and OECD area, fertility rate trends differ markedly across countries, but the general trend is that fertility rates declined in higher-income countries before they fell in many medium and/or low-income countries. In 1970, the average Total Fertility Rate (TFR – see the notes to Figure 1.1 for the definition) across OECD countries had already been on a downward trend, and stood at 2.8 children per woman, while in Japan it stood at the replacement level of approximately 2.1 children per woman, which would keep the size of the population constant in the absence of migration (see the notes to Figure 1.1). By contrast, in all other countries of the Asia/Pacific region, TFRs were above replacement rate level in 1970 and were highest at 7 children per woman or more in the Maldives, Mongolia, Samoa and Tajikistan. The average TFR across the Asia/Pacific region stood at 5.2 children per woman and countries with a TFR above 5 children per woman in 1970 included China, India, Indonesia and Thailand.

Figure 1.1. Fertility rates have halved over the past five decades in many Asian/Pacific countries

Total fertility rates in 1970 and 2022 (or latest year)

Note: The total fertility rate in a specific year is defined as the total number of children that would be born to each woman if she were to live to the end of her child-bearing years and give birth to children in alignment with the prevailing age‑specific fertility rates. It is calculated by totalling the age‑specific fertility rates as defined over five‑year intervals. OECD averages are unweighted averages. The OECD average for the TFR data includes all 38 OECD countries. The average for the Asia/Pacific region includes all countries in the figure, i.e. it does not include the observations for Hong Kong (China) and Macau (China). The replacement fertility rate corresponds to the average number of children per woman necessary for each generation to sustain population levels. It is approximate around 2.1 children per woman, but it would be higher in countries with elevated child mortality where children are less likely to live to their reproductive years and have their own children. By the same token, the replacement rate can be below 2.1 children per woman if migration inflows sustain the population (see the discussion on population dynamics below).

Source: OECD (2024), Indicator SF2.1 Fertility rates, www.oecd.org/els/family/database.htm and World Bank (2024), World Development Indicators, http://data.worldbank.org/indicator.

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The situation in 2022 was very different (Figure 1.1). The TFR across Asia/Pacific had fallen to replacement level, and in Hong Kong (China) and Korea the TFR had fallen to 0.7 to 0.8 children per woman. At almost four children per woman the TFR remained highest in Samoa, while it stood at 3.0 and over in Kazakhstan, Pakistan, Papua New Guinea, Tajikistan, Timor-Leste, Tonga and Uzbekistan. By 2022, the TFR across the OECD on average had fallen to an all-time low of 1.5 children per woman (OECD, 2024[6]).

A more detailed look at fertility trends for a selected number of countries provides a better picture of cross-national trend differences (Figure 1.2). By 1990, the TFR across the OECD on average had already fallen to just below 2 children per woman, and it continued to fall throughout the 1990s to 1.65 children per woman in 2002. This decline was caused in part by a postponement of first births, which contributed to a TFR-fertility increase in the 2000s at a peak of 1.76 in 2008 (Burkimsher, 2015[9]; Beaujouan and Berghammer, 2019[10]). The following years saw a new decline on the TFR, falling to an all-time low of 1.5 in 2022 on average across the OECD.

Figure 1.2. Fertility rates have trended downwards in Asia/Pacific since 1990, but not continuously

Total fertility rate (left axis) 1990 to 2022, OECD average*

Note: See notes to Figure 1.1.

Source: OECD (2024), Indicator SF2.1 Fertility rates, www.oecd.org/els/family/database.htm and World Bank (2024), World Development Indicators, http://data.worldbank.org/indicator.

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Among the Asian/Pacific OECD countries, the TFRs in Australia and New Zealand stood at 1.63 and 1.66 respectively, and fertility rates were just above the OECD average for most of the 1990‑2022 period. Over this period, the TFR in Japan has been consistently below the OECD average and stood at 1.26 children per woman in 2022. The TFR in Korea has also been below the OECD average since 1990, but in the early 2010s, it commenced its strong downward trend towards the low level of 0.78 in 2022. At 0.70 in 2022, only Hong Kong (China) had a lower TFR than Korea.

The TFR in China edged up after 2001 to 1.81 children per woman in 2017, but since then declined rapidly to 1.18 in 2022. In Thailand the TFR also fell markedly since 2015, as in Indonesia. Fertility rates in India have been consistently downward since 1990 and fell from almost 6 children per women in that year, to two children per women in 2022. The one country in Figure 1.2 which bucks the trend to some extent is Mongolia. From its low point of 2 children per women in 2004 the TFR peaked at 3 children per woman in 2015, it has fallen since to 2.7 in 2022.

The COVID‑19 pandemic led to fluctuations in births and fertility in many countries. In 2019 and in 2020, when the pandemic started, TFRs declined in more than two‑thirds of OECD countries, while in 2021, TFRs increased in two‑thirds of OECD countries, although the 2020 base of comparison was rather low ( (OECD, 2024[11]), Indicator SF2.1). Lockdowns at the onset of the pandemic significantly reduced fertility in many European countries in early 2021, but this was followed by a quick rebound in fertility by the end of the first quarter of 2021 (Pomar et al., 2022[12]). In a study based on 37 mostly OECD countries, Sobotka et al. (2023[13]) confirm this pattern but also show, that, unexpectedly, births declined again in January 2022 with underlying conceptions in spring 2021 when the pandemic measures were mostly eased out and vaccination was gaining momentum. This may be due to a related postponement of births as the vaccination campaign was rolled out, a general return to work and pre‑pandemic fertility behaviour (Sobotka et al., 2023[13]). For Korea, there is little evidence that the pandemic directly affected the number of births up to and including 2021, however, the pandemic did lead to a reduction in marriages which is likely to have a significant impact on fertility in subsequent years (Jung and Lee, 2023[14]). As for China, different studies show that COVID‑19 has lowered the fertility intentions of Chinese women of childbearing age (Chen et al., 2022[15]) and regarding third children (Li and Qian, 2023[16]).

Childlessness and the birth order of children

The fall in TFRs is related to women having fewer children and/or none at all. Comprehensive data for the Asia/Pacific countries is missing but across the OECD childlessness has been on the rise. The increase in Australia was limited, childlessness among women aged 45‑49 increased from 14.4% in 2006 to 16.4% in 2021 (AIFS, 2024[17]). The increase was much more pronounced in Italy, Spain and Japan, where childlessness among women born 1955 and 1975 (women aged 49 in 2024), more than doubled in Italy and Spain (around 24%) and was highest in Japan at 28% of women born in 1975 (OECD, 2024[6]). In Singapore, 28% of women born in 1975‑80 were childless in 2020 and childlessness is higher still in Hong Kong (China), where it peaked at 35% among women born in 1971, and then started to fall, reaching 30% among those born in 1979 (Sobotka, 2021[18]). From the data on cohort fertility, it is not possible to discern whether definite childlessness is voluntary or involuntary.

There are no comprehensive data on family size and birth order across the Asia/Pacific region. On average across the OECD, there was little change in the birth-order of children between 1980 and 2022 (OECD, 2024[6]). In 2022, the share of first-borns was about 45% of children born, the share of second children was around 35%, and the share of third or higher order children was about 20%. However, the overall stability between 1980 and 2022 masks important country differences in “fertility dynamics”. For example, in Korea in 2022, the share of third (and higher) order children was only 8%, while in Japan it was 17%. At 28% the incidence of childlessness among women in Japan is very high, while it was only 13% among women in Korea who were born in 1975. This suggests that once women in Japan decide to have children, they are much more likely to have two or three (or more) children than women in Korea. It also helps to explain why at 1.3 the TFR in Japan in 2022 is above that for Korea (0.8) in 2022 (OECD, 2024[6])).

The age of women at childbirth

At the same time as fertility rates fell in OECD countries, the mean age at which mothers have children increased across the OECD (OECD, 2024[6]). As fertility rates across the Asia/Pacific started to decline later than in OECD countries, available data suggests that the increase in mean ages of mothers at childbirth has been moderate so far (United Nations, 2022[19]). Indeed, across Oceania – the area with the highest fertility rates in the Asia/Pacific region, fertility rates remain highest among women in the 20‑24 age‑group (Sorchik et al, 2019[20]).

The mean age at which mothers have their first child on average across the OECD has increased by 3 years to 29.4 years of age over the 2000‑21 period, and the highest mean age of mothers at first childbirth is recorded for Korea at 33 years of age (Figure 1.3). Across the Asia/Pacific region, the mean age at first childbirth is almost five years below the OECD average. The trend towards postponement of births across the OECD and in more affluent Asian countries potentially has negative consequences for overall fertility. As young people wait longer to have children, they may shift family formation to a point where fecundity problems – that is the ability to have children – could interfere with the realisation of desired fertility. Advances in reproductive medicine can, at least in part, allow women to have children at older ages (Box 1.1).

Figure 1.3. The mean age of women at first childbirth in the Asia/Pacific region is almost five years below the OECD average

Mean age of women at first childbirth, 2022 or nearest year^{1, 2}

Notes: 1) Data for 2022 refer to 2021 for Australia; 2019 for Amenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Turkmenistan and Uzbekistan; 2017 for Indonesia and Tajikistan; 2016 for Nepal, Sri Lanka and Timor-Leste; 2015 for Singapore; 2021/22 for Cambodia; 2019/21 for India; 2017/18 for Bangladesh and Pakistan; 2016/18 for Papua New Guinea; and 2016/17 for the Maldives.

2) For Georgia, data does not cover Abkhazia and South Ossetia.

a. Counties marked with an ‘‘(a)’’ refer to the median age at first birth rather instead of the mean age at first birth. For Sri Lanka, data represents median age at first birth among women 30‑34. For Cambodia, India, Indonesia, Nepal, the Maldives, Pakistan, Papua New Guinea and Timor-Leste, data represents the median age at first birth among women 25‑49. For Bangladesh, data represents median age at first birth among women 20‑49. For Singapore, no specific age cohort is specified for the median age at first birth.

Source: OECD (2024), “Figure 1.1. Simultaneous trends of fewer and later births”, Society at a Glance 2024: OECD Social Indicators, https://doi.org/10.1787/918d8db3-en, OECD Korea Policy Centre (2024), Family Database in the Asia-Pacific Region, https://oecdkorea.org/eng/product/familyDatabase_view.asp?BRDNUM=1985, and the World Factbook, CIA: www.cia.gov/the-world-factbook/field/mothers-mean-age-at-first-birth/.

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Box 1.1. Medical advances in reproductive medicine mean more births are intentional

The increasing postponement of births could result in some men and women no longer being able to have the number of children they intended. This is likely to hold particularly for higher-order births rather than first births: when people start their families later in life, they are more likely to experience pregnancy-related health issues (Bhasin et al., 2019[21]). Infertility rates are rising, and while women have previously predominantly borne its stigma, both men and women are equally likely to contribute to a couple’s infertility (Turner et al., 2020[22]). With decreasing sperm counts and testosterone concentrations as well as increasing prevalence of testicular cancer and puberty disorders (Skakkebaek et al., 2019[23]), male reproductive health has deteriorated over recent decades (Huang et al., 2023[24]). However, there is some ambiguity in the literature as Borumandnia et al., (2022[25]) found that primary male infertility declined in high income countries and increased in lower income countries. This finding may be related to a decline in TFRs in high-income countries that masks infertility – i.e. many cases of infertility remain unknown, while in low-income countries dietary insufficiencies and environmental and work-related toxicants play a role, while access to infertility treatment is limited.

Medical advances – including contraceptive methods, fertility treatments and assistive reproductive technology (ART) – mean that men and women have more control over their childbearing choices today than they had in the past. Such increased autonomy has had a direct impact on fertility trends, particularly through a decline in unplanned childbirths and a lower number of adolescent pregnancies (Tridenti and Vezzani, 2022[26]; Lindberg, Santelli and Desai, 2018[27]). At the same time, the availability of fertility treatments and ART also give young people the feeling that they can postpone the choice to have children. In Israel, for example, ART is found to have contributed to a delay in marriage and an increase of the age at which women give birth (Gershoni and Low, 2021[28]).

On the other hand, fertility treatments and ART have given couples exposed to fecundity issues a chance to have (more) children. The share of births that involve some form of ART has steadily increased in many countries (Doepke et al., 2022[29]), making up 9.2% of all live births in Denmark in 2019, a leading ART country (Sundhedsdatastyrelsen, 2021[30]).

In Asian OECD countries, there has been a similar trend. For example, in Japan, the share of births involving ART has increased more than fivefold over the past 14 years from 1.7% of all live births in 2007 to 8.6% in 2021 (Katagiri et al., 2023[31]). Australia and New Zealand have also seen a gradual rise in the share of births from ART, reaching 5.4% and 3.6% in 2021 respectively (Newman JE, 2023[32]). In 2017, Korea began covering infertility treatment through its National Health Insurance, causing the number of ART treatments to increase: in 2018 the share of births involving ART was 2.8%, it was 10.6% of all births in 2020 (YoonAng, 2021[33]). In Indonesia, Thailand and Viet Nam ART services are available but are scarce and mostly located in urban areas, and are fully paid out-of-pocket, while public financial supports are available in Japan, Korea and Singapore (The Economist, 2023[34]).

Adolescent fertility rates are falling

One of the factors tempering the increase in the mean age of women at childbirth are the relatively high adolescent fertility rates in the region, even though they are falling (Figure 1.4). In 2022, adolescent fertility rates ranged from as low as 0.4 births per 1 000 girls aged 15‑19 in Korea to 82.4 births per 1 000 girls aged 15‑19 in Lao PDR. Adolescent fertility rates are also substantial among Pacific Island countries and territories (51 births per 1 000 girls), and Southeast Asia (43 births per 1 000 girls), and South Asia (26 births per 1 000 girls) (UNFPA, 2021[35]).

Figure 1.4. Adolescent fertility rates are falling but remain substantial in the Asia/Pacific region

Adolescent fertility rate – births per 1 000 girls, 15‑19 year‑olds, 1990 and 2022 or latest available year

Note: Data for 2022 for Australia, Japan, Korea and the OECD average refer to 2021.

Source: World Health Organization (2024), Maternal, newborn, child and adolescent health and ageing database, https://platform.who.int/data/maternal-newborn-child-adolescent-ageing/indicator-explorer-new; For OECD countries: OECD Family Database (2024), https://www.oecd.org/en/data/datasets/oecd-family-database.html.

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However, in almost all cases, with increasing access to contraceptives, adolescent fertility rates are considerably lower than they were in 1995 and much lower than in 1970. For example, in Indonesia, the adolescent fertility rate fell from 174.8 births per 1 000 girls aged 15‑19 in 1990 to 26.6 births per 1 000 in 1995 and has since declined to 33.9 births per 1 000 girls aged 15‑19 in 2021. In Japan, adolescent fertility rates have remained broadly stable at very low levels since 1970 and, as in Korea and Singapore adolescent fertility rates are below 2.5 births per 1 000 girls aged 15‑19.

Marriage and its association with fertility

Over the past 20 years, the age at which women have their first childbirth across the OECD on average has increased from 28.5 to 30.8 years of age. Over the same period the mean age of first marriage for women increased even faster: from 27.4 to 31.5 years of age. The mean age at first marriage has risen above the mean age at first childbirth, as many people in the OECD now get married after having children or have children without getting married. Across the OECD on average, just over 40% of the children born in 2020 were born outside marriage, and in 14 of 38 OECD countries it concerned the majority of children born that year (see (OECD, 2024[11]), SF2.4 Share of births outside of marriage).

The situation in many Asian countries is rather different as marriage rates are generally higher and the share of births outside marriage lower. Marriage rates in non-OECD countries in Asia have declined over past decades, but generally are between 6 and 8 marriages per 1 000 people. By contrast, across the OECD on average marriage rates are around 4 marriages per 1 000 people, and are below that in Korea, Australia and New Zealand (Figure 1.5)

The relatively low marriage rates in Australia and New Zealand do not have much of a bearing on fertility trends as close to 40% of children in Australia are born outside of marriage whereas this is close to 50% in New Zealand (Figure 1.6). However, in Malaysia and Mongolia, and particularly in Japan, Korea and Singapore, births outside marriage are uncommon (OECD Korea Policy Centre, 2024[36]). In these countries marriage remains strongly associated with births, and the steep decline in the marriage rate in Korea since 1980 has contributed to the fall of the TFR in Korea, while childlessness within marriage is also increasing (Hwang, 2023[37]).

Figure 1.5. Marriage rates in Asia are higher than across the OECD

Crude marriage rate – marriages per 1 000 people, 1980, 2000 and 2021 or latest available year

Source: OECD Family Database (2024), https://www.oecd.org/en/data/datasets/oecd-family-database.html, and OECD Korea Policy Centre Family Database in the Asia-Pacific Region (2023), https://oecdkorea.org/eng/product/familyDatabase_view.asp?BRDNUM=1985, “SF3.1 Marriage and divorce rates”.

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Figure 1.6. The share of births outside marriage is relatively high across the OECD

Share of births outside of marriage1 (a), 1970, 1995 and 2022 or latest available year2

1. Births where the child’s parents are not registered as married to each other (or, for New Zealand only, in a civil union with each other) at the time of the birth.

2. 2022 data refer to 2021 for Australia, Japan and the OECD average; 2017 for Singapore; and 2015 for Malaysia.

Source: OECD Family Database (2024), https://www.oecd.org/en/data/datasets/oecd-family-database.html, and OECD Korea Policy Centre Family Database in the Asia-Pacific Region (2023), https://oecdkorea.org/eng/product/familyDatabase_view.asp?BRDNUM=1985, “SF2.4 Share of births outside of marriage”.

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The decline in marriage rates contributes to the increase in “singlehood”. For example, the rate of singlehood among Korean women in their thirties, stood at 33.6% in 2020, up from 4.1% in 1990 (Hwang et al., 2023[38]). In 2015, one in four women and one in three men in their thirties in Japan were single. Moreover, half of the singles aged 18‑39, reported that they had no interest in romantic relationships with someone of a different sex (Ghaznavi et al., 2022[39]). Among single men and women in Japan, those who reported no interest in heterosexual romantic relationships were more likely to have lower income and educational attainment levels and were more likely not to be in regular employment (Ghaznavi et al., 2020[40]).

Population dynamics

Population dynamics vary considerable across countries. In Japan the number of births has been declining since 1973 and has been below the number of deaths since 2005, and with limited immigration, the population has been declining since 2009. In Korea, the population started to decline in 2020, and the population in China has declined since 2021 (Reuters, 2024[41]). In Thailand, the gap between the number of births and death is becoming small. COVID‑19 contributed to the sharp increase in the number of deaths in India and Indonesia in 2020 and 2021 (Annex Figure 1.A.1). In Australia and New Zealand, the number of births remain well above the number of deaths, as populations increase with the influx of immigrants that has taken place over the years, although subject to considerable annual variation (Annex Figure 1.A.1).

Population projections

TFRs remain high and well above replacement levels in some parts of the world, and more than half of the projected increase in global population up to 2050 will be concentrated in just eight countries: the Democratic Republic of the Congo, Egypt, Ethiopia, India – which surpassed China as the world’s most populous country in 2023 (UN DESA, 2023[42]), Nigeria, Pakistan, the Philippines and Tanzania. Nevertheless, even high-fertility countries are experiencing declines in TFRs and the most recent global fertility rate projections estimate the global TFR to fall from 2.21 in 2022 to 1.83 in 2050 and 1.59 in 2100 (Bhattacharjee et al., 2024[1]). This long-term trend towards having fewer children reflects economic development, noticeable improvements in reproductive health as well as women’s economic and social empowerment (Skirbekk, 2022[43]).

Population growth across the OECD and in many Asian countries is projected to remain limited in future, and ensuing demographic change will have substantial wider policy implications (Box 1.2). The projections for Asia/Pacific vary across regions (and countries) but hold a path to convergence at low fertility levels. Across global regions the TFR is currently highest in Oceania at 4.0 children per woman, which is projected to stabilise around 1.7 by 2100. On average across East Asia, South-east Asia, Australia and New Zealand, the TFR is projected to be close to 1.3 children per woman by 2100, and in South Asia (including India and Nepal), a TFR of 1.1 is projected for 2100 – though this estimate has a large margin of error. In high income Asia/ Pacific countries (including Japan and Korea), the TFR is projected to stabilise just above 1.1 children per woman (Bhattacharjee et al., 2024[1]).

Box 1.2. Wider policy implications of demographic change

The downward trend in fertility rates and births coincides with increased life expectancy across the OECD and the Asia /Pacific region (OECD, 2023[44]; OECD/WHO, 2022[45]). Living longer is generally good news for the individuals involved, but in conjunction with low-fertility rates it will result in substantially older populations in the future along with a declining share of the working-age population. Population ageing will result in stronger fiscal pressures as government expenditures increase (e.g. on pensions, health services and services for the elderly) along with decreasing public revenue with shrinking working-age populations (for OECD countries, see (Guillemette and Turner, 2021[46])).

With the shrinking relative size of the working-age population, there is more room for immigration (OECD, 2023[47]) and further scope for a better integration of women in the labour force. Gains in educational attainment among young men and women can come with positive spill-over effects on economic productivity. Greater female labour force participation can spur on economic growth across the OECD (Fluchtmann, Keese and Adema, 2024[48]) and leading to output gains of 10‑15% in Europe, Central Asia and East Asia Pacific (Ostry et al., 2018[49]). In addition, longer working lives – for example by raising effective retirement ages along with future increases in life expectancy – could reduce imminent pressures on pension systems.

Past population trends and projections on future outcomes suggest that the face of future societies will change considerably, although the degree of change is subject to cross-national variation (Figure 1.7) In Australia and New Zealand, the number of children is projected to be rather similar in 2060 compared to 2020. But in all other countries, the number of children is projected to decline, although the decline in Mongolia is to start only around 2050. In all countries the share of the elderly population will increase from now to 2060, with a feminisation of older ages. In Japan this is because the size of all 5‑year age‑groups are projected to decline expect for those over 79 years of age. China, Korea and Thailand are not far behind as only the age‑groups for those over 65 years of age are projected to increase. The other countries will remain “younger” as sizes of age‑groups will increase from age 35 or 40. Mongolia is projected to remain a “young country” for many years to come.

Figure 1.7. Population ageing is widespread, but Mongolia’s population will remain young for many years to come

Population by age group and gender, in 2020 and 2060

 

Source: United Nations (2022), World Population Prospects: 2022 Revision, Washington DC, http://esa.un.org/unpd/wpp.

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The conditions for family formation and parenthood have changed

In 1960, Gary Becker published the first and arguably one of the most influential articles on the relationship between economics and fertility (Doepke et al., 2022[29]). In this work he argues: “... For most parents, children are a source of psychic income or satisfaction...” (Becker, 1960[2]). Becker’s economic approach of fertility also postulates that “...children would be considered a consumption good.... an increase in income or a decline in the cost of children would affect both the quantity and quality (expense) of children, usually increasing both. An increase in contraceptive knowledge would also affect both but would increase quality while decreasing quantity....” (Becker, 1960[2]).

Over the years, the increase in contraceptive use has contributed to a reduction in unplanned births and decline in fertility rates (UN DESA, 2020[50]), and while educational attainment, earnings and incomes increased across the Asia/Pacific region and the OECD, total fertility rates declined.

Following Becker’s approach, this suggests that the direct and/or indirect costs of children have increased relatively strongly. Such costs include direct costs like education or housing, but also opportunity costs to spending time away from work to be with one’s children, and these opportunity costs increase with earnings.

Comprehensive cross-national data on variables reflecting policy variables and/or the cost of education and housing or policy variables regarding family supports is not available for the Asia/Pacific region. Box 1.3 summarises results from an OECD wide study found that fertility trends are affected by men’s and women’s employment, public family policies, the cost of housing, and labour market insecurity (Fluchtmann, van Veen and Adema, 2023[5]). However, much of the variation in fertility trends is not explained, which could point to an important role of perceived insecurity, and societal attitudes and norms, issues that are also addressed below, with findings from the literature, where possible with a perspective on Asia/Pacific countries.

Both men’s and women’s employment are positively associated with the TFR across the OECD on average

Fertility choices can critically hinge on economic factors, determining whether (prospective) parents can afford (another) child(ren). Individual labour market situations are an important determinant for fertility behaviour. This is because it helps determine whether adults have the necessary means to afford the direct costs of parenthood, and it also affects the opportunity costs of having children, as becoming a parent often comes with career interruptions and changes in working time, especially for women (Adema, Fluchtmann and Patrini, 2023[51]). Cross-national regressions do not reflect the impact of individual (or couple’s) labour market situations on fertility choices but show that aggregate labour market outcomes have an important bearing on fertility outcomes. In fact, labour market variables explain more of the variation in fertility outcomes than the public policy factors discussed below (Fluchtmann, van Veen and Adema, 2023[5]).

Box 1.3. OECD-wide evidence on the association between fertility rates, labour market outcomes, public policy and housing costs

Employment participation of men and women is significantly and positively associated with TFRs (Figure 1.8, Panel A), a finding that is supported by the literature (Doepke et al., 2022[29]; Oshio, 2019[52]). Furthermore, the coefficient estimate on women’s employment rates is more than twice as large as the one on men’s employment, suggesting that women’s employment is a particularly important driver of fertility outcomes. This was not always so. Fluchtmann, van Veen and Adema (2023[5]) showed that while there was a clear negative relationship in the 1970s, since the 1990s women’s employment is positively associated with TFRs. Figure 1.8, Panel A, also suggests that poor labour market conditions have a negative effect on fertility choices, but the regressions do not find evidence for a statistically significant link between part time or full-time working hours and fertility.

Results from OECD-wide regressions on the impact of public policies on fertility rates are presented in (Figure 1.8, Panel B). The analysis found associations between TFRs, public spending on parental leave and ECEC, and to a lesser extent with the duration of paid leave available to mothers and general financial support to households with children. The regressions also found a clear negative association between the increase of private expenditure on housing and fertility rates.

Figure 1.8. Summary results of OECD-wide regression on drivers of fertility trends

Note: These are summary results of an OECD-wide two‑way fixed-effects regression with clustered standard errors, 2002 to 2019. Mindful of the statistical limitations and the relatively small sample size, the resulting estimates should be interpreted as a simple association between outcomes/policies in a specific country and its respective fertility rate; they do not provide evidence of a causal relationship with fertility. All specifications are a two‑way fixed-effects model with linear country time trends and controls for average years of schooling and log GDP. It is estimated over the period 2002 to 2019 using country-level data from Austria, Canada, Czechia, Denmark, Finland, Germany, Hungary, Italy, Korea, the Netherlands, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, the United Kingdom and the United States. The standard errors are heteroskedasticity- and panel-corrected (for fixed effects models). ***, ** and * represent significance at 1%, 5% and 10% level, respectively. “...” indicates insignificant estimates (less than at the 10% level). “+” stands for a positive sign of a significant point estimate, and “‑” stands for a negative sign.

Source: Fluchtmann, J., V. van Veen and W. Adema (2023[5]), “Fertility, employment and family policy, A cross-country panel analysis”, https://doi.org/10.1787/326844f0‑en, Tables 4 and 5 for the main baseline regressions and Annex Tables 5.B.9 and 5.B.10 for the supplementary regression results.

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The link between educational attainment and fertility has changed for women

Across the Asia/Pacific region on average, adults have had about 9.5 years of schooling (Figure 1.9). Educational attainment is highest in Georgia, Kazakhstan and among OECD countries in the region at over 12 years of schooling or more, while it is lowest in Cambodia, Papua New Guinea, Nepal and Pakistan at 5 years of schooling or less. Over past decades, men’s and women’s average years of schooling and their educational attainment have increased substantially (Barro and Lee, 2013[53]; OECD, 2023[54]); over the 2005‑22 period the average years of schooling across the Asia/Pacific region increased by almost 2 years (Figure 4 10).

Among OECD countries until the 1990s, the higher women’s level of education, the lower was the likelihood of them giving birth, largely because higher education and earnings increased the opportunity cost to childbirth, as evident through strong motherhood penalties on earnings (Kleven et al., 2019[55]; OECD, 2022[56]). These opportunity costs were high because combining work and raising children was generally not possible. However, increasing public and private work-life balance supports have reduced the opportunity costs to having children, and in some OECD countries (e.g. Denmark, Norway and Sweden), higher-educated women are now more likely than lower-educated women to have children (Ciganda, Lorenti and Dommermuth, 2021[57])).

Patterns appear different for the Asia/Pacific region. For Australia there is evidence of convergence in childlessness rates across different levels of education, but the gap in fertility rates between education groups continue to increase across the 1952‑56 to the 1977‑81 birth cohorts (Gray and Lazzari, 2023[58]). Among East Asian economies (Chinese Taipei, Hong Kong (China), Japan and Korea), with more traditional attitudes on gender roles, more educated women married at a much lower rate than less educated ones, and gaps increased over time (Bertrand et al., 2020[59]). Increasing “singleness” among college‑educated women contributes to a decline in fertility for this group with out-of-marriage births being uncommon in East Asia.

As in many other countries, for men, the likelihood of becoming a father increases with the level of education in Japan (Ghaznavi et al., 2022[39]). This effect mainly occurs because men with higher educational attainment are more likely to enter a stable partnership than men with low levels of education who are more likely to face difficulties in the “marriage market” (Trimarchi and Van Bavel, 2017[60]).

Figure 1.9. On average across the Asia/Pacific region, adults have had about 9.5 years of schooling

Mean duration of schooling, people aged 25 and older, 2022, in years

Note: The average for the Asia/Pacific region includes all countries in the figure, i.e. it does not include the observation for Hong Kong (China).

Source: UNDP (2024), Human Development Index Report 2023‑24, https://hdr.undp.org/sites/default/files/2023-24_HDR/HDR23-24_Statistical_Annex_HDI_Table.xlsx.

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The effect of women’s incomes on fertility depends on national contexts

Higher wages and incomes lead to more household resources and “more consumption of children”, i.e. more children and/or spending more time and money per child (Becker, 1960[2]). However, higher wages also increase the opportunity cost of childbirth, particularly among women, assuming they shoulder the majority of childcare over the early years after birth – which is indeed very often the case. But higher incomes can contribute to higher fertility levels, provided combining work and family life is a realistic option. Work-life balance supports (see the policy section below) help explain the evidence on the positive link between women’s earnings and fertility in Denmark (Berninger, 2013[61]) and Norway (Hart, 2015[62]), where dual-earner households have long been the norm.

In 1980, there was still a clear negative relationship between income per capita and fertility across the OECD, with the highest fertility rates in countries with relatively low GDP per capita (e.g. Portugal and Spain), but by the year 2000, this relationship had reversed: richer OECD economies now have slightly higher fertility rates than poorer ones (Doepke et al., 2022[29]). Ryu and Inoue (2023[63]) applied this framework to Japan by considering variation among 47 prefectures: Gross Regional Product (GRP) and fertility still have a negative relationship, but the negative relationship has weakened since the 1960s, however, areas with higher labour force participation rates by mothers, and more dual-earner families had higher fertility rates. Similarly, (Chung and Lee, 2022[64]) found with their analysis of annual household data over the 1999‑2016 period for Korea that married women’s economic power relates positively to childbirth for the period after 2006. They also found the higher birth likelihood among top income quartile women was largely attributed to their better accessibility to maternity protection benefits.

It is not just about having a job, but the stability of that job is important too

While employment is positively associated with fertility rates, labour market dualism and the associated poor labour market conditions for the “outsiders” reduce the likelihood of having (more) children (Seltzer, 2019[65]; Vignoli, Tocchioni and Mattei, 2020[66]; Yoo., 2022[67]). Labour market insecurities increased after the 2008 financial crisis, and affect younger workers in particular through higher unemployment risks and increased reliance on temporary and platform work (Chung, Bekker and Houwing, 2012[68]; Causa, Luu and Abendschein, 2021[69]). A survey among Australians found that job security and the direct costs of raising children are the two most important factors in people’s decisions about fertility (Gray et al., 2022[70])

Both Japanese and Korean Labour markets are characterised by a sharp dichotomy in employment conditions of regular and non-regular employees. Regular employees receive employer-provided training and benefits, and their compensation is strongly linked to age and tenure. Regular employees signal their commitment to their employer and career by putting in long hours, including unpaid overtime and taking little leave. Non-regular workers often are on fixed term contracts, with limited access to benefits and training,

The share of non-regular workers is increasing in both Japan and Korea, and concern many young workers, and women are more likely to be in non-regular work than men (Hwang et al., 2023[38]; Nishikitani, Inoue and Tsurugano, 2018[71]; OECD, 2024[72]; OECD, 2024[73]). Earnings of non-regular workers are often much lower than for regular workers. For, example, in Korea on average regular workers are paid twice as much as non-regular workers (Hwang et al., 2023[38]). Regular workers are more likely than non-regular workers to be able to meet the cost of children. This has a bearing on fertility intentions: the desired number of children is largest for regularly employed men, around 1.85 children compared to around 1.25 for non-regularly employed men (Nishikitani, Inoue and Tsurugano, 2018[71]). Both men and women in Japan who consistently are in non-regular employment are less likely to marry than regular workers (Mugiyama, 2017[74]). In Korea the likelihood of transitioning from non-regular employment to regular employment has diminished over the 2006‑21 period (Hwang et al., 2023[38]).

Furthermore, the dichotomy between regular and non-regular workers is associated with gender differences in employment conditions and pay, as women are over-represented among non-regular workers. This contributes to Korea having the widest gender pay gap in the OECD; at the median for full-time workers, it amounted to 31.2% while this stood at 21.3% (OECD, 2024[75]). As it is very difficult to return to regular employment after a career break, there are high opportunity cost for women in regular employment in Japan and Korea (OECD, 2024[73]; OECD, 2024[72]). The Australian gender pay gap fell to a record low of 11.5% in 2024, with increased pay transparency in the private sector and pay rises for Early Childhood workers among the drivers for the recent narrowing (Risse, 2024[76]). The gender pay gap is lowest in New Zealand at 8.6% in 2023, however, the pay gap has been stable since 2017 (Manatu Wahine - Ministry of Women, 2024[77]). The persistent motherhood penalty exerts a negative impact on the fertility rate, with the effect being largest in Japan and Korea compared to Australia and New Zealand.

Typical working hours can be another important factor for the timing and number of births. The international literature identifies a negative link between worked hours and fertility choices (Maralani and Stabler, 2018[78]; Liu and Hynes, 2012[79]; Cooke, 2009[80]), and excessively long working hours may even affect reproductive health itself of women (Ahn et al., 2021[81]; Gaskins et al., 2015[82]). There is some evidence for Japan that the longer women work the less likely they are to have children (Ishida et al., 2017[83]; Moribe et al., 2015[84]). Women of childbearing age in paid work for more than 45 hours per week in Korea had lower pregnancy intentions than those in paid work for 20 to 45 hours per week (Kim, 2023[85]).

Families postpone having children due to both real and perceived economic uncertainties

To a certain degree, fertility follows the ups and downs of the business cycle, most analyses generally find that birth rates react negatively to economic downturns, for example, fertility rates in Central Asia and Mongolia fell after the demise of the Soviet Union until the mid‑2000s. However, this does not always hold: for example, the Norwegian economy rebounded swiftly after the 2008‑09 economic crisis and remained one of strongest across the OECD throughout the 2010s, but all the while fertility fell to record low levels (OECD, 2023[86]).

Indeed, actual economic outcomes are not all that matter. Fertility choices are made based – at least partly – on perceived economic uncertainty and expectations of the economic outlook (Buckles, Hungerman and Lugauer, 2020[87]; Comolli and Vignoli, 2021[88]; Gatta et al., 2021[89]). For example, (Hwang et al., 2023[38]) report that perceived economic insecurity in 2022 was higher among Korean Millennials and Generation Z than their counterparts in 46 other countries, regarding both the cost of living and their future financial prospects. Koreans are also more likely to worry about job-loss than workers across the OECD (OECD, 2024[6]; 2023[90]).

Perceived and anticipated uncertainties that influence fertility choices are heavily impacted by prevailing narratives in society, including the tone in media, the experiences among friends and dinner table conversations among families. By construction, news reporting filters and simplifies complex information, and this is becoming a key factor in an increasingly globalised world. The perception of economic strength or weakness is strongly rooted in the public narratives conveyed through the media (Vignoli et al., 2021[91]).

There are justified concerns about, for example, climate change, cost of energy, food and/or housing costs (OECD, 2023[90]), and many people anticipate geo-political and socio‑economic instability and the outlook is markedly more negative over a 10‑year timeframe (WEF, 2024[92]). Sixty percent of Koreans, 70% of Australians and 80% of Japanese survey respondents think that their children will be financially worse off than their parents (Pew Research Center, 2023[93]) and (OECD, 2024[6]). Climate concerns are considerable in the south-west pacific region where amongst other issues, rising sea-levels threaten complete island populations (WMO, 2024[94]). However, it is unclear, if, and to what extent, these concerns have contributed to the declining fertility rates in the region.

Population growth can have negative effects on climate issues; along with increased consumption it strains resources and exposes more people to climate‑related events (Guzmán, 2009[95]). Dillarstone et al. (2023[96]) found that climate change concerns were typically associated with less positive attitudes towards reproduction and a desire and/or intent for fewer children or none at all – their systematic review was based on studies conducted between 2012 and 2022 in European countries, Canada, New Zealand and the United States.

Public family supports

Families remain a cornerstone of any society and modern family policy aims to support families through pursuit of a range of interdependent policy objectives (Adema, 2012[97]). These include, in no particular order:

• Combat child and family poverty.

• Promote child development and enhancing child well-being throughout the early life‑course.

• Enhance gender equality.

• Mobilise female labour supply to foster economic growth and underpin the financial sustainability of social protection systems.

• Support parents with the reconciliation of work and family responsibilities.

• Promote conditions which help adults to have the number of children they desire at the time of their choosing.

The prevailing balance of these family policy objectives varies across countries and over time.

Indeed, over the years there has been considerable change in the objectives of population policy in Asian countries. Back in the second part of the past century many Asian countries, including India and Japan (1950s), Korea (1960s), China, Indonesia and Thailand (1970s) introduced family planning policies that actively discouraged having children and contributed to the decline in fertility rates (Annex Table 1.A.1). India engaged in mass sterilisation, which in the period 1974‑79 involved 18.5 million men and 8.1 million in 1977 alone, with sterilisation measures sharply reduced after the fall of the Gandhi Government in 1977 (Gupte, 2017[98]). The one‑child policy in China introduced in the 1980s involved rewards for families with one child and punishment for families with two children including physical abuse. Sex-selective abortions were also prevalent. In addition to issues around human rights and freedom of reproduction, the policy is controversial in population terms since an important decline in the Chinese fertility rate took place in the 1970s (Feng, Cai and Gu, 2013[99]). For a detailed overview of family planning policies in the second part of the 1990s in 22 countries around the world, including Bangladesh, India, Indonesia, Korea, Malaysia, Nepal, Pakistan, the Philippines, Singapore, Sri Lanka and Thailand, see (Robinson and Ross, 2007[100]).

India and Indonesia can still be said to exercise some population control policy. But the authorities in Japan (1990s), Korea (2000s), and China (2010s) have introduced family policy packages that are focused on supporting families to have children and “counteract low-fertility” (Annex Table 1.A.1). The policy pendulum swung back and forth in Mongolia, which introduced pro-natalist policies in the 1960s, relaxed these policies in the 1980s, but since the 2000s it pursues a pro-natalist policy stance with important financial supports for families (see below) culminating in “Vision 2050” that aims to increase the TFR to 3.5 children per woman by 2050.

Family policies provide varying degrees of support for families over the early life‑course of their child(ren), which may also influence people’s choices on whether to start a family or not. Policy measures can include, among others, family leave around childbirth, ECEC services, and child benefits. Considering the often large (opportunity) costs of childbearing – for example, through reductions in disposable household income and foregone career progression (future earnings) – family supports can help make parenthood more attractive to (prospective) parents (Box 1.3). As Gauthier and Gietel-Basten (2024[101]) observe with respect to family policy: “It is in its signalling support for families to meet their reproductive aspirations in both sentiment and holistic policy intervention that, perhaps, the strongest contribution to fertility comes in.”

However, it is not just a matter of making individual supports such as child allowances or parental leave available. Ideally, such measures are designed and put in place in a coherent manner, so that parents can access a continuum of supports over the child’s life course which helps them with the reconciliation of work and family life (OECD, 2007[102]; 2011[103]; 2024[6]). Thus, when entitlement to parental runs out, ECEC should be accessible, followed by publicly supported mandatory schooling combined with Out-of-School Hours (OSH) services, child benefits and flexible workplace supports as fitting (Adema, 2006[104]). In this sense, reducing the costs of children may influence preferences on family size, but for this to occur, policy support has to be sufficiently comprehensive and consistent over time (Thévenon, 2011[105]). The notion of providing coherent support throughout to support parents overlaps with the notion of productive investment in childhood that purports to start early with investing in children, do so where it is needed most, and sustain it throughout childhood (Heckman and Masterov, 2007[106]).

In Asian/Pacific OECD countries, public spending on family benefits in 2022 was 1.6% of GDP in Korea, 1.9% of GDP in Australia, 2% in Japan and 2.5% in New Zealand, well above an estimated average of 0.9% of GDP across the Asia/Pacific region (Figure 1.10). There is, however, an important exception: spending on family benefits was at 4.6% of GDP in Mongolia in 2022, well above what OECD countries spend on family benefits – which was 2.3% on average across the OECD and highest in France, Sweden and Poland at around 3.5% of GDP.

Figure 1.10. Public spending on family benefits in the Asia/Pacific region is highest in Mongolia

Public spending on family benefits, 2023 or latest available year (% of GDP)

Notes: Public spending on family cash benefits includes spending on child allowances and paid leave as well as investment in ECEC until the age of 6, but does not include education spending. The average for the Asia/Pacific region includes all countries in the figure, i.e. it does not include the observation for Hong Kong (China). Data for Australia, Japan, Korea, Mongolia, New Zealand and the OECD average refer to 2022.

Source: preliminary data from the OECD Social Expenditure Database (SOCX); ILO (2024), ILO (2023), World Social Protection Database, https://wspdb.social-protection.org; ADB (2024), Mongolia: Developing Inclusive and Resilient Social Protection Systems in Asia and the Pacific, Technical Assistance Consultant’s Report, Project Number: 57064‑001, June; and, United Nations Children’s Fund (2021), Analysis of child-focused budgets and expenditure in the social sectors in Mongolia.

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Child benefits

In terms of spending the biggest programme family benefit programme in Mongolia is the “Child Money Program”: a universal child allowance at present with a payment rate of around MNT 100 000 (USD 35 per child) with spending amounting to 2.6% of GDP in 2022 (ADB, 2024[107]). This high spending level is related to the government increasing payment rates – from MNT 20 000 to MNT100 000 during the COVID‑19 pandemic (UNICEF Mongolia, 2023[108]). The programme has been instrumental in reducing child poverty, improve food security and meeting basic needs. Spending on paid maternity leave and childcare allowances for caregivers with children under 3 years of age amounted to 0.2% of GDP each. Furthermore, Mongolia ranks among the countries with the highest regional enrolment rates in ECEC (Chapter 4, Figure 4.6) and public spending on ECEC supports amounted to 1.4% of GDP in 2022.

The introduction of cash transfers for children and newlyweds in the mid‑2005s signalled an end to the period of non-natalist policy in Mongolia (Annex Table 1.A.1) and after the introduction of the “Child Money Program” fertility increase further until 2015 (Figure 1.2). However, the TFR has fallen to 2.7, and it remains to be seen how it holds up in future. The increase in fertility rates in Mongolia until 2015 has indeed been linked to the introduction and expansion of cash supports since 2006 (Spoorenberg and Enkhtsetseg, 2009[109]; Judger, Baffour and Zhao, 2021[110]). But it is not the only reason for the increase in fertility rates. The Mongolian pattern involves some similarities with fertility trends in Central Asia – Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan, where fertility rates on average increased from 2.6 children per women in 2005 to 3.2 in 2024 (Worldometer, 2024[111]). Strong economic growth in these countries (Eurasian Development Bank, 2022[112]; World Bank, 2024[113]) will have contributed to the increase in the fertility rates (Spoorenberg, 2015[114]).

Cash transfers for families with children, such as family or child allowances, lower the direct costs of having children and may therefore increase fertility rates (Figure 1.8). However, substitution effects might also occur, such as investing more in children who have already been born instead of having more children (Bergsvik, Fauske and Hart, 2021[115]). In 2023, a single‑earner couple family with two children (age 4 and 6) with average earnings in the four OECD countries in the region would receive child allowances worth 4.5% of the Average Wage (AW) in Japan to 8.8% of AW in Korea. The payment in Korea (until age 8) and Japan (until age 18) are not income‑tested,1 unlike child benefits in Australia and New Zealand. An otherwise similar couple family with earnings at 167% of AW would not receive child benefits (OECD, 2024[116]). Many other countries in the region have universal child allowances. For example, Thailand has a child allowance that is considered as a social assistance benefit; it was worth THB 800 (about USD 25) per month in 2024 paid to families with incomes below THB 100 000 around USD 3 000 per person per annum. For children born in 2018 and after, there is also a child tax credit of THB 30 000 (around USD 925) per annum for the first child and THB 60 000 for each subsequent child (Nishimura and Asahi, 2024[117]). Indonesia also has a tax credit for up to three dependents worth up to IDR 4.5 million (about YSD 295) (PWC, 2024[118]), but the “Family Hope Program” is a conditional cash transfer programme that pays out cash transfers to low-income families subject to participation in health and education services (Syamsulhakim and Khadijah, 2021[119]). In China, in 2022 taxpayers who took care of children aged under 3 years, those in preschool, or those full-time education, were entitled to a tax deduction of RMB1 000 (approximately USD 140) per month (UNICEF China, 2023[120]), while cities and regions may provide additional cash payments.

Most international research shows that monetary transfers for families with children have no or only modestly positive or temporary effects on fertility (OECD, 2024[6]; OECD, 2011[103]; Skirbekk, 2022[43]). For example, the Polish 500+ child benefit programme, has substantially reduced (extreme) child poverty, but failed to raise fertility rates (Magda et al., 2019[121]; Ekert, 2022[122]). The Australian Baby Bonus was a universal payment to all women having a baby from 2004 until 2014, when it was a lump-sum birth grant worth AUD 500 (it was replaced in 2014 by an income‑tested child benefit, that cannot be claimed with parental leave pay for the same child). The payment was found to have had a small but statistically significant impact on the fertility rate, with the biggest effects among immigrant women of low educational attainment (Bonner and Sarkar, 2020[123]). The concentration of effects among lower educated and immigrant women highlights that these groups, like young people, are likely particularly sensitive to the financial costs of childbearing (Gray et al. (2022[70]) includes an overview of various studies). Financial support may also affect decisions on having another child. For example, see Drago et al. (2010[124]) on Australia, while Matsuda (2019[125]) found for Japan that child allowances could affect the desire to have another child for parents, especially fathers.

Parental leave

Employment-protected paid family leave entitlements are a major feature of family policy across the world. Maternity leave entitlements are designed to protect infants and mothers around childbirth, but increasingly policy is moving to give both parents some time to provide childcare in the early years of life of a new-born. Indeed, paternity leave arrangements are emerging in Asia/Pacific countries, while, for now, only OECD countries in the region provide parental leave benefits over and above paid maternity- and paternity leaves (Figure 1.11).

Over 30 countries in the Asia/Pacific region have constituted national paid maternity leave benefits with an average duration of just over 15 weeks (for a “global discussion of maternity protection” see ILO (2024[126])), compared to an OECD average of just below 19 weeks (OECD, 2024[11]). Across the region paid maternity leave is longest in India, New Zealand and Viet Nam at around 6 months and shortest Bhutan the Maldives and Samoa at below 10 weeks (Figure 1.11, Panel A).

There is increasing awareness among policy makers that getting fathers to take leave to care for children may help generate a more gender equal division of paid and unpaid work and reduce discrimination of women in the workplace (including regarding hiring and promotion practices), as well as strengthening the bond between fathers and children. By 2022, about 20 countries in the region had introduced specific paid paternity leaves that were generally short in duration: about 1.5 weeks across the Asia/pacific region on average (Figure 1.11, Panel B), compared to 2.5 weeks on average across the OECD.

Over and above these periods of paid maternity and paternity leave, many OECD countries, including Australia, Japan and Korea also have introduced paid parental leave legislation (Figure 1.11, Panel C).2 In fact, at one year of paid leave Japan and Korea have the longest periods of paid parental leave earmarked for fathers of all OECD countries. In Japan, parents can take periods of paid parental leave at the same time, while in Korea parents take paid parental leave consecutively. Available evidence suggests that women in Korea with access to leave are more likely to plan to have children (Jung, Jang and Park, 2024[127]). Survey-based analysis suggests that the introduction of paid parental leave in Australia in 2011 had a positive effect on the fertility intentions of women with high levels of education and therefore a likely positive effect on realised fertility (Bassford and Fisher, 2020[128]).

Figure 1.11. Paid maternity, paternity and parental leave in the Asia/Pacific region, 2023 or latest year

1. In Australia, in 2023 there was no separate regulation for (paid) maternity leave, with stipulations all integrated into the parental leave scheme. However, it is assumed that the 12 weeks of “Parental Leave Pay” are used by the mother straight after the birth, effectively functioning as a paid maternity leave (12 weeks must be used in one block within the first 12 months after childbirth). The remaining 6 weeks are considered mother-specific parental leave. The average for the Asia/Pacific region in the first two panels includes all countries in the figure, i.e. it does not include the observation for Hong Kong (China).

2. In Japan, each parent can take a maximum of 12 months of paid leave until a child is 12 months old; if both parents take some of the leave, then one parents can take leave up until the child is 14 months.

Source: for Panels A and B: ILO (2024), World Social Protection Data Dashboards, Key features of social protection schemes and benefits, OECD (2023), PF2.1. Parental leave systems, OECD Family Database, and The World Bank (2024), Women Business and the Law, Parenthood. For Panel C, OECD (2023) only.

Statlink

However, the systemic characteristics captured in (Figure 1.11) paint too rosy a picture. This is because many workers – and in many less affluent countries most workers, do not have access to paid maternity, paternity and parental leaves. Paid leave is generally only accessible to workers with a formal employment contract, and across the Asian/Pacific region about two/thirds of workers are in informal employment without access to social security benefits (ILO, 2023[129]). In a similar vein, many workers in Japan and Korea do not have access to parental leave benefits as non-regular workers are often not entitled. Increasing the use of paid leave benefits is an important policy challenge for Japanese and Korean authorities, and some progress is being made (Hwang et al., 2023[38]; OECD, 2024[73]; OECD, 2024[72]; OECD, 2019[130]). In Japan, 30.1% of fathers took some parental leave in 2023 up from 2.03% 10 years earlier (Ministry of Health, Labor and Work, Japan, 2024[131]; OECD, 2024[72]). In Korea in 2013, 4 500 fathers took some parental leave and by 2022 this had increased to 54 000 on 230 000 births (KOSIS, 2024[132]).

Evidence on the impact of father’s leave these policies for Asia/Pacific is scant, as paid father’s leave is relative new or underused (OECD, 2024[73]; OECD, 2024[72]). Evidence on the introduction in Australia of Dad and Partner Pay is, as yet, inconclusive (Gray et al., 2022[70]), while evidence for Korea suggests that fathers who took family leave were less likely to want another child relative to those who are just about to start their leave (Lee, 2022[133]). Then again, as few fathers have taken leave so far, this result is unlikely to have an important bearing on fertility rates in Korea.

Early childhood education and care (ECEC)

Public support for high-quality and affordable early childhood education and care (ECEC) services helps achieve a range of policy goals. Public investment in ECEC simultaneously enhances child development and helps children acquire the necessary skills to support their future lives, while it also supports parents in their daily quest to balance work and family commitments. As women traditionally engage most in care work, such supports particularly facilitate women’s labour force participation and are thus crucial to achieving greater gender equality in employment participation.

Across the Asia/Pacific region participation in ECEC is increasing, on average from two/thirds of all 3‑5 years olds in 2021 just below 80% in 2020 (Figure 4.6). During this period enrolment rates in in Asian/Pacific increased steadily in about three‑quarters of the countries, and doubled in Bangladesh, Lao PDR and Uzbekistan and almost tripled in Azerbaijan.

There is no comprehensive data available on participation in ECEC among 0‑3 years olds in the Asia/Pacific region. Enrolment in ECEC in Australia, Japan and New Zealand among children in the 0‑2 age‑groups was above the OECD average at 45%, and about two/thirds of children in this age‑group in Korea were participating in ECEC (OECD, 2024[11]), Indicator PF3.2, “Enrolment in childcare and pre‑school”). This is the second highest enrolment rate across the OECD after the Netherlands, which is even more impressive when one realises that children in the Netherlands often only participate in formal ECEC services for one or two days per week; children in Korea often attend ECEC for 8‑10 hours per day, 5 days per week.

The OECD wide regressions (Box 1.3) showed that public spending on ECEC – which covers accessibility, availability and intensity of use as well as affordability and quality of ECEC, has a significant positive association with fertility rates. ECEC enrolment rates (which are a proxy for the availability of ECEC) are not significant in any of the regressions. The international literature frequently – but not always, finds positive effects of ECEC availability on fertility, and effects may differ across birth parity. For example, expansions of ECEC availability in Japan have been positively linked with slightly increased fertility in regions where women are most likely to engage in the labour market (Fukai, 2017[134]), but despite the important expansion of ECEC and family supports in general, Korea has not been able to reverse its downward trend in the TFR (Jeong et al., 2022[135]). Part of this may be explained by the difficulties to reconcile work and family life, for example through very long working hours. Other potential factors include changing societal norms and notions on gender roles, labour market dualism and the large number of parents who are reluctant to use or are ineligible for paid leave around childbirth.

Direct costs of children

Increasing housing costs affects fertility

Formal childcare, education, food, and housing are significant parts of a family budget, and more children mean more costs. Changes in the price of such goods and services are therefore likely to change fertility outcomes. Across the OECD, household expenditure on housing and utilities has increased substantially, in line with strong increases in (real) house prices over past decades, but particularly since the mid‑2010s (OECD, 2023[8]).

Establishing a family and having (more) children, often means an increase in housing expenditure through moves to bigger housing space to accommodate a larger family size. Increasing housing costs make it more expensive to have (more) children, and ipso facto an increase in housing costs exerts a negative effect on fertility rates. At the same time, for a homeowner, an increase in housing prices increases equity, which could lead to an increase in birth rates among homeowners. There is thus an ambiguous relationship between housing and fertility, and the relationship with countries (regions) depends on context. The nature of the local housing market can exacerbate the effect of house price increases on fertility, as does the state of family formation and tenure. Increasing house prices are more likely to affect first-time buyers, who are considering having a first child, but have less of an effect (or a positive effect) on those parents already on the housing ladder who are considering having more children.

The literature reflects these effects. For Australia (Atalay, Li and Whelan, 2021[136]), showed that an AUD 100 000 increase in housing wealth among home owners was associated with an 18% increase in the probability of having a child, but was associated with a decreased probability of having a child among renters. For Japan (Mizutani, 2012[137]) found that for families with mortgages, the chance of having a child increased due to the increase in housing assets, and there is evidence for Korea that increasing house prices suggests affects fertility choices among couples in short term rental housing, but do not carry over to the second child (Kim and Sparks, 2019[138]).

Since house and rental prices have risen dramatically in many OECD countries, partnership and family formation may in part have been inhibited by more young adults having to live with their parents for financial reasons for a longer time into their 20s and 30s (Esteve et al., 2020[139]; Cournède and Plouin, 2022[140]). Indeed, living with parents can for some young people be the only way to deal with a situation of high rental prices and insecure jobs. Across the OECD, there has been an increase in the proportion of youth (aged 20‑29) living in their parents’ households, to 50% on average. This share is 30% in New Zealand, 40% in Australia and 80% in Korea, the highest share in the OECD (OECD, 2024[6]). In Japan in 2019 around 80% of the 20‑24 year‑olds were living with their parents, and this proportion was over 60% for the 24‑29 year‑old age group (NIPSSR, 2022[141]).

Overall, regression analyses for OECD countries suggest that the increase in house prices and housing costs found that increases in household expenditure on housing had a significant and negative effect on TFRs (Box 1.3), and this evidence is corroborated through panel data analysis across OECD countries by (Hwang et al., 2023[38]) who also present evidence on the negative effect of increasing house prices on the fertility rate in Korea.

While a recent survey in Japan found that housing costs were a reason for not achieving the ideal family size, for 9.4% of respondents to the National Fertility Survey (NIPSSR, 2023[142]). For Singapore, where 81% of the population lived in public housing in 2018, (Saguin, 2021[143]) found that the resale price of public housing negatively impacted fertility levels in the long run, providing evidence for the prevailing notion of “no flat, no child” among many young Singaporeans. (Clark, Yi and Zhang, 2020[144]) illustrate the negative relationship between the cost of housing and fertility in urban China: the negative effect is significant in 30‑five large cities in China but not significant for other smaller cities.

Governments have a range of policy options to promote housing affordability for renters. Policies could aim to increase the supply of housing through measures such as facilitatory land use and building permit regulations, as for example, a review of boundaries on urban development or relaxation of building height regulations (OECD, 2021[145]); support social housing policies and housing allowances that tend to target lower-income and other vulnerable households (OECD, (2021[146]; 2020[147])), while access to more affordable rental housing makes it easier for younger people to have children (Brauner-Otto, 2021[148]). In addition, easier access to mortgage and homeownership for younger people through subsidies and guarantees could positively affect fertility (Gurov and Kulikova, 2022[149]). In Hungary, for example, increased home‑ownership support has been shown to positively affect fertility (Szabó-Morvai et al., 2019[150]). For an overview of affordable housing policy initiatives in China, see Zhang et al. (2023[151]), who argue that policies should improve the location of new affordable housing projects, address discord between central and local governments, make better use of new technologies including the assembly of prefabricated housing and engage in more comprehensive evaluations of socio‑economic benefits of planned housing initiatives.

Education costs establish a barrier to having (more) children in some Asian countries

Korea is a rather competitive society (Hwang et al., 2023[38]) and competition for good school and university places that may help secure and well-paid careers starts early in life. Even before primary school age, many parents invest in supplementary private education to position their children as well as possible for entrance into Korea’s most prestigious schools and universities. Across most of childhood, Korean parents and their children engage in an educational struggle to get ahead that involves daily participation in schools, after-school programmes, private tutoring schools or “Hakwon”, as well as homework – children often spend more than 10 hours per day on such activities. The high private education costs often pose a barrier to having more children and help to explain while many Korean parents have one child, rather than two or more. The cost of private cram school education can also establish a barrier to having (more) children in urban China and Japan – in both countries these countries these private tutoring schools are known as “Juku” (CSM, 2021[152]; Jones, 2019[153]; Masuda, 2016[154]; NIPSSR, 2023[142]; OECD, 2024[73]; OECD, 2024[72]; OECD, 2019[130]; The Lauder Institute, 2022[155]).

Changes in attitudes and norms can be important for fertility trends

There are large differences in the Asia/Pacific region regarding traditional perceptions on having children: In the Philippines, Kyrgyzstan, Tajikistan over 80% and almost 90% of Bangladeshi survey respondents, agree or strongly agree with the notion that there is a duty towards society to have children. This notion is more prevalent in the Asia/Pacific than across the OECD and least so in the Netherlands and New Zealand where fewer than 5% of respondents agree or strongly agree (WVS, 2022[156]).

Unfortunately, comprehensive historical trend data in this regard are not available, but understanding how attitudes and norms affect the way people think about their conditions, how norms and attitudes have changed over time, and how “more recent” norms and attitudes drive behaviour among young adults will help to better comprehend the decline in fertility and the choices couples make.

The Second Demographic Transition theory has emerged as a central theory to explain changes in family formation over the course of the 2000s and 2010s (Sobotka, 2008[3]). It postulates that as societies reach a certain level of economic advancement, non-materialist values such as self-fulfilment become more important to people. It predicts that the family ideal weakens because of a greater focus on individual autonomy, choice, and self-actualisation. In this sense, having children and investing time and resources in raising them according to the high standards required by society (see below) can be seen as competing with alternative life goals, and life goals other than family and children have gained importance in recent years (OECD, 2023[86]).

The Second Demographic Transition may be a useful framework for explaining recent trends in many OECD countries of very low fertility combined with alternative union and family types, but it does not fully apply to East Asia. Past rigid lifestyles and life courses are now more flexible, but family ideals have not changed as much in many other OECD countries in line with prevailing influences of Confucianism and collectivism in Asian societies (Le et al., 2020[157]). Attitudes towards marriage and having children, gender roles and care provision at home have been slow to change in East Asia (Gietel-Basten, 2023[158]; Lee and al, 2018[159]). For example, for Japan (Raymo, 2022[160]) found that endorsement of conventional family patterns and gender roles has declined, but that they remain more prevalent than in most other OECD countries. In China, social trends include an increasing mean age at first marriage and premarital cohabitation, but there has not been a rise in nonmarital childbirths, even though there has been growing tolerance toward nonmarital childbearing and childlessness (Yu and Xie, 2022[161]).

Younger people are rejecting expected norms, and are embracing individual autonomy, self-actualisation and self-expression (Gietel-Basten, 2022[162]). There is an increasing number of young people in East Asia who support gender-egalitarian values, especially among those with high levels of educational attainment (Lee and al, 2018[159]). However, as the reconciliation of work and family life is so hard to achieve (e.g. (Cho and Han, 2024[163]; Tsutsui, 2019[164]), many young people in East Asia choose not to have children.

Pressures of parenting

The normative demands on what it means to be a “good” parent have grown, or at least grown in importance. The act of balancing the costs and benefits of having children – both financial and non-financial – has been widely studied to better understand the reasoning behind the choice to have fewer, if any, children today than in the past (see, for example (Mynarska and Rytel, 2022[165]; Lebano and Jamieson, 2020[166]). Parents tend to put in increasing amounts of time into raising children, rather than letting children grow up without much intervention, and this holds especially for parents with higher levels of education (Ellingsæter, Kitterød and Hansen, 2022[167]), as postulated by (Becker, 1960[2]).

Parents in Korea are subject to a strong culture of “helicopter parenting” or “over-parenting”, that requires parents – and particularly mothers – to micromanage their children’s days to maximise their chances in an increasingly competitive education environment. This “helicopter parenting” culture was found to inhibit parents’ emotional and financial abilities to have children, as well as children’s ability to develop autonomy, independence, and happiness (OECD, 2019[130]). Similarly, parenting in Japan tends to be particularly intensive, and it is primarily mothers who look after children’s daily needs and help them succeed in a highly competitive education system (OECD, 2024[72]). a fear of not being able to live up to the ideal of intensive parenting is an important reason for postponing or avoiding family formation.

With the de‑stigmatisation of childlessness and a wider discussion about whether it is right to have children, it is not surprising that young adults increasingly consider the state of the world in which their potential future children will grow up when making fertility choices. A 2020 survey found that 26% of childless adults in the United States reported that climate change was either a “major reason” or a “minor reason” for not having children (Jenkins, 2020[168]). Another poll shows similar results in Australia: 33% of female respondents under 30 reported “reconsidering having children or more children because I am increasingly worried that if I have children, they will face an unsafe future from climate change” (Australian Conservation Foundation, 2019[169]). Evidence from China shows that while not the most frequently cited concern around fertility choices, climate worries do play some role (Fu, Schneider-Mayerson and Montefrio, 2022[170]). ILO (2024[126]) showed that populations in countries that are most susceptible to climate hazards – among which many countries in the Pacific countries remain woefully unprepared, in terms of social protection coverage and decent work opportunities. However, it is unclear to what extent these concerns have contributed and/or will contribute to declining fertility rates in these countries.

Concluding remarks

The Asia/Pacific region is very diverse, also in socio‑economic terms (Chapter 3 of this volume) and any summary will fail to do justice to its rich cultural and historical palette that also contributes to different regional and national fertility trends. However, some summary observations can be put forward.

Fertility rates, including teenage fertility rates, have fallen in most countries of the Asia/Pacific region over the past 50 years. Better access to contraceptives and family planning services and increasing educational attainment have contributed to people having greater control over their life choices and has contributed to the fall of Total Fertility Rates (TFRs) towards the replacement level of approximate 2.1 children per woman across the Asia/Pacific region on average. TFRs remain over 3 children per woman in some countries in Central and South Asia, and across less affluent Australasian Island nations. In India and Indonesia TFRs are around replacement level, while in Australia and New Zealand they hover around 1.6‑1.7 children per woman, with immigration inflows slowing down overall population ageing in these two countries. However, East Asian countries such as Japan, Korea and Singapore, as well as China are experiencing persistently low fertility rates, which are contributing to rapidly ageing societies.

It is not surprising therefore, that these countries have changed their overall policy stance from “population control” in the 1960s, 1970s and 1980s to one of “counteracting low fertility” since the turn of the millennium. Overcoming low fertility appears to be an important driver of policy development in China, Japan, Korea and Singapore.

Personal choices towards having children depend on a range of factors. Consequently, a multifaceted policy approach is required to enable people to have the number of children they desire at the time of their choice, as solving one issue (e.g. support with care for children) may not address other barriers to parenthood (e.g. the cost of housing or long working-hours). The massive expansion of ECEC services in Korea is a case in point, it is helping parents reconcile work and family life, but clearly there are other barriers to having children (e.g. low pay in non-regular employment, the cost of private education) that curtail the upward effect of public work/life balance supports on fertility rates.

Also, public policy cannot do it alone, it needs coherence with labour market institutions and workplace practices that are co-determined by employers and unions. For example, Japan’s increased public support for families is well-documented, but the chasm between regular and non-regular employment conditions and the associated (gender) pay gap limits household incomes, and fulfilment of many women’s aspirations. The workplace culture needs to change to help both parents to combine work and family life in a financially rewarding way. Examples of relevant measures would include increasing opportunities for mothers to return to regular employment and extending the social insurance coverage of non-regular workers.

Fiscal space for additional investment in families may be limited, but the best approach for countries that are concerned about fertility rates remains to promote more gender equality and fairer sharing of work and childrearing. This involves providing family policies that help the reconciliation of work and family life, but policy must also have a greater focus on the costs of children, especially housing costs. Then again, in Singapore most of the population lives in public housing, but comprehensive housing policies on their own are not enough to avoid low fertility rates.

Attitudes towards parenthood appear to be changing, albeit more slowly in Asia than across the OECD. Endorsement of conventional family patterns and gender roles has declined, but they remain more prevalent than in most other OECD countries. For example, having children outside marriage remains uncommon in East Asia, but there is an increasing number of young people who support gender-egalitarian values, especially among those with high levels of educational attainment.

At the same time, the normative demands on what it means to be a “good” parent have grown in importance, and the changing balance in costs and benefits of having a child in for example, urban China, Japan and Korea – both financial and non-financial, affects the choice to have children and how many. As the reconciliation of work and family life is so hard to achieve, many young people in East Asia have fewer, if any, children today than in the past.

References

[107] ADB (2024), Mongolia: Developing Inclusive and Resilient Social Protection Systems in Asia and the Pacific, Asian Development Bank.

[97] Adema, W. (2012), “Setting the scene: The mix of family policy objectives and packages across the OECD”, Children and Youth Services Review, Vol. 34/3, pp. 487-498, https://doi.org/10.1016/j.childyouth.2011.10.007.

[104] Adema, W. (2006), “Towards coherent care and education support policies for New Zealand families”, Social Policy Journal of New Zealand - Te Puna Whakaaro 28, pp. pp. 46-76, https://www.msd.govt.nz/about-msd-and-our-work/publications-resources/journals-and-magazines/social-policy-journal/spj28/28-towards-coherent-care-and-education-support-policies-for-new-zealand-families-p46-76.html.

[51] Adema, W., J. Fluchtmann and V. Patrini (2023), “Mainstreaming gender equality”, in Joining Forces for Gender Equality: What is Holding us Back?, OECD Publishing, Paris, https://doi.org/10.1787/a3452d6b-en.

[81] Ahn, J. et al. (2021), “The Association Between Long Working Hours and Infertility”, Safety and Health at Work, Vol. 12/4, pp. 517-521, https://doi.org/10.1016/j.shaw.2021.07.005.

[17] AIFS (2024), Births in Australia, https://aifs.gov.au/research/facts-and-figures/births-australia-2024.

[136] Atalay, K., A. Li and S. Whelan (2021), “Housing wealth, fertility intentions and fertility”, Journal of Housing Economics, Vol. 54, p. 101787, https://doi.org/10.1016/j.jhe.2021.101787.

[169] Australian Conservation Foundation (2019), New survey shows women will change their lives – and votes – for climate action, https://www.acf.org.au/women_will_change_their_lives_and_votes_for_climate_action.

[171] Australian Government (2023), How much you can get? - Parental Leave Pay for a child born or adopted from 1 July 2023 is based on the national minimum wage., https://www.servicesaustralia.gov.au/how-much-parental-leave-pay-you-can-get-for-child-born-or-adopted-from-1-july-2023?context=64479.

[53] Barro, R. and J. Lee (2013), “A new data set of educational attainment in the world, 1950–2010”, Journal of Development Economics, Vol. 104, pp. 184-198, https://doi.org/10.1016/j.jdeveco.2012.10.001.

[128] Bassford, M. and H. Fisher (2020), “The Impact of Paid Parental Leave on Fertility Intentions*”, Economic Record, Vol. 96/315, pp. 402-430, https://doi.org/10.1111/1475-4932.12561.

[10] Beaujouan, E. and C. Berghammer (2019), “The Gap Between Lifetime Fertility Intentions and Completed Fertility in Europe and the United States: A Cohort Approach”, Population Research and Policy Review, Vol. 38/4, pp. 507-535, https://doi.org/10.1007/s11113-019-09516-3.

[2] Becker, G. (1960), “An economic analysis of fertility”, Columbia University Press, pp. 209-240, http://www.nber.org/chapters/c2387.pdf.

[115] Bergsvik, J., A. Fauske and R. Hart (2021), “Can Policies Stall the Fertility Fall? A Systematic Review of the (Quasi-) Experimental Literature”, Population and Development Review, Vol. 47/4, pp. 913-964, https://doi.org/10.1111/padr.12431.

[61] Berninger, I. (2013), “Women’s income and childbearing in context: First births in Denmark and Finland”, Acta Sociologica (United Kingdom), Vol. 56/2, https://doi.org/10.1177/0001699312444933.

[59] Bertrand, M. et al. (2020), “Social Norms, Labour Market Opportunities, and the Marriage Gap Between Skilled and Unskilled Women”, The Review of Economic Studies, Vol. 88/4, pp. 1936-1978, https://doi.org/10.1093/restud/rdaa066.

[21] Bhasin, S. et al. (2019), “The Implications of Reproductive Aging for the Health, Vitality, and Economic Welfare of Human Societies”, The Journal of Clinical Endocrinology & Metabolism, Vol. 104/9, pp. 3821-3825, https://doi.org/10.1210/jc.2019-00315.

[1] Bhattacharjee, N. et al. (2024), “Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021”, The Lancet, https://doi.org/10.1016/s0140-6736(24)00550-6.

[123] Bonner, S. and D. Sarkar (2020), “Who responds to fertility-boosting incentives? Evidence from pro-natal policies in Australia”, Demographic Research, Vol. 42, pp. 513-548, https://doi.org/10.4054/demres.2020.42.18.

[25] Borumandnia, N. et al. (2022), “Worldwide trend analysis of primary and secondary infertility rates over past decades: A cross-sectional study”, International Journal of Reproductive BioMedicine (IJRM), pp. 37-46, https://doi.org/10.18502/ijrm.v20i1.10407.

[148] Brauner-Otto, S. (2021), “Housing and fertility: a macro-level, multi-country investigation, 1993-2017”, Housing Studies, pp. 1-28, https://doi.org/10.1080/02673037.2021.1893279.

[87] Buckles, K., D. Hungerman and S. Lugauer (2020), “Is Fertility a Leading Economic Indicator?”, The Economic Journal, Vol. 131/634, pp. 541-565, https://doi.org/10.1093/ej/ueaa068.

[9] Burkimsher, M. (2015), “Europe-wide fertility trends since the 1990s: Turning the corner from declining first birth rates”, Demographic Research, Vol. 32, pp. 621-656, https://doi.org/10.4054/demres.2015.32.21.

[69] Causa, O., N. Luu and M. Abendschein (2021), “Labour market transitions across OECD countries: Stylised facts”, OECD Economics Department Working Papers, No. 1692, OECD Publishing, Paris, https://doi.org/10.1787/62c85872-en.

[15] Chen, T. et al. (2022), “The Impacts of the COVID-19 Pandemic on Fertility Intentions of Women with Childbearing Age in China”, Behavioral Sciences, Vol. 12/9, p. 335, https://doi.org/10.3390/bs12090335.

[163] Cho, D. and J. Han (2024), “Women’s Career Interruptions and the Declining Fertility Rate in South Korea”, SSRN Electronic Journal, https://doi.org/10.2139/ssrn.4881265.

[68] Chung, H., S. Bekker and H. Houwing (2012), “Young people and the post-recession labour market in the context of Europe 2020”, Transfer: European Review of Labour and Research, Vol. 18/3, pp. 301-317, https://doi.org/10.1177/1024258912448590.

[64] Chung, M. and K. Lee (2022), “A recent change in the relation between women’s income and childbirth: heterogeneous effects of work-family balance policy”, Journal of Demographic Economics, Vol. 88/3, pp. 419-445, https://doi.org/10.1017/dem.2021.9.

[57] Ciganda, D., A. Lorenti and L. Dommermuth (2021), “Changes in the educational gradient of fertility not driven by changes in preferences”, MPIDR Working Paper, Vol. 2021/016, https://www.demogr.mpg.de/papers/working/wp-2021-016.pdf.

[144] Clark, W., D. Yi and X. Zhang (2020), “Do House Prices Affect Fertility Behavior in China? An Empirical Examination”, International Regional Science Review, Vol. 43/5, pp. 423-449, https://doi.org/10.1177/0160017620922885.

[88] Comolli, C. and D. Vignoli (2021), “Spreading Uncertainty, Shrinking Birth Rates: A Natural Experiment for Italy”, European Sociological Review, Vol. 37/4, pp. 555-570, https://doi.org/10.1093/esr/jcab001.

[80] Cooke, L. (2009), “Gender equity and fertility in Italy and Spain”, Journal of Social Policy, Vol. 38/1, https://doi.org/10.1017/S0047279408002584.

[140] Cournède, B. and M. Plouin (2022), No Home for The Young? Stylised Facts and Policy Challenges, OECD Publishing, Paris, https://www.oecd.org/en/publications/no-home-for-the-young_adbee321-en.html.

[152] CSM (2021), Cram school is out, forever. Why Chinese parents aren’t rejoicing., https://www.csmonitor.com/World/Asia-Pacific/2021/1014/Cram-school-is-out-forever.-Why-Chinese-parents-aren-t-rejoicing.

[29] Doepke, M. et al. (2022), The Economics of Fertility: A New Era, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w29948.

[124] Drago, R. et al. (2010), “Did Australia’s Baby Bonus Increase Fertility Intentions and Births?”, Population Research and Policy Review, Vol. 30/3, pp. 381-397, https://doi.org/10.1007/s11113-010-9193-y.

[122] Ekert, M. (2022), “Subject: Econometric analysis of the “family 500+” program – a study of the impact of the social benefit on the fertility of poles”, https://doi.org/10.19253/reme.2022.01.001.

[167] Ellingsæter, A., R. Kitterød and M. Hansen (2022), “How does parental time relate to social class in a Nordic welfare state?”, Acta Sociologica, Vol. 65/2, https://doi.org/10.1177/00016993211052079.

[139] Esteve, A. et al. (2020), Moving out the parental home and partnership formation as social determinants of low fertility, Verlag der Österreichischen Akademie der Wissenschaften, https://doi.org/10.1553/populationyearbook2020.deb02.

[112] Eurasian Development Bank (2022), The Economy of Central Asia: A Fresh Perspective, https://eabr.org/upload/iblock/1fe/EDB_2022_Report-3_The-Economy-of-CA_eng.pdf.

[99] Feng, W., Y. Cai and B. Gu (2013), “Population, Policy, and Politics: How Will History Judge China’s One‐Child Policy?”, Population and Development Review, Vol. 38/s1, pp. 115-129, https://doi.org/10.1111/j.1728-4457.2013.00555.x.

[48] Fluchtmann, J., M. Keese and W. Adema (2024), “Gender equality and economic growth: Past progress and future potential”, OECD Social, Employment and Migration Working Papers, No. 304, OECD Publishing, Paris, https://doi.org/10.1787/fb0a0a93-en.

[5] Fluchtmann, J., V. van Veen and W. Adema (2023), “Fertility, employment and family policy, A cross-country panel analysis”, OECD Social, Employment and Migration Working Papers, No. 299, OECD Publishing, Paris, https://doi.org/10.1787/326844f0-en.

[134] Fukai, T. (2017), “Childcare availability and fertility: Evidence from municipalities in Japan”, Journal of the Japanese and International Economies, Vol. 43, pp. 1-18, https://doi.org/10.1016/j.jjie.2016.11.003.

[170] Fu, X., M. Schneider-Mayerson and M. Montefrio (2022), “The reproductive climate concerns of young, educated Chinese: ‘when the nest is upset, no egg is left intact’”, Environmental Sociology, https://doi.org/10.1080/23251042.2022.2132629.

[82] Gaskins, A. et al. (2015), “Work schedule and physical factors in relation to fecundity in nurses”, Occupational and Environmental Medicine, Vol. 72/11, pp. 777-783, https://doi.org/10.1136/oemed-2015-103026.

[89] Gatta, A. et al. (2021), “Employment uncertainty and fertility intentions: Stability or resilience?”, Population Studies, Vol. 76/3, pp. 387-406, https://doi.org/10.1080/00324728.2021.1939406.

[101] Gauthier, A. and S. Gietel‐Basten (2024), “Family Policies in Low Fertility Countries: Evidence and Reflections”, Population and Development Review, https://doi.org/10.1111/padr.12691.

[28] Gershoni, N. and C. Low (2021), “Older Yet Fairer: How Extended Reproductive Time Horizons Reshaped Marriage Patterns in Israel”, American Economic Journal: Applied Economics, Vol. 13/1, pp. 198-234, https://doi.org/10.1257/app.20180780.

[40] Ghaznavi, C. et al. (2020), “The herbivore’s dilemma: Trends in and factors associated with heterosexual relationship status and interest in romantic relationships among young adults in Japan—Analysis of national surveys, 1987–2015”, PLOS ONE, Vol. 15/11, p. e0241571, https://doi.org/10.1371/journal.pone.0241571.

[39] Ghaznavi, C. et al. (2022), “Salaries, degrees, and babies: Trends in fertility by income and education among Japanese men and women born 1943–1975—Analysis of national surveys”, PLoS ONE, Vol. 17(4), https://doi.org/10.1371/journal.pone.0266835.

[162] Gietel-Basten, S. (2022), “Demographic and social anxieties: the second demographic transition in Asia”, China Population and Development Studies, Vol. 6/3, pp. 338-349, https://doi.org/10.1007/s42379-022-00121-0.

[172] Government of Japan (2023), Children’s Future Strategy Policy (in Japanese), https://www.cas.go.jp/jp/seisaku/kodomo_mirai/pdf/kakugikettei_20231222.pdf.

[58] Gray, E. and E. Lazzari (2023), “The continuing decline in cohort fertility and mixed evidence of narrowing educational differences”, Australian Population Studies, Vol. 7/1, pp. 1-16, https://doi.org/10.37970/aps.v7i1.112.

[70] Gray, E. et al. (2022), Impacts of policies on fertility rates, Australian National University, https://population.gov.au/sites/population.gov.au/files/2022-03/ANU_Impacts-of-Policies-on-Fertility-Rates-Full-report.pdf.

[46] Guillemette, Y. and D. Turner (2021), “The long game: Fiscal outlooks to 2060 underline need for structural reform”, OECD Economic Policy Papers, No. 29, OECD Publishing, Paris, https://doi.org/10.1787/a112307e-en.

[98] Gupte, P. (2017), “India: “The Emergency” and the Politics of Mass Sterilization”, Education About Asia, Vol. Volume 22:3 (Winter 2017):, https://www.asianstudies.org/publications/eaa/archives/india-the-emergency-and-the-politics-of-mass-sterilization/.

[149] Gurov, I. and E. Kulikova (2022), “Fertility-Household Credit Burden Nexus at the Present Stage”, Population and Economics, Vol. 6/1, pp. 36-61, https://doi.org/10.3897/popecon.6.e76066.

[95] Guzmán, J. (2009), Population Dynamics and Climate Change, UNFPA and IIED, https://www.unfpa.org/sites/default/files/resource-pdf/pop_dynamics_climate_change_0.pdf.

[62] Hart, R. (2015), “Earnings and first birth probability among Norwegian men and women 1995-2010”, Demographic Research, Vol. 33/1, https://doi.org/10.4054/DemRes.2015.33.38.

[106] Heckman, J. and D. Masterov (2007), “The Productivity Argument for Investing in Young Children”, Review of Agricultural Economics, Vol. 29/3, pp. 446-493, https://doi.org/10.1111/j.1467-9353.2007.00359.x.

[85] Herbertson, E. (ed.) (2023), “The impact of working hours on pregnancy intention in childbearing-age women in Korea, the country with the world’s lowest fertility rate”, PLOS ONE, Vol. 18/7, p. e0288697, https://doi.org/10.1371/journal.pone.0288697.

[24] Huang, B. et al. (2023), “Global, regional and national burden of male infertility in 204 countries and territories between 1990 and 2019: an analysis of global burden of disease study”, BMC Public Health, Vol. 23/1, https://doi.org/10.1186/s12889-023-16793-3.

[38] Hwang, I. et al. (2023), Lowest-low Fertility and Super-aged Society: Causes and Impacts of the Extreme Population Structure, and Policy Options, https://www.bok.or.kr/imerEng/bbs/B0000519/view.do?menuNo=600379&nttId=10085155.

[37] Hwang, J. (2023), “Later, Fewer, None? Recent Trends in Cohort Fertility in South Korea”, Demography, Vol. 60/2, pp. 563-582, https://doi.org/10.1215/00703370-10585316.

[126] ILO (2024), World social protection report 2024-26, International Labor Organization, https://doi.org/10.54394/zmdk5543.

[129] ILO (2023), Women and men in the informal economy: A statistical update, International Labor Organization, https://www.ilo.org/publications/women-and-men-informal-economy-statistical-update.

[83] Ishida, H. et al. (2017), Leaving Parental Home, Family Formation, Educational Insurance, and Attitudes toward Crisis: The Results of the Japanese Life Course Panel Survey (JLPS) 2016, https://csrda.iss.u-tokyo.ac.jp/panel/dp/PanelDP_101.pdf.

[168] Jenkins, L. (2020), 1 in 4 Childless Adults Say Climate Change Has Factored Into Their Reproductive Decisions, https://morningconsult.com/2020/09/28/adults-children-climate-change-polling/.

[135] Jeong, K. et al. (2022), “The relationship between changes in the korean fertility rate and policies to encourage fertility”, BMC Public Health, Vol. 22/1, https://doi.org/10.1186/s12889-022-14722-4.

[96] Jia, F. (ed.) (2023), “Climate change, mental health, and reproductive decision-making: A systematic review”, PLOS Climate, Vol. 2/11, p. e0000236, https://doi.org/10.1371/journal.pclm.0000236.

[153] Jones, G. (2019), “Ultra-low fertility in East Asia: policy responses and challenges”, Asian Population Studies, Vol. 15/2, pp. 131-149, https://doi.org/10.1080/17441730.2019.1594656.

[110] Judger, M., B. Baffour and Z. Zhao (2021), “Recent fertility changes in Mongolia: what can we learn from examining tempo-adjusted fertility?”, Asian Population Studies, Vol. 17/2, pp. 162-180, https://doi.org/10.1080/17441730.2021.1882097.

[14] Jung, M. and S. Lee (2023), “Subnational variations in births and marriages during the COVID-19 pandemic in South Korea”, Demographic Research, pp. 867-882, https://doi.org/10.4054/DemRes.2023.48.30 (accessed on  July 2024).

[127] Jung, Y., Y. Jang and E. Park (2024), “Impact of parental leave system on the childbirth plan among working married women: a three-year follow-up study of the Korean longitudinal survey of women and families”, BMC Pregnancy and Childbirth, Vol. 24/1, https://doi.org/10.1186/s12884-024-06286-5.

[31] Katagiri, Y. et al. (2023), “Assisted reproductive technology in Japan: A summary report for 2021 by the Ethics Committee of the Japan Society of Obstetrics and Gynecology”, Reproductive Medicine and Biology, Vol. 23/1, https://doi.org/10.1002/rmb2.12552.

[138] Kim, J. and C. Sparks (2019), The influence of housing on family size in South Korea: Unstable housing and parity specific risk, Center for Open Science, https://doi.org/10.31235/osf.io/89gcu.

[55] Kleven, H. et al. (2019), “Child Penalties across Countries: Evidence and Explanations”, AEA Papers and Proceedings, Vol. 109, pp. 122-126, https://doi.org/10.1257/pandp.20191078.

[132] KOSIS (2024), Total parental leave users (based on start date), https://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_CC2020D001&vw_cd=MT_ETITLE&list_id=D_002&scrId=&seqNo=&language=en&lang_mode=en&obj_var_id=&itm_id=&conn_path=MT_ETITLE&path=Labor%2520%253E%2520Parental%2520Leave%2520Statistics.

[166] Lebano, A. and L. Jamieson (2020), “Childbearing in Italy and Spain: Postponement Narratives”, Population and Development Review, Vol. 41/1, pp. 121-144, https://doi.org/10.1111/padr.12313.

[159] Lee, S. and E. al (2018), Changes in Family Attitudes and Behaviors in East Asia, Korea Institute for Health and Social Affairs, http://www.kihasa.re.kr.

[133] Lee, Y. (2022), “Is Leave for Fathers Pronatalist? A Mixed-Methods Study of the Impact of Fathers’ Uptake of Parental Leave on Couples’ Childbearing Intentions in South Korea”, Population Research and Policy Review, Vol. 41/4, pp. 1471-1500, https://doi.org/10.1007/s11113-022-09697-4.

[157] Le, H. et al. (2020), “Work–life balance in Asia: A systematic review”, Human Resource Management Review, Vol. 30/4, p. 100766, https://doi.org/10.1016/j.hrmr.2020.100766.

[27] Lindberg, L., J. Santelli and S. Desai (2018), “Changing Patterns of Contraceptive Use and the Decline in Rates of Pregnancy and Birth Among U.S. Adolescents, 2007–2014”, Journal of Adolescent Health, Vol. 63/2, pp. 253-256, https://doi.org/10.1016/j.jadohealth.2018.05.017.

[79] Liu, S. and K. Hynes (2012), “Are difficulties balancing work and family associated with subsequent fertility?”, Family Relations, Vol. 61/1, https://doi.org/10.1111/j.1741-3729.2011.00677.x.

[16] Li, Z. and S. Qian (2023), “The impact of COVID-19 on the intention of third-child in China: an empirical analysis based on survey data”, BMC Public Health, Vol. 23/1, https://doi.org/10.1186/s12889-023-15944-w.

[121] Magda, I. et al. (2019), “Family 500+” - program evaluation and proposed changes, https://for.org.pl/en/publications/for-reports/report-family-500-program-evaluation-and-proposed-changes.

[77] Manatu Wahine - Ministry of Women (2024), The Gender Pay Gap, https://www.women.govt.nz/women-and-work/gender-pay-gap.

[78] Maralani, V. and S. Stabler (2018), “Intensive Parenting: Fertility and Breastfeeding Duration in the United States”, Demography, Vol. 55/5, pp. 1681-1704, https://doi.org/10.1007/s13524-018-0710-7.

[158] Mary Daly, B. (ed.) (2023), Family change in the context of social changes in Asia, Oxford University Press, https://global.oup.com/academic/product/the-oxford-handbook-of-family-policy-over-the-life-course-9780197518151?cc=fr&lang=en&.

[4] Maslow, A. (1943), “A theory of human motivation.”, Psychological Review, Vol. 50/4, pp. 370-396, https://doi.org/10.1037/h0054346.

[154] Masuda, M. (2016), “Educational Support/Burden and Fertility in Local Governments”, NIER Discussion Paper Series, 増田幹人, "地方自治体における教育支援・負担と出生率", NIER Discussion Paper Series, pp. 1-13, https://www.nier.go.jp/05_kenkyu_seika/pdf_seika/h28/masuda_2.pdf.

[125] Matsuda, S. (2019), “Research on the effects of childcare support measures on childbearing behavior using vignette surveys”, Journal of population studies, 松田 茂樹, 2019, "ヴィネット調査を用いた子育て支援策が出生行動に与える効果の研究", "人口学研究”５５, pp. p.41-53, https://doi.org/10.24454/jps.1902004.

[131] Ministry of Health, Labor and Work, Japan (2024), Basic Survey of Gender Equality in Employment Management, Ministry of Health, Labour and Welfare (in Japanese), https://www.mhlw.go.jp/toukei/list/71-23.html.

[137] Mizutani, N. (2012), “Impact of Housing Price Changes on Births”, Japanese Journal of Research on Household Economics, 水谷 徳子, 住宅価格の変化が出産に与える影響’, 季刊家計経済研究, pp. 25-34, https://kakeiken.jp/old_kakeiken/jp/journal/jjrhe/pdf/96/096_04.pdf.

[84] Moribe, H. et al. (2015), “Impact of Working Hours on Fertility”, Inter-university Seminar for the future of Japan, 守部晴香, 筒井亮太, 平野慶, 水野七帆. "労働時間が出生率に与える影響", p. 48, http://www.isfj.net/article_search.html#byYear.

[74] Mugiyama, R. (2017), “Employment History and Transition to Marriage: Different Effect of Employment Status, Occupation, Firm Size, and Associated Changes According to Gender”, Kazoku syakaigaku kenkyu, 麦山 亮太, "職業経歴と結婚への移行――雇用形態・職種・企業規模と地位変化の効果における男女差", 家族社会学研究, pp. 129-141, https://www.jstage.jst.go.jp/article/jjoffamilysociology/29/2/29_129/_article/-char/ja/.

[165] Mynarska, M. and J. Rytel (2022), “Childbearing motivation at the onset of emerging adulthood”, Journal of Youth Studies, https://doi.org/10.1080/13676261.2022.2080536.

[32] Newman JE, P. (2023), Assisted reproductive technology in Australia and New Zealand 2021, University of New South Wales, https://www.unsw.edu.au/content/dam/pdfs/research/2023-12-npesu/2024-01-Assisted-Reproductive-Technology-in-Australia-and-New-Zealand-2021.pdf.

[142] NIPSSR (2023), Marriage and Childbirth in Japan Today: The Sixteenth Japanese National Fertility Survey, 2021, National Institute for Population and Social Security Reseach, https://www.ipss.go.jp/ps-doukou/j/doukou16/doukou16_gaiyo.asp.

[141] NIPSSR (2022), Eight Annual Household Survey (第８回世帯動態調査), National Institute for Population and Social Security Reseach, https://www.ipss.go.jp/ps-dotai/j/DOTAI8/houkoku/Hhoukoku.pdf.

[71] Nishikitani, M., M. Inoue and S. Tsurugano (2018), “Nonregular Employment in a Society with a Decreasing Birthrate: Workers’ Marriage, Childbirth, and Childcare”, Nippon Eiseigaku Zasshi (Japanese Journal of Hygiene), Vol. 73/2, pp. 215-224, https://doi.org/10.1265/jjh.73.215.

[117] Nishimura and Asahi (2024), Tax Allowances for 2023 and 2024 - Thailand, https://www.nishimura.com/en/knowledge/publications/tax-allowances-for-2023-and-2024.

[75] OECD (2024), Gender Wage Gap: OECD Dashboard on Gender Gaps, https://www.oecd.org/en/data/dashboards/gender-dashboard/comparison.html.

[72] OECD (2024), OECD Economic Surveys: Japan 2024, OECD Publishing, Paris, https://doi.org/10.1787/41e807f9-en.

[73] OECD (2024), OECD Economic Surveys: Korea 2024, OECD Publishing, Paris, https://doi.org/10.1787/c243e16a-en.

[11] OECD (2024), OECD Family Database, https://www.oecd.org/els/family/database.htm.

[116] OECD (2024), OECD Tax-Benefit Models, https://www.oecd.org/en/data/tools/oecd-calculator-of-taxes-and-benefits.html.

[6] OECD (2024), Society at a Glance 2024: OECD Social Indicators, OECD Publishing, Paris, https://doi.org/10.1787/918d8db3-en.

[54] OECD (2023), Education at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/e13bef63-en.

[86] OECD (2023), Exploring Norway’s Fertility, Work, and Family Policy Trends, OECD Publishing, Paris, https://doi.org/10.1787/f0c7bddf-en.

[44] OECD (2023), Health at a Glance 2023: OECD Indicators, OECD Publishing, Paris, https://doi.org/10.1787/7a7afb35-en.

[47] OECD (2023), International Migration Outlook 2023, OECD Publishing, Paris, https://doi.org/10.1787/b0f40584-en.

[7] OECD (2023), Joining Forces for Gender Equality: What is Holding us Back?, OECD Publishing, Paris, https://doi.org/10.1787/67d48024-en.

[90] OECD (2023), Main Findings from the 2022 OECD Risks that Matter Survey, OECD Publishing, Paris, https://doi.org/10.1787/70aea928-en.

[8] OECD (2023), OECD Affordable Housing Database, https://www.oecd.org/housing/data/affordable-housing-database/.

[56] OECD (2022), The Role of Firms in the Gender Wage Gap in Germany, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/e8623d6f-en.

[145] OECD (2021), Brick by Brick: Building Better Housing Policies, OECD Publishing, Paris, https://doi.org/10.1787/b453b043-en.

[146] OECD (2021), Building for a better tomorrow: Policies to make housing more affordable, OECD Publishing, Paris, https://www.oecd.org/en/publications/2021/01/building-for-a-better-tomorrow-policies-to-make-housing-more-affordable_51f68a86.html.

[147] OECD (2020), Social housing: A key part of past and future housing policy, OECD Publishing, Paris, https://www.oecd.org/en/publications/2020/10/social-housing-a-key-part-of-past-and-future-housing-policy_ef96d6d9.html.

[130] OECD (2019), Rejuvenating Korea: Policies for a Changing Society, Gender Equality at Work, OECD Publishing, Paris, https://doi.org/10.1787/c5eed747-en.

[103] OECD (2011), Doing Better for Families, OECD Publishing, Paris, https://doi.org/10.1787/9789264098732-en.

[102] OECD (2007), Babies and Bosses - Reconciling Work and Family Life: A Synthesis of Findings for OECD Countries, OECD Publishing, Paris, https://doi.org/10.1787/9789264032477-en.

[36] OECD Korea Policy Centre (2024), Family Database in the Asia-Pacific Region, https://oecdkorea.org/eng/product/familyDatabase_view.asp?BRDNUM=1985.

[45] OECD/WHO (2022), Health at a Glance: Asia/Pacific 2022: Measuring Progress Towards Universal Health Coverage, OECD Publishing, Paris, https://doi.org/10.1787/c7467f62-en.

[52] Oshio, T. (2019), “Is a positive association between female employment and fertility still spurious in developed countries?”, Demographic Research, Vol. 41, pp. 1277-1288, https://doi.org/10.4054/demres.2019.41.45.

[49] Ostry, J. et al. (2018), Economic Gains From Gender Inclusion New Mechanisms New Evidence, International Monetary Fund, https://www.imf.org/en/Publications/Staff-Discussion-Notes/Issues/2018/10/09/Economic-Gains-From-Gender-Inclusion-New-Mechanisms-New-Evidence-45543.

[93] Pew Research Center (2023), International Question Search - Pew Global Attitudes & Trends Question Database, https://www.pewresearch.org/global/question-search.

[12] Pomar, L. et al. (2022), “Impact of the first wave of the COVID-19 pandemic on birth rates in Europe: a time series analysis in 24 countries”, Human Reproduction, https://doi.org/10.1093/humrep/deac215.

[118] PWC (2024), Indonesian Pocket Tax Book 2024, https://www.pwc.com/id/en/pocket-tax-book/english/pocket-tax-book-2024.pdf.

[160] Raymo, J. (2022), “The second demographic transition in Japan: a review of the evidence”, China Population and Development Studies, Vol. 6/3, pp. 267-287, https://doi.org/10.1007/s42379-022-00116-x.

[41] Reuters (2024), “China’s population drops for second year, with record low birth rate”, https://www.reuters.com/world/china/chinas-population-drops-2nd-year-raises-long-term-growth-concerns-2024-01-17/.

[76] Risse, L. (2024), Australia’s gender pay gap has hit a record low – but we still have work to do, https://theconversation.com/australias-gender-pay-gap-has-hit-a-record-low-but-we-still-have-work-to-do-236894 (accessed on  2024).

[100] Robinson, W. and J. Ross (eds.) (2007), The Global Planning Revolution: Three Decades of Population Policies and Programs, https://documents1.worldbank.org/curated/ru/259541468177850467/pdf/405350Familiy0101OFFICIAL0USE0ONLY1.pdf.

[63] Ryu, Y. and H. Inoue (2023), “Is it still true in Japan that the common belief that an increase in income and women’s participation in society hinders a rise in the birth rate?”, Kyushu-sangyo-daigaku Keizaigakkai, 柳 永珍, 井上 寛, 日本では所得上昇と女性社会進出が出生率増加を阻むという通説がまだ通じるのか。 : 『The Economic of Fertility: A New Era』のアプローチの適用, pp. 63-80, http://hdl.handle.net/11178/8354.

[143] Saguin, K. (2021), No Flat, No Child in Singapore: Cointegration Analysis of Housing, Income, and Fertility, https://www.adb.org/publications/no-flat-no-child-singapore-analysis-housing-income-fertility.

[65] Seltzer, N. (2019), “Beyond the Great Recession: Labor Market Polarization and Ongoing Fertility Decline in the United States”, Demography, Vol. 56/4, pp. 1463-1493, https://doi.org/10.1007/s13524-019-00790-6.

[23] Skakkebaek, N. et al. (2019), “Populations, decreasing fertility, and reproductive health”, The Lancet, Vol. 393/10180, pp. 1500-1501, https://doi.org/10.1016/s0140-6736(19)30690-7.

[43] Skirbekk, V. (2022), Decline and Prosper!, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-030-91611-4.

[18] Sobotka, T. (2021), “World’s Highest Childlessness Levels in East Asia”, Population et Sociétés, Vol. n° 595, https://doi.org/10.3917/popsoc.595.0001.

[3] Sobotka, T. (2008), “Overview Chapter 6: The diverse faces of the Second Demographic Transition in Europe”, Demographic Research, Vol. 19, pp. 171-224, https://doi.org/10.4054/DemRes.2008.19.8.

[13] Sobotka, T. et al. (2023), “Pandemic Roller‐Coaster? Birth Trends in Higher‐Income Countries During the COVID‐19 Pandemic”, Population and Development Review, https://doi.org/10.1111/padr.12544.

[20] Sorchik et al (2019), Fertility trends in Pacific Island Countries and Territories, https://www.spc.int/updates/blog/2019/07/fertility-trends-in-pacific-island-countries-and-territories.

[114] Spoorenberg, T. (2015), “Explaining recent fertility increase in Central Asia”, Asian Population Studies, Vol. 11/2, pp. 115-133, https://doi.org/10.1080/17441730.2015.1027275.

[109] Spoorenberg, T. and B. Enkhtsetseg (2009), “Future low fertility prospects in Mongolia? An evaluation of the factors that support having a child”, Journal of Population Research, Vol. 26/3, pp. 227-247, https://doi.org/10.1007/s12546-009-9017-2.

[30] Sundhedsdatastyrelsen (2021), Assisteret reproduktion 2019, https://sundhedsdatastyrelsen.dk/da/tal-og-analyser/analyser-og-rapporter/sygdomme-og-behandlinger/assisteret-reproduktion.

[119] Syamsulhakim, E. and N. Khadijah (2021), Graduating from a Conditional Cash Transfer Program in Indonesia: Results of a Household Survey of Prosperous-Independent Graduates of the Family Hope Program in 2020, World Bank, https://hdl.handle.net/10986/36784.

[150] Szabó-Morvai, Á. et al. (2019), “Evaluation of family policy measures and their impact on fertility”, HÉTFA Research Institute, https://hetfa.hu/wp-content/uploads/2019/12/2019_fertilitymodels-family-policy.pdf.

[34] The Economist (2023), Fertility policy and practice; the APAC Fertility and Family Scorecard, https://impact.economist.com/perspectives/health/fertility-policy-and-practice-apac-fertility-and-family-scorecard.

[155] The Lauder Institute (2022), China’s Three-Child Policy: Passive Permission vs. Active Incentive, Wharton, University of Pennsylvania, https://lauder.wharton.upenn.edu/wp-content/uploads/2022/02/Chinas-Three-Child-Policy-GBIR2022.pdf.

[105] Thévenon, O. (2011), “Family Policies in OECD Countries: A Comparative Analysis”, Population and Development Review, Vol. 37/1, pp. 57-87, https://doi.org/10.1111/j.1728-4457.2011.00390.x.

[26] Tridenti, G. and C. Vezzani (2022), “035 What to do when it fails? Teenage pregnancy in Europe”, European Journal of Obstetrics & Gynecology and Reproductive Biology, Vol. 273, pp. e13-e14, https://doi.org/10.1016/j.ejogrb.2022.02.064.

[60] Trimarchi, A. and J. Van Bavel (2017), “Education and the Transition to Fatherhood: The Role of Selection Into Union”, Demography, Vol. 54/1, pp. 119-144, https://doi.org/10.1007/s13524-016-0533-3.

[164] Tsutsui, J. (2019), “Factors Influencing the Fertility Decline in Japan”, in Work and Family in Japanese Society, SpringerBriefs in Population Studies, Springer Singapore, Singapore, https://doi.org/10.1007/978-981-13-2496-3_2.

[22] Turner, K. et al. (2020), “Male Infertility is a Women’s Health Issue—Research and Clinical Evaluation of Male Infertility Is Needed”, Cells, Vol. 9/4, p. 990, https://doi.org/10.3390/cells9040990.

[42] UN DESA (2023), UN DESA Policy Brief No. 153: India overtakes China as the world’s most populous country, https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/PB153.pdf.

[50] UN DESA (2020), World Fertility and Family Planning 2020: Highlights, https://www.un.org/en/development/desa/population/publications/pdf/family/World_Fertility_and_Family_Planning_2020_Highlights.pdf.

[35] UNFPA (2021), Understanding and Addressing Adolescent Pregnancy, UNFPA, https://asiapacific.unfpa.org/en/publications/understanding-and-addressing-adolescent-pregnancy.

[120] UNICEF China (2023), Family policies in China, https://www.unicef.cn/media/25321/file/FAMILY%20POLICIES%20IN%20CHINA.pdf.

[108] UNICEF Mongolia (2023), Child money for every child, https://www.unicef.org/mongolia/stories/child-money-every-child.

[19] United Nations (2022), Female mean age of childbearing (years), https://data.un.org/Data.aspx?d=PopDiv&f=variableID%3A195.

[91] Vignoli, D. et al. (2021), “Economic Uncertainty and Fertility Intentions: The Causal Effect of Narratives of the Future”, DISIA Working Paper 5.

[66] Vignoli, D., V. Tocchioni and A. Mattei (2020), “The impact of job uncertainty on first-birth postponement”, Advances in Life Course Research, Vol. 45, p. 100308, https://doi.org/10.1016/j.alcr.2019.100308.

[92] WEF (2024), The Global Risks Report 2024, https://www3.weforum.org/docs/WEF_The_Global_Risks_Report_2024.pdf.

[94] WMO (2024), State of the climate in south west pacific 2023, https://library.wmo.int/records/item/68995-state-of-the-climate-in-south-west-pacific-2023.

[113] World Bank (2024), Europe and Central Asia Economic Update, Spring 2024: Unleashing the Power of the Private Sector, https://hdl.handle.net/10986/41214.

[111] Worldometer (2024), Central Asia Population, https://www.worldometers.info/world-population/central-asia-population/ (accessed on 25 September 2024).

[156] WVS (2022), World Values Survey Wave 7, https://www.worldvaluessurvey.org/WVSDocumentationWV7.jsp.

[67] Yoo., J. (2022), Comparative analysis of marriage and birth rates according to employee characteristics, http://www.keri.org/web/www/research_0201.

[33] YoonAng (2021), This year, 1 in 8 newborns are born through ’infertility treatment’... Tripled in 2 years [출처:중앙일보], https://www.joongang.co.kr/article/24104933.

[161] Yu, J. and Y. Xie (2022), “Is there a Chinese pattern of the second demographic transition?”, China Population and Development Studies, Vol. 6/3, pp. 237-266, https://doi.org/10.1007/s42379-022-00113-0.

[151] Zhang, G. et al. (2023), “Policy-based initiatives on promoting China’s affordable housing: Challenges and opportunities”, Developments in the Built Environment, Vol. 16, p. 100222, https://doi.org/10.1016/j.dibe.2023.100222.

Annex 1.A. Supplementary figures and tables

Annex Figure 1.A.1. Births, deaths, net migration, and population, 1960‑2021, selected countries, in millions

 

Note: Net migration is the number of immigrants minus the number of emigrants. Migration is defined here as a change in usual residence over the past 12 months.

Source: Calculations from United Nations, World Populations Prospects – 2022 Revisions.

Statlink

Annex Table 1.A.1. Major policies changes in population policy across selected Asian countries

Decade	China	India	Indonesia	Japan	Korea	Mongolia	Thailand
1950s		Introduction of population control: aiming for 2 children per woman.	.	Introduction of population control: promotion of family planning.
1960s	Establishment of the Family Planning Commission.				Introduction of population control: family planning in the five‑year economic development plan.	Introduction of pronatalist policy, e.g. benefits for large families – prohibition of contraceptives.
1970s	Introduction of population control: aiming for two children per women at most.	Mass sterilisation camps: millions of men were sterilised e.g. around 18.5 million from 1974 to 1979.	Introduction of population control: Nat. Population and Family Planning Board (BKKBN).	Policy advocated no more than two children per woman.	Abortion was legalised, policy aimed for the TFR to fall to replacement level by 1990.	Easing of pronatalist policy: selected permission to use contraceptives (e.g. related to age or health).	Introduction of population control – the national Family planning programme.
1980s	One child policy. In rural areas, couples whose first child was a girl were allowed a 2nd child.					Abortion and contraceptive use were fully legalised
1990s		Enactment of the Pre‑natal Diagnostic Techniques Act against gender-selective abortion.		Introduction of low fertility countermeasures: the first “Angel Plan”, which included parental leave.
2000s			Family planning to counter variation in contraceptive use across the country	Increase of child allowance	Introduction of low fertility countermeasures, including parental leave.	A shift back to pronatalist policy: Introduction of the Child Money Program	Five‑year plan aimed to maintain the TFR around replacement level.
2010s	Easing of population control, by stepwise relaxation of rules towards allowing couples to have two children.	Awareness campaign on sex-discrimination to address the falling child-sex-ratio. Maternity leave extended to 6 months.		Extension of childcare support by increasing consumption tax	Extension of parental leave and introduction of free childcare and child allowance.	Home‑care allowance for children <3. Allowances for single parents with three+ children <18.	Maternity leave was expanded from 90 days to 98 days.
2020s	A three‑child policy. Plans to expand childcare services, parental leave, and housing support.	Reinforcement of Population Control: a two‑child policy law was introduced in some states.	Extended maternity leave from 3 to 6 months; introduction of paternity leave.	Strengthening of family support policies and inception of the Children and Family Agency.		Vision 2050: a TFR target of 3.5 by 2050. Introduction of paternity leave	Introduction of Long-Term Population Development Plan (2022‑37) to create a family-friendly policy environment.

Annex 1.B. Country information resources

China

Zhang, T. et al. (2023),”The Effect of Family Fertility Support Policies on Fertility, Their Contribution, and Policy Pathways to Fertility Improvement in OECD Countries” International Journal of Environmental Research and Public Health 20, no. 6: /1/2, https://doi.org/10.3390/ijerph20064790.

Zhai, Z. and G. Jin (2023), “China’s family planning policy and fertility transition” Chinese Journal of Sociology, 9(4), 479‑496, https://doi.org/10.1177/2057150X231205773.

The Government of the People’s Republic of China (2022), “Guidance on Further Improving and Implementing Active Birth Support Measures” (in Chinese), www.gov.cn/zhengce/zhengceku/2022-08/16/content_5705882.htm.

India

Gupte, P. R. (2017), “India: “The Emergency” and the Politics of Mass Sterilization,” Education About Asia, Volume 22:3 (Winter 2017): Demographics, Social Policy, and Asia, Part I, www.asianstudies.org/publications/eaa/archives/india-the-emergency-and-the-politics-of-mass-sterilisation/.

Harris Green, H. (2018), “The legacy of India’s quest to sterilise millions of men,” Quartz, https://qz.com/india/1414774/the-legacy-of-indias-quest-to-sterilise-millions-of-men.

Madhekar, M. et al. (2020), “An overview of the maternity benefits act in India and comparison with select countries”, www.researchgate.net/publication/343934448_AN_OVERVIEW_OF_THE_MATERNITY_BENEFITS_ACT_IN_INDIA_AND_COMPARISON_WITH_SELECT_COUNTRIES.

Sharma, D. (2014), “India’s sterilisation scandal,” The Lancet, Vol.384, December 2014, www.thelancet.com/journals/lancet/article/PIIS0140-6736(14)62224-8/fulltext.

Indonesia

UNFPA, BkkbN (2014), “Discussion Paper on Family Planning, Human Rights and Development in Indonesia Complement to the State of the World Population Report 2012”, https://indonesia.unfpa.org/sites/default/files/pub-pdf/Discussion_Paper_on_Family_Planning%2C_Human_Rights_and_Development_in_Indonesia_%28SWOP_2012%29.pdf.

Copenhagen Consensus Center, “Indonesian Perspectives Population and Demography”, https://copenhagenconsensus.com/sites/default/files/documents/indonesia_packet_population.pdf.

Japan

Committee on Future of Choice, Council on Economic and Fiscal Policy (2015) “A Future of Choice – Future Vision from Population Estimates” (in Japanese), www5.cao.go.jp/keizai-shimon/kaigi/special/future/sentaku/index.html.

Hirosima, K. (2020) “A Brief History of the Population Policy of Post-War Japan” (in Japanese), Japan Health & Human Ecology, 86(5), pp.231‑241.  https://doi.org/10.3861/kenko.86.5_231.

“Children’s Future Strategy”, (Cabinet Decision on 22 December 2023, in Japanese), www.cas.go.jp/jp/seisaku/kodomo_mirai/pdf/kakugikettei_20231222.pdf.

Children and Families Agency, “Free early childhood education and Care” (in Japanese), www.cfa.go.jp/policies/kokoseido/mushouka.

Korea

Kim, H (2003), “Population Control Policy in South Korea: Very low Fertility and Sec Ration Imbalance at Birth”, Annals of Region and Community Studies, Vol.15, pp.152‑166, https://doi.org/10.20737/jarcs.15.0_152.

Repetto. R et al. (1981), “Economic Development, Population Policy, and Demographic Transition in the Republic of Korea: Studies of the Modernization of the Republic of Korea: 1945‑75”, Council on East Asian Studies Harvard University, www.kdi.re.kr/eng/research/reportView?pub_no=95.

Choe, M. J., & Park, K. (2006), Fertility decline in South Korea: Forty years of policy-behaviour dialogue,  Korea Journal of Population Studies, 29(2), 1‑26, https://koreascience.kr/article/JAKO200601436745566.page.

Cho, N. (2000), “Policy responses to population ageing and population decline in Korea”, www.un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/unpd-egm_20/1/2_cho.pdf.

Mongolia

Spoorenberg, T (2008), “The Demographic Window, Development, and Population Policy Implications in Mongolia” Asian Population Studies, 4(2), 215‑232, https://doi.org/10.1080/17441730802247513.

Judger, M et al. (2021), “Recent fertility changes in Mongolia: what can we learn from examining tempo‑adjusted fertility?” Asian Population Studies, 17(2), 162‑180, https://doi.org/10.1080/17441730.2021.1882097

Spoorenberg, T (2015), “Reconstructing Historical Fertility Change in Mongolia: Impressive Fertility Rise before Continued Fertility Decline.” Demographic Research, vol. 33, pp. 841‑70. JSTOR, www.jstor.org/stable/26332006. Accessed 8 July 2024.

Mongolia Vision 2050, https://vision2050.gov.mn/eng/vis2.html.

Thailand

UNFPA (2011), Impact of Demographic Change in Thailand, https://thailand.unfpa.org/sites/default/files/pub-pdf/Impact-Full-Report-a-Eng.pdf.

UNICEF (2022), Family-Friendly Policies and Practices in Thailand’s Private Sector, Summary report on in-depth research, www.unicef.org/thailand/media/8361/file/Friend-friendly%20Policies%20and%20Practices%20in%20Thailand’s%20Private%20Sector%20EN.pdf.

Morakot, M (2021), “Public Policy Related to Fertility in Thailand: Past, Present and the Way Forward” International Journal of Crime, Law and Social Issues, Vol. 8, No. 1, https://ssrn.com/abstract=3897320.

Laowong, P (2023), “Thailand’s Policy Perspectives on the (Third) Demographic Dividend”, The Office of the National Economic and Social Development Council, https://ntaccounts.org/doc/repository/NTA14.Lao.pdf.

Notes

← 1.  In October 2024, Japan eliminated the income test for the child allowance, and extended coverage to all children not yet 18 years of age. The monthly payment rate is JPY 15 000 (around USD 100) for the first and second child under 3, and JPY 10 000 (around USD 70) for children 3 years and over. For the third and subsequent children, it is JPY 30 000 (around USD 200), regardless of age per month for third and subsequent children, regardless of age. (Government of Japan, 2023[172]).

← 2.  In April 2023, New Zealand provided paid leave for half a year to the primary career but leave for partners was unpaid. Australia had 20 weeks of paid parental leave, of which two weeks were earmarked for fathers. However, in Australia parental leave will gradually be extended and by 1 July 2026 the primary carer will be entitled to 26 weeks of leave, while the recently introduced Dad and Partner pay will be extended to 4 weeks of paid leave (Australian Government, 2023[171]).