Maintitle

Copyright

José Manuel Salazar-Xirinachs

Executive Secretary

Javier Medina Vásquez

Deputy Executive Secretary a.i.

Simone Cecchini

Chief, Latin American and Caribbean Demographic Centre

(CELADE)-Population Division of ECLAC

Sally Shaw

Chief, Documents and Publications Division

This publication was prepared by Helena Cruz Castanheira, Gabriel Mendes Borges, Jorge Rodríguez Vignoli and Yanitza Nicole Flórez Rodríguez, under the supervision of Fabiana Del Popolo, Chief of the Demography and Population Information Area of the Latin American and Caribbean Demographic Centre (CELADE)-Population Division of the Economic Commission for Latin America and the Caribbean (ECLAC), and Simone Cecchini, Chief of CELADE-Population Division of ECLAC.

The authors would like to thank the Statistics Division of ECLAC for the valuable support in processing the household survey microdata, and Amalia Plana and Zulma Sosa, also of CELADE-Population Division of ECLAC, for their contributions.

Support in the preparation of this publication was provided by the 2025 ECLAC/United Nations Population Fund (UNFPA) Regional Programme on Population and Development.

The United Nations and the countries it represents assume no responsibility for the content of links to external sites in this publication.

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Latin American and Caribbean Demographic Centre (CELADE)-Population Division of ECLAC

Email: celade@cepal.org

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This publication should be cited as: Economic Commission for Latin America and the Caribbean. (2025). Demographic Observatory 2025 (LC/PUB.2025/19-P).

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Contents

Maintitle

Copyright

Foreword

Introduction

I. The fall in fertility in the context of the first demographic transition

II. Post-transitional demographic regimes in the countries of the region

III. The effect of postponement on fertility rates in the region

IV. Socioeconomic differentials in fertility and their proximate determinants

V. Public programmes and policies in a low-fertility context

VI. Conclusions

Bibliography

Foreword

The Latin American and Caribbean Demographic Centre (CELADE)-Population Division of the Economic Commission for Latin America and the Caribbean (ECLAC) is pleased to present the 2025 edition of the Demographic Observatory, which offers an in-depth analysis of low fertility rates in the region. The aim is to describe the current trends of low fertility across the countries and territories of Latin America and the Caribbean, on the basis of demographic estimates drawn from various data sources —such as vital statistics, censuses and household surveys— as well as recent scientific literature.

This edition includes an analysis of the historic decline in fertility in Latin America and the Caribbean, with a focus on recent changes. The fertility transition has varied considerably across countries of the region. In Argentina and Uruguay, for example, fertility began to decline in the late nineteenth and early twentieth centuries, falling to low levels in the 1960s. The transition began later but occurred faster in Brazil, Chile, Colombia and Mexico, while it was more gradual in Guatemala, Honduras and the Plurinational State of Bolivia. Since 2015, the region’s fertility rate has fallen below the replacement level, with current averages of 1.8 children per woman in Latin America and 1.5 children per woman in the Caribbean.

In addition to the overall decrease in the total fertility rate, significant changes have occurred with regard to age structure. The prolonged period of rejuvenation observed up to the early twenty-first century was followed by postponement of childbearing over the past two decades. This means that during the initial phase of the transition, there were fewer higher-order births (third child or more) and fertility rates among women over the age of 20 decreased notably. Subsequently, beginning in 2014 for the most part, fertility among adolescents (ages 15–19) declined noticeably. This lag in the lowering of adolescent fertility gave rise to a “bimodal” pattern in certain countries, which experienced high fertility among adolescents at the same time as increased births among women of older reproductive ages.

The postponement of childbearing has played a key role in the decrease to low fertility rates in developed countries. This “postponement transition” is seen as a response to economic uncertainty and the expansion of higher education. Accordingly, in this edition of the Demographic Observatory, the effect of the postponement of childbearing on the period total fertility rate (or “tempo effect”) is measured. However, it should be noted that the sharp drop in fertility in Latin America and the Caribbean in recent years is closely associated with decreasing fertility among adolescent and young women.

The shift in population age structure towards increasingly ageing societies, as a result of the sustained decrease in fertility, affects all areas of public policy and leads to a considerable rise in demand for long-term care services. In addition, high levels of inequality in socioeconomic conditions and in access to public goods and services in the region present further challenges. This study therefore underscores the importance of demographic phenomena in building more productive, inclusive and sustainable societies.

The analysis presented in this edition of the Demographic Observatory draws on selected indicators from the 2024 revision of the population estimates and projections for 47 countries and territories of Latin America and the Caribbean. These estimates and projections, prepared jointly with the United Nations Population Division, have been updated to incorporate age- and sex-disaggregated census data from the 2020 round for Argentina, Brazil, the Dominican Republic, Ecuador and Panama, as well as data from demographic and health surveys and vital statistics up to 2023. In addition to the results of the estimates and projections, the analysis includes indicators from recent household surveys and population and housing censuses conducted in countries across the region.

Simone Cecchini

Chief

Latin American and Caribbean Demographic Centre

(CELADE)-Population Division of ECLAC

Introduction

The demographics of Latin America and the Caribbean have undergone profound transformations, the decline in fertility being one of the most significant. Within the region’s highly uneven social, political and economic context, fertility analysis is especially important because it provides insights into underlying population dynamics and their interaction with sexual and reproductive rights and with population ageing amid great social and gender inequality.

Unlike the gradual transition towards lower fertility levels seen in Europe, the process in Latin America and the Caribbean occurred precipitously from the second half of the twentieth century onward. The rapid pace of change quickly transformed the region’s reproductive patterns, from high fertility levels falling to almost replacement level within a relatively short period of time (Economic Commission for Latin America and the Caribbean [ECLAC], 2008). This trend has accelerated in the first quarter of the twenty-first century, producing significant implications for various aspects of sustainable development, such as work, social protection, health, education and care (ECLAC, 2024b).

Despite differences among countries in the region depending on their social, economic, and cultural context, all have experienced this shift to a greater or lesser extent. The rapid drop in fertility reflects a combination of factors, including the decline in mortality; broader access to education, especially for women; increased female participation in the labour market; widespread access to modern contraceptive methods; and progress towards greater gender equality. These factors have changed reproductive preferences, expanded the possibilities for regulating fertility, and made it easier to postpone childbearing.

This transition also raises significant challenges and contradictions. While the fertility decline has been linked to expanded educational opportunities and greater female participation in the labour market, persisting structural barriers in many countries in the region make it hard to balance work and family life. Insufficient childcare services, a lack of adequate maternity and paternity leave and difficulties encountered by women in rejoining the workforce after the birth of their children combine to form an adverse milieu for starting a family without compromising professional development and financial well-being. These conditions are not a disincentive to motherhood; they also accentuate gender inequalities by relegating women to a double burden of work, limiting their autonomy and opportunities for advancement.

Adolescent pregnancy is another important topic: although it has decreased, it remains a significant issue in many countries in the region, which still has the second highest rate in the world, after Africa. Adolescent pregnancy —associated with lack of access to comprehensive sexuality education, socioeconomic inequalities and barriers to accessing reproductive health services— significantly limits adolescents’ educational, employment and economic opportunities, perpetuating cycles of poverty and inequality and imposing heavy social costs (United Nations Population Fund [UNFPA], 2025).

The fall in fertility has had a significant impact on the size and structure of the population in Latin America and the Caribbean. The decline in births has contributed to a drop in the proportion of young people, shrinking the base of the population pyramid. This has facilitated the onset of the demographic dividend, a period in which the proportion of the working-age population peaks relative to dependants. As fertility continues to decline and life expectancy increases, the region faces accelerated population ageing, which poses significant challenges, such as the sustainability of pension and health systems for the growing older population. It also creates opportunities, such as the possibility of improving the quality of education for a decreasing number of children, adolescents and young people. In terms of population size, the transition to lower fertility levels has also slowed the pace of total population growth.

The United Nations Population Division and the Latin American and Caribbean Demographic Centre (CELADE)-Population Division of the Economic Commission for Latin America and the Caribbean (ECLAC) have made it a priority to study fertility and fertility projections in Latin America and the Caribbean. They have produced ongoing analyses based mainly on time-period measures, such as the total fertility rate (TFR) or specific fertility rates, which offer a snapshot of fertility levels at a given time.

This edition of the Demographic Observatory offers an in-depth exploration of the subject of low fertility in Latin America and the Caribbean and its recent trends, differences in fertility between regions, countries and socioeconomic contents and the factors associated with the changes seen. The document has six chapters.

Chapter I examines the decline in fertility in the region since 1950, comparing it with the pattern in other parts of the world, within the framework of the first demographic transition. It describes the effect of this transition on the age structure of the population and its impact on the population dependency ratio. It also analyses the main theories explaining the decline in fertility within the framework of the first demographic transition, and the key factors discussed in the literature. Lastly, it summarizes the changes in the age profile of fertility in Latin America and the Caribbean overall, drawing attention to the significant changes that have occurred in specific fertility rates in the region over the past 70 years.

Chapter II centres its analysis on the countries in the region, exploring differentials between them and the factors associated with below-replacement fertility. It also considers ultra-low fertility and the theories that seek to explain it, the postponement of childbearing, and the increase in the proportion of women with no children or a single child, reflecting significant changes in reproductive trajectories. Finally, it analyses age-specific fertility variations and how these transformations take different forms from one country to another.

Chapter III addresses the effect of the postponement of maternity on fertility rates in the region, analysing cohort fertility and using demographic techniques to measure the impact of this postponement on the period total fertility rate (tempo effect). This analysis enables a deeper understanding of the impacts of maternity postponement in the region.

Chapter IV deals with reproductive inequality, examining socioeconomic differentials in the level and timing of total fertility and early fertility. It also presents socioeconomic differentials of intermediate variables and their association with differentials in the level and timing of fertility. Lastly, it sets forth differentials in reproductive ideals and observed fertility, and provides evidence to underpin the implementation of specific policies to ensure reproductive rights in the various social groups and territorial contexts.

Chapter V examines programmes and policies aimed at families in a low-fertility context, looking at current family policies in the region and referring to the main international and regional instruments that address this issue, such as the Montevideo Consensus on Population and Development and the 2030 Agenda for Sustainable Development. These instruments promote universal access to sexual and reproductive health services, with an emphasis on preventing adolescent pregnancy, and treat gender equality as a cross-cutting theme guiding policymaking. Progress in this sphere is essential to ensuring informed decisions —to enable women to have the desired number of children over their lifetimes— reducing inequalities and promoting sustainable development.

Lastly, chapter VI offers some conclusions, with key considerations regarding the decline in fertility in the region, drawing attention to the context of persistent inequalities and limited welfare structures, and offering recommendations on public policies and on strengthening statistical data to better monitor the new demographic reality of the countries in the region.

I. The fall in fertility in the context of the first demographic transition

This chapter provides an overview of the fertility decline in the region and the demographic transition theories that account for it. The first of the chapter’s five sections addresses the historical decline in fertility, comparing the situation in Latin America and the Caribbean with that of other world regions, and explores the differentials in fertility decline between countries. The second section analyses the impact of the decline in births on the population structure, describing how the steady decline in fertility has changed the shape of the pyramid. The third section then reviews the main theories of the fertility decline in the context of the first demographic transition. The fourth addresses the factors associated with the fertility decline and its convergence toward replacement level, including its correlation with the human development index (HDI), the expansion of education, urbanization, women’s increasing participation in the labour market, changes in families’ reproductive preferences, and access to contraceptive methods. Lastly, the fifth section examines transformations in the age profile of fertility, looking at changes in specific fertility rates and in the average age of fertility.

A. Fertility decline in the region from a comparative perspective

Fertility began to decline in Latin America and the Caribbean around the 1960s, within the framework of the demographic transition.[1] The demographic transition is a process of change in the characteristics of a population over time, with changes in both birth and death rates. Initially, pre-transitional societies have high birth and death rates, low life expectancy, low population growth and a predominantly young population. As improvements come about in public health, living conditions and access to education, mortality begins to decline, leading to rapid population growth. Later, fertility also declines, which over time, added to falling mortality, gives way to post-transitional societies, with low birth and death rates, longer life expectancy and population ageing. This process has transformed economic and social structures worldwide (Dyson, 2010), influencing, for example, labour markets and the organization of welfare systems.

Globally, the transition began around 1800 in North-West Europe with a fall in mortality, mainly infant mortality (fertility began to fall around 1870), while in developing countries mortality began to fall in the early twentieth century, and much more rapidly after World War II (Lee, 2003). In most countries, mortality fell before fertility; however, fertility started to decline before or at the same time as mortality in some places (e.g. in France, the United States and half of the territorial entities of Germany) (Lee, 2003; Dyson, 2010).

In Latin America, mortality began to come down significantly and steadily in the 1930s, as infectious, parasitic and respiratory diseases declined in the child population (Arriaga and Davis, 1969), and this contributed to population growth. Later, in the 1960s, fertility began to drop steadily, resulting in slowing population growth (see figure I.1), which shows the population growth rate for Latin America and the Caribbean. Although the fall in the birth rate did not begin simultaneously across the region, the fertility transition was under way in all the countries by the 1980s (Economic Commission for Latin America and the Caribbean [ECLAC], 2023a).

Figure I.1

Latin America and the Caribbean: crude birth and death rates and annual population growth, 1950–2024

(Per 1,000 persons)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Note: The growth rate refers to the growth rate of the total population, which includes the effects of the migratory balance. The vegetative or natural growth rate (birth rate minus death rate) is slightly higher than the total rate, because the region experienced a negative migratory balance over the entire period.

The changes in mortality and fertility led to population growth increasing at the beginning of the transition and thereafter falling steadily, a process that has continued over the past 60 years (see figure I.1). The declines in mortality and, especially, in fertility also lead in the medium and long terms to population ageing, with an increase in the proportion of older persons in the population. At the regional level, population growth is projected to remain positive until 2053. By 2024, population growth had turned negative in Cuba and Uruguay, in Latin America, and in eight countries and territories in the Caribbean: Dominica, Guadeloupe, Jamaica, Martinique, Montserrat, Puerto Rico, Saint Vincent and the Grenadines, and the United States Virgin Islands.[2]

The demographic transition occurred rapidly in Latin America and the Caribbean, compared to Europe, taking the region from high levels of mortality and fertility to low levels of both rates today. The drop in fertility in the region is unprecedented: the total fertility rate[3] fell by half between 1950 and 1995, from 5.8 to 2.9 children per woman. The fertility rate reached replacement level (2.1 children per woman) in 2014 and fell to 1.8 children per woman in 2024.[4] Compared with other world regions, in the 1950s and 1960s, fertility rates in Latin America and the Caribbean were exceeded only by those in Africa, where the rate was over 6 children per woman (see table I.1). However, the total fertility rate of 1.8 children per woman in 2024 is below the rates not only for Africa, but also for Asia and Oceania, and comes very close to the figure in North America (see box I.1 for an explanation of the methodology employed for United Nations fertility estimates (2024), which are used in this document).

Table I.1

World regions: total fertility rate, 1950–2024

(Number of live births per woman aged 15–49 years)

Region

1950

1960

1970

1980

1990

2000

2010

2024

Africa

6.5

6.7

6.7

6.6

5.9

5.2

4.9

4.0

Asia

5.7

5.2

5.6

3.9

3.3

2.6

2.3

1.9

Europe

2.7

2.6

2.3

1.9

1.7

1.4

1.6

1.4

Latin America and the Caribbean

5.8

5.9

5.2

4.2

3.2

2.6

2.2

1.8

North America

3.1

3.7

2.5

1.8

2.0

2.0

1.9

1.6

Oceania

3.7

4.1

3.6

2.6

2.6

2.5

2.5

2.1

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Box I.1

Methodology and data sources for fertility estimation

The main data source for the calculation of birth and fertility indicators is the civil registration and vital statistics systems in the countries, provided they are complete and have national coverage. The quality of this information is often assessed using data from censuses, demographic and health surveys and household surveys. If it is found to be underestimated, either record adjustment techniques can be applied, or the figures from censuses and surveys can be used via direct or indirect demographic estimation techniques.

Data sources and fertility estimation methods

In addition to fertility rates estimated from vital birth statistics, data sources and methods used to estimate fertility in the region include data from birth histories collected through demographic and health surveys conducted in various years. Census data are also used, with information on live births in the past 12 months corrected using data on total live births by mother’s age. Different indirect methods are used to make this correction, such as the Brass P/F ratio or the relational Gompertz method, which uses data on live births and births in the last 12, 24 or 36 months, classified by mother’s age. Indirect estimates can also be made by applying the inverse survival function to census data. These methods and sources make it possible to obtain an estimate of the overall total fertility rate and the age-specific fertility pattern. The figures used as the basis for the fertility estimates are available on the UN Population Division Data Portal (https://population.un.org/dataportal/) and in the publication World Fertility Data (https://www.un.org/development/desa/pd/data/world-fertility-data).

Estimating fertility series from 1950 to 2023

The total fertility rate for the 2024 revision of the United Nations (2024) estimates and projections, used in this document, is based on data and estimates collected for the entire period 1950–2023. The annual time series of the total fertility rate from 1950 to 2023 for each country is estimated using logistic curves or a Bayesian hierarchical model, based on the theoretical model used by the United Nations to model fertility change. This model takes into account the biases and uncertainty associated with empirical estimates from different types of data sources, direct and indirect estimation methods, and other factors that contribute to systematic biases and non-sampling error. The model considers two types of data characteristics, depending on the type of source and estimation. As a general rule, fertility was taken from vital registration data only for years and countries where birth registration was estimated to be at least 60% complete. The fertility time series for countries whose birth registration since 1950 was at least 98% complete was treated as unbiased.

Source: Economic Commission for Latin America and the Caribbean on the basis of the United Nations (2024, July). World Population Prospects 2024: Methodology of the United Nations population estimates and projections. (UN DESA/POP/2024/DC/NO. 10).

B. The impact of the fertility transition on population structure

The demographic transition has not only influenced total population growth, but has also had a significant impact on the age structure of populations. The population is considered a stock that, over time, ages, immigrates or emigrates, and dies. The main driver of the shape of population pyramids over time is the size of birth cohorts, along with mortality and the migration balance. Figure I.2 shows the population pyramid for each region of the world (dark blue line) and the total number of births corresponding to the birth year for each age (light blue line). The 5-year-old population as of 1 January 2024 (dark blue line), for example, is the population born in 2019 (light blue line) minus deaths occurring between 2019 and 2023 plus the migration balance for that period. In the cases of Africa, Latin America and the Caribbean, and Asia, in general, births are greater than the population (due to the greater effect of mortality and emigration in these regions). However, in the cases of North America, Europe and Oceania, the number of births is lower than the population, notwithstanding that mortality also affects these birth cohorts, due to the greater weight of immigration.

Even with these differences, it is clear that the shapes of the pyramids for the different world regions are largely defined by the sizes of the birth cohorts. It may be concluded from figure I.2 that the the shape of population pyramids in the medium and long terms is strongly moulded by the speed of the fall in births. Likewise, the positive or negative migration balance can also significantly affect the shape of the pyramids, depending on the magnitude of that balance over the years.

Figure I.2

World regions: population on 1 January 2024 by age and sex, and number of births per year of birth, 1950–2023

(Millions of persons or births)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Population changes may be summarized by annual population growth rates. Figure I.3 shows these rates for the different world regions for the period 1950–2024. It may be observed that annual population growth rates in Latin America and the Caribbean were the highest in the world in 1950 and 1960, but by 1970 were lower than those of Africa. The region’s growth rates have been gradually declining at a rate similar to those of Asia, and today they are similar to those of North America and Asia, but still higher than the rates seen in Europe, which are negative today. The image in figure I.3 shows the different regional demographic trajectories and summarizes the different rates of demographic change in the various regions over time.

The transformations in population age structures across the regions driven by the demographic transition are also observed in the way the dependency ratio evolves in each region. Between 1990 and 2024, the dependency ratio trended upwards in regions such as Europe, North America and Oceania, reflecting progressive ageing of their populations (see figure I.4). By contrast, the total dependency ratio series declined in Latin America and the Caribbean and Africa, meaning that their population aged 15–64 years is still growing, compared to their populations aged 0–14 years and 65 years or over. However, the dependency ratio in Latin America and the Caribbean is considerably lower than in Africa, indicating that its demographic dividend will end much earlier. Asia shows quite a stable dependency ratio, with a fall in this indicator until around 2010, followed by a recent increase marking the beginning of the ageing process in that region. This comparative evolution enables a summary of the effects of the different rates of fertility decline and the demographic transition.

Figure I.3

World regions: annual population growth rate, 1950–2024

(Rate per 1,000 inhabitants)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Figure I.4

World regions: total dependency ratio, 1990–2024

(Per 100)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Note: The demographic dependency ratio is the quotient between the population aged 0–14 years plus the population aged 65 years and over, and the potentially active population (aged 15–64 years), multiplied by 100.

C. Theories on fertility decline in the context of the first demographic transition

The classic explanation of fertility decline in the context of the first demographic transition refers to industrialization, urbanization and economic development. Specifically, improved health and nutrition, macro- and micro-level public health measures,[5] advances in health treatments and the population’s greater access to these contribute to lower mortality and, in turn, reduce fertility. The classic authors attribute a major role to the fall in mortality in explaining the drop in fertility, asserting that the latter is a multiphasic response to the stimulus produced by the fall in mortality (Notestein 1945; Davis, 1963). In addition to the classic theory, Mason (1997) draws attention to five other main theories to explain the fall in fertility in the first transition, as described below.

The first additional theory is Coale (1973), who focuses on the individual and points to three fundamental conditions for fertility to decline: (i) fertility must be within the couple’s ability to make a conscious choice; (ii) fertility reduction must be advantageous; and (iii) fertility control techniques must be available.

Another explanation for the fertility decline refers to the reversal of the intergenerational flow of resources in modern societies (Caldwell, 1982). Caldwell argues that, in traditional societies, children contribute from an early age to household economic production, whereas, in modern societies —mainly due to mass education— there is a much more significant transfer of resources from parents to children, which reduces the incentive to have large families.

Third, the microeconomic theory of Becker (1960) and Schulz (1973) emphasizes three determinants of couples’ fertility decisions: the cost of children, the couple’s income, and preferences between having children and consuming alternative goods. In this theory, increased female labour market participation is central to the decline in demand for children, as women’s time becomes more onerous, increasing the relative cost of children, and women’s changing roles increase the opportunity costs of childbearing. The costs of education and parenting are also rising in modern societies.

Fourth, the analytical model of Easterlin (1975) and Easterlin and Crimmins (1985) extends the microeconomic approach to fertility by adding the supply of children without deliberate fertility control. In this model, fertility has three determinants: the supply of children (number of children that parents would have without constraints), the demand for children (desired number of surviving children) and the costs of fertility regulation (psychological, social and monetary).

Finally, Cleland and Wilson’s (1987) theory of ideational change relates fertility decline to the diffusion of information and new social norms on birth control. Cultural changes —including individuation, desacralization, secularization, rationalization, and equalization of rights, including for women— which some authors consider part of “modernity”,[6] are linked to new social norms regarding the benefit attributed to fertility control.

D. Factors associated with fertility decline towards replacement level

As mentioned earlier, the factors associated with the first demographic transition and the fall in fertility to replacement level are generally socioeconomic and cultural, mediated by intermediate variables, and sensitive —to varying degrees— to public policies.

The inverse relationship between socioeconomic development and fertility levels in various countries of the world was analysed by Myrsklä et al. (2009), who show that, at human development index (HDI) levels drop below 0.86, the relationship between HDI and total fertility rate (TFR) is negative, i.e. the higher HDI, the lower TFR. However, at more advanced levels of development, where HDI is above 0.86, the authors show that the negative relationship no longer holds. In other words, in high human development contexts, there is no longer a strong negative relationship between the human development index and the total fertility rate.

Figure I.5 shows this relationship for 193 countries and territories of the world in 2023. Latin American and Caribbean countries follow the expected pattern in intermediate stages of development: lower fertility as HDI improves. Argentina, Chile and Uruguay record the highest HDI in the region and among the lowest TFRs.

In a recent paper, Schubert et al. (2024) analyse the relationship between human development and fertility in different states in the United States of America between 1969 and 2018. The results point to the existence of factors that may attenuate and even reverse the negative association between development and fertility as suggested by the theory of the demographic transition. The paper argues that factors such as economic stability and gender equality may mediate the relationship between development and fertility. These two factors are extensively discussed in chapter II, which deals with post-transitional fertility.

Figure I.5

193 countries and territories: total fertility rate and human development index (HDI), 2023

(Number of live births per woman and HDI values on a scale from 0 to 1.0)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/temas/proyecciones-demograficas/america-latina-caribe-estimaciones-proyecciones-poblacion, for the total fertility rate, and the human development index of the United Nations Development Programme.

Note: Includes the 193 countries and territories of the world for which information on the human development index and total fertility rate is available. The human development index is presented in the graph based on the following logarithmic scale, used in Myrsklä et al. (2009): -log(1 - HDIm). The graph shows two reference values: HDI of 0.86, which the literature identifies as a threshold within the high range (0.8–1), and the fertility rate of 1.3 children per woman, which is identified as ultra-low fertility.

In analysing fertility transitions in low- and middle-income countries, Bongaarts (2024) argues that changes in reproductive preferences (i.e. decreasing desired family size and increasing demand for contraceptives), as well as increased availability of and access to contraceptives, are drivers of the fertility transition.

In Latin America and the Caribbean, on the one hand, rapid urbanization and growing access to education, particularly for women, played a central role.[7] On the other hand, the development of family planning programmes during the 1960s, often funded with international support, facilitated access to contraceptive methods and promoted the adoption of a smaller family ideal. At the same time, economic modernization of economies, including women’s increased participation in the labour market, increased the opportunity cost of having children, thus contributing to the decline in fertility (Palloni, 1990).

The pace and characteristics of this transition varied significantly among countries in the region. Argentina and Uruguay, where fertility decline had begun in the late nineteenth and early twentieth centuries, already had lower fertility levels at the start of the 1960s. By contrast, in Brazil, Chile, Colombia and Mexico, the transition started later but proceeded more rapidly, with substantial reductions occurring in the following decades. In the cases of Guatemala, Honduras and the Plurinational State of Bolivia, the decline was slower, reflecting persistent inequalities in access to education and health services within the region.

Whereas in the European model in the nineteenth century and in the middle and upper socioeconomic sectors of Latin America in the first half of the twentieth century, economic and social development was key to the fertility transition, it is doubtful that the same reasons applied to fertility declines in the lower classes. One hypothesis is that part of the drop in fertility in this group may reflect the pressure of economic needs in periods of crisis (Chackiel and Schkolnik, 2003). Although economic crises may have led to fertility declines, poorer strata have also been influenced by overall development, through improvements in education, health, communications and women’s economic participation. Fertility differentials by social group in the region will be analysed in more detail in chapter IV.

In Europe, nuptiality and the use of modern contraceptives were key to the fertility transition. Access to family planning and contraceptive methods were fundamental to the secular reduction in fertility during the first demographic transition. Analysing data from the United States, Goldin and Katz (2002) find that access to the contraceptive pill was essential in transforming women’s educational and employment trajectories. Once able to control fertility, women were able to delay marriage and childbearing, which facilitated their investment in higher education and professional careers. Reproductive control reduced the costs associated with career decisions, increasing female participation in traditionally male-dominated professions and contributing significantly to women’s labour market integration and economic autonomy.

Beginning in the 1960s, several studies began to document the transformations in reproductive patterns in Latin America. However, these did not occur uniformly across all social groups. According to Chackiel and Schkolnik (2003), in countries with lower fertility, the contraceptive behaviour of less educated women tended to resemble that of more educated women, reflecting some convergence in access to and use of family planning methods. However, in countries where fertility remained high, contraceptive use remained low, especially among the most left-behind sectors, limiting fertility reduction in these groups.

The literature shows that the transition to low fertility levels is mainly due to increased contraceptive use, while changes in nuptiality —understood as a lower proportion of unmarried women or a higher age at first marriage— have not had such a noticeable effect on fertility reduction. Fertility in Latin America has declined with the spread of modern contraceptive methods since the second half of the 1960s. Contraceptive use increased markedly in the last decades of the twentieth century, although unevely across countries, as a result of family planning programmes, changes in desired family size, and new forms of contraception (Bay, Del Popolo, and Ferrando, 2003). In the early 2000s, there was also a significant correlation between fertility and the prevalence of contraceptive use. The countries with the highest contraceptive use were those with the lowest fertility (such as Cuba) or the fastest reduction in the average number of children per woman (Brazil and Mexico).

E. Transformations in the age profile of fertility during the transition

The transition from high to low fertility characteristic of the first demographic transition has been mainly a result of the decrease in the incidence of higher parity births, i.e. births to women with at least one child. Unlike transitional regimes, post-transitional regimes, which will be analysed in chapter II, are distinguished by postponement of first children and an increase in the proportion of childless women at the end of their reproductive period. Trends toward smaller families accompany the high monetary and opportunity costs of higher parity births (Morgan and Taylor, 2006). Thus, along with changes in the total fertility rate, changes also occur in the structure of specific fertility rates. During the first transition, specific fertility rates decreased at typical ages of higher parity (30 years and older).

Figures I.6A and I.6B show, respectively, the change in specific fertility rates and their relative distribution in relation to the total fertility rate in Latin America and the Caribbean between 1970 and 2024.[8] Figures I.6A shows specific fertility rates declining substantially in all age groups in the region. The highest rates between 1970 and 1980 exceeded 200 births per 1,000 women aged 20–24 years, whereas by 2024 this value had fallen to less than 100 births per 1,000 women. Although the fall in specific fertility rate occurs in all groups, the significant drop in adolescent fertility (15–19 years) is observed only in the 2014 and 2024 curves. Due to this lag in the reduction of adolescent fertility, Lima et al. (2018) pointed to a “bimodal” fertility pattern in Latin America when analysing data from 2000 and 2011, mainly in the cases of Chile and Uruguay, where high levels of adolescent fertility persisted alongside higher first birth rates at later reproductive ages.

With respect to the relative distribution of fertility, between 1970 and 1980 a decrease occurred in the proportion of fertility at age 35 and older (see figure I.6B). This is followed by increasing rejuvenation of the age structures, with the mode of the curve shifting increasingly to the left up to the year 2000. Between 2000 and 2014 (the year in which the region reached the replacement level of 2.1 children per woman), the proportion of fertility between ages 20 and 29 decreased within total fertility while the proportion of fertility at older ages increased; however no significant decrease occurred in the contribution made by adolescent fertility to the total fertility rate. This changed between 2014 and 2024, with a decrease in the proportion of adolescent fertility in total fertility and a rightward shift of the cusp, showing an increase in the contribution of fertility at older ages to total fertility.

Figure I.6

Latin America and the Caribbean: specific fertility rates and their relative distribution in relation to the total fertility rate (TFR), selected years between 1970 and 2024

(Number of live births per 1,000 women and proportions of TFR)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/temas/proyecciones-demograficas/america-latina-caribe-estimaciones-proyecciones-poblacion.

These changes are reflected in the average age of fertility (see figure I.7). In Latin America and the Caribbean, the average age of fertility showed an overall downtrend from 1950, when it was 29 years, to a low of 26.9 years in 2010. In the past decade, however, since 2013, the average age of fertility eased back up, to 27.6 years in 2024. This suggests that, despite a historical trend toward earlier fertility and the fact that the region currently has the lowest average age of fertility, recent years have brought a shift towards slightly later fertility. In general, as TFR values come close to dropping below replacement level, the average age of fertility rises, with the postponement of childbearing. This pattern has been observed in most European countries which experienced fertility declines to low or very low levels and a rise in the average age at first and second order births (Sobotka, 2004). The fertility decline in Latin America and the Caribbean has some particular characteristics: low fertility levels were reached without the onset of a steady increase in the average age of fertility, while fertility in adolescence remained high (Cabella and Pardo, 2014; Lima et al., 2018); and the average age of fertility has increased more recently, since 2013.

Changes in the average age of fertility are also related to changes in the adolescent-specific fertility rate, which measures births per 1,000 women aged 15–19 in a given year. Adolescent fertility in the region remains among the highest in the world, reflecting structural inequalities and gaps in access to sexual and reproductive health services. As figure I.8 shows, the specific adolescent fertility rate —despite having gradually declined and more markedly so in the past 15 years— is still higher in Latin America and the Caribbean than in all other regions except Africa, which may be linked to social, cultural and economic factors, as well as to difficulties in closing gaps in the exercise of sexual and reproductive rights.[9]

Figure I.7

World regions: total fertility rate and average age of fertility, 1950–2024

(Number of live births per woman and years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/temas/proyecciones-demograficas/america-latina-caribe-estimaciones-proyecciones-poblacion.

Figure I.8

World regions: specific fertility rate in adolescence, 1950–2024

(Number of live births per 1,000 women aged 15–19 years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/temas/proyecciones-demograficas/america-latina-caribe-estimaciones-proyecciones-poblacion.

1. [1] The theory of demographic transition was first developed by Thompson (1929) and Notestein (1945) and argues that changes in economic production and social shifts from traditional to modern societies are the main factors behind it.

2. [2] The groupings used in this document are as follows: Latin America includes Argentina, Bolivarian Republic of Venezuela, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Plurinational State of Bolivia and Uruguay. The Caribbean includes 27 countries and territories: Anguilla, Antigua and Barbuda, Aruba, Bahamas, Barbados, Belize, British Virgin Islands, Caribbean Netherlands, Cayman Islands, Curaçao, Dominica, French Guiana, Grenada, Guadeloupe, Guyana, Jamaica, Martinique, Montserrat, Puerto Rico, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Sint Maarten, Suriname, Trinidad and Tobago, Turks and Caicos Islands, and United States Virgin Islands.

3. [3] The total fertility rate indicates the number of live births (both female and male) for a woman during her childbearing years (usually between the ages of 15 and 49), if she were subject to the age-specific fertility rates of a given year or period. It is calculated as the sum of age-specific fertility rates, which are the quotient of the total number of births per woman in a specific age group and the number of person-years lived by women in that age group, based on the mid-year estimated population of women. The terms “live births per woman” or “children per woman” are used to express the total fertility rate in this document.

4. [4] The replacement level of the total fertility rate (TFR) is the value reached when the net reproduction rate (NRR) is equal to 1. NRR is defined as , where is the sex specific female live birth fertility rate (or specific childbearing rate) between ages x and x+n in year t; is the number of person-years lived between ages x and x+n by a hypothetical cohort in the female mortality table in year t; and is the size of the hypothetical cohort in the mortality table, usually 100,000 persons (Preston et al., 2001). NRR may be interpreted as the average number of daughters that women in a birth cohort would have during their reproductive lifetime if they were exposed to the age-specific fertility rates observed in year t () and the mortality rates of year t over their lifetime. If NRR is greater than 1, then the cohort of girls will be larger than the cohort of mothers; if equal to 1, the two cohorts will be equal. In general, at low levels of mortality, the TFR corresponding to NRR= 1 is about 2.1 (TFR = * NRR where SR is the sex ratio at birth and p(Am) is the probability of survival at mean childbearing age). For simplicity’s sake, this document takes 2.1 children per woman to represent the replacement level for all countries.

5. [5] Improvements in public health are related, at the macro level, to large public works projects: supply of filtered and chlorinated water to the population, construction of public sanitation systems (sewerage), drainage of swamps, pasteurization of marketed milk, and mass vaccination campaigns (Preston, 1975; Soares, 2007). At the micro level, improvements in public health involve individual changes fostered by the public sector, such as the practices of boiling bottles and boiling water and milk before drinking, protecting food from insects, washing hands, ventilating rooms, and keeping children’s vaccinations up to date (Preston, 1975). The significant decline in waterborne and foodborne diseases that led to the drop in mortality —typhoid fever, cholera, dysentery, and non-respiratory tuberculosis, among others— reflects the key role of public health in reducing mortality. Cutler and Miller (2005), for example, estimate that purification of water supplies accounts for the one-third reduction in mortality in the United States between 1900 and 1930.

6. [6] See Bravo (1992) and Giddens (1995).

7. [7] In the case of Brazil, for example, it has been shown that a decrease in child mortality, a rise in the percentage of homes with electricity, an increase in women’s education and greater participation in the labour market are highly correlated with the onset and the rate of fertility reduction (Potter el al., 2002).

8. [8] There was no significant change in the percentage distribution between 1950 and 1970.

9. [9] Garbett et al. (2025) analyse adolescent fertility in 15 countries in the region and its relationship to school enrolment over the past 60 years, finding that, while school enrolment continues to be associated with lower adolescent fertility and adolescent girls’ school retention is crucial, it is also necessary to address the structural inequalities and social dynamics that influence adolescent girls’ reproductive decisions.

II. Post-transitional demographic regimes in the countries of the region

This chapter analyses the sharp fall in the total fertility rate to below replacement level in the countries of the region in recent years. It also reviews the years at which countries crossed key fertility thresholds, including the replacement level (2.1 children per woman), associated with zero long-term population growth, and the lowest-low fertility threshold, which may lead to rapid population decline. Lastly, it examines the main theories used to interpret this demographic shift in the context of below-replacement fertility.

A. Low and lowest-low fertility in the region and the world

Although it is a universal process that has taken place in all countries, albeit with varying timing and speed, the first demographic transition is insufficient to account for the decline in fertility once the replacement level has been reached. This is because the theory assumed that fertility would stabilize around that level, resulting in zero population growth, which has not materialized in practice.

Since 2015, the fertility rate in Latin America and the Caribbean has fallen below replacement level. Currently, the average fertility rate in Latin America is 1.8 children per woman, while it stands at 1.5 in the Caribbean. In 2024, 76% of the countries and territories of Latin America and the Caribbean recorded fertility rates below replacement level, a proportion surpassed only by Europe and North America, where 96% of countries were in the same situation (see figure II.1). By comparison, fertility rates below replacement level were recorded in 55% of countries in Asia, 30% in Oceania and only 7% in Africa. Figure II.1 also shows that until 1998, Latin America and the Caribbean and Asia had a similar percentage of countries and territories with below-replacement fertility —approximately 30% in both cases (15 countries and territories in Latin America and the Caribbean and 14 in Asia). However, in the 2000s, the number of countries and territories with low fertility began to grow more rapidly in Latin America and the Caribbean

than in Asia.

Figure II.1

World regions: countries and territories with a total fertility rate below or equal to 2.1 live births per woman, 1950–2024

(Percentages of total countries and territories of each region)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

In the region, no country or territory that has reached the replacement level has maintained a rate of 2.1 children per woman; on the contrary, fertility has continued to decline steadily. Some are even on a trajectory towards low (TFR ≤ 1.5 children per woman) and lowest-low (TFR ≤ 1.3 children per woman) fertility levels, similar to patterns in Europe, Japan and other countries. Map II.1 presents the estimated total fertility rate for 2024 in 47 countries and territories of Latin America and the Caribbean, with values ranging from 0.94 to 3.3 children per woman. In Latin America, the lowest fertility rates are in Chile (1.14 children per woman), Costa Rica (1.32), Uruguay (1.4) and Argentina (1.5), with several already registering lowest-low fertility levels. At the other end of the spectrum are Haiti (2.63 children per woman), the Plurinational State of Bolivia (2.52), Honduras (2.48), Paraguay (2.42) and Guatemala (2.29), which have the highest fertility rates in the region. However, as fertility remains below 3 children per woman in these countries, their levels are considered intermediate.

Map II.1

Latin America and the Caribbean (47 countries and territories): total fertility rate, 2024

(Number of live births per woman aged 15 to 49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

Note: The boundaries and names shown on this map do not imply official endorsement or acceptance by the United Nations.

Among Caribbean countries and territories, the highest total fertility rate is found in French Guiana (3.34 children per woman), followed by Sint Maarten (2.67), Guyana (2.39) and Suriname (2.23). All other Caribbean countries and territories recorded rates below replacement level in 2024, with many already at lowest-low levels. The lowest rates were registered in Puerto Rico (0.94), British Virgin Islands (1.05) and Curaçao (1.07).

Table II.1 presents the total fertility rate of countries and territories of Latin America and the Caribbean in 1990, 2010 and 2024, as well as the years in which they reached specific fertility rate thresholds (≤ 3, ≤ 2.1, ≤ 1.5 and ≤ 1.3 children per woman).[1] In 1990, five countries or territories in the region had fertility rates below replacement level (Barbados, British Virgin Islands, Cayman Islands, Cuba and Martinique). By 2010, this group had expanded to include 6 countries in Latin America (Brazil, Chile, Colombia, Costa Rica, Cuba and Uruguay) and 18 Caribbean countries or territories. In 2024, only eight Latin American countries[2] and four Caribbean countries or territories had not yet reached rates below replacement level.

Table II.1

Latin America and the Caribbean (47 countries and territories): total fertility rate in 1990, 2010 and 2024, and years of decline

(Number of live births per woman aged 15–49, and year)

Country or territory

TFR

Year of decline of TFR

1990

2010

2024

≤ 3

≤ 2.1

≤ 1.5

≤ 1.3

Latin America and the Caribbean

3.24

2.18

1.80

1994

2014

-

-

Latin America

3.26

2.19

1.80

1994

2014

-

-

Argentina

3.03

2.41

1.50

1966

2018

2022

-

Bolivia (Plurinational State of)

4.90

3.21

2.52

2014

-

-

-

Brazil

2.90

1.79

1.61

1990

2002

-

-

Chile

2.58

1.84

1.13

1977

1999

2019

2021

Colombia

2.99

2.01

1.63

1990

2009

-

-

Costa Rica

3.17

1.83

1.32

1993

2003

2020

-

Cuba

1.81

1.67

1.45

1975

1978

1993

-

Dominican Republic

3.41

2.55

2.22

1997

-

-

-

Ecuador

3.68

2.61

1.81

2002

2019

-

-

El Salvador

3.96

2.24

1.76

2001

2015

-

-

Guatemala

5.48

3.37

2.28

2016

-

-

-

Haiti

5.41

3.50

2.63

2017

-

-

-

Honduras

5.27

3.08

2.48

2011

-

-

-

Mexico

3.44

2.34

1.89

1996

2016

-

-

Nicaragua

4.59

2.59

2.21

2001

-

-

-

Panama

3.07

2.58

2.11

1991

-

-

-

Paraguay

4.56

2.69

2.41

2005

-

-

-

Peru

3.91

2.42

1.96

1999

2019

-

-

Uruguay

2.48

2.01

1.39

1977

2004

2020

-

Venezuela (Bolivarian Republic of)

3.45

2.39

2.08

1997

2022

-

-

The Caribbean

2.60

1.97

1.68

1992

2012

-

-

Anguilla

2.18

1.62

1.36

1984

1992

2006

-

Antigua and Barbuda

2.25

1.79

1.58

1974

1982

2016

-

Aruba

2.34

1.85

1.61

1970

1998

-

-

Bahamas (The)

2.52

1.84

1.37

1979

2000

2016

-

Barbados

1.84

1.78

1.71

1973

1978

-

-

Belize

4.80

2.55

2.02

2007

2020

-

-

British Virgin Islands

1.77

1.18

1.04

1980

1984

2002

2002

Caribbean Netherlandsa

2.40

1.67

1.46

1972

1998

-

-

Cayman Islands

1.78

1.69

1.52

1974

1982

2013

2015

Curaçao

2.30

2.18

1.07

1972

2004

2017

2019

Dominica

3.09

1.88

1.48

1978

2003

2020

-

Grenada

3.05

2.03

1.47

1981

2009

2017

-

Guadeloupe

2.24

2.13

2.07

1977

2017

-

-

French Guiana

3.73

3.42

3.34

-

-

-

-

Guyana

3.18

2.68

2.39

2001

-

-

-

Jamaica

2.95

1.79

1.35

1988

2006

2016

-

Martinique

2.02

2.03

1.99

1976

1985

-

-

Montserrat

2.16

1.58

1.44

1975

1994

1998

-

Puerto Rico

2.29

1.61

0.93

1973

1998

2013

2016

Saint Kitts and Nevis

2.73

1.76

1.52

1984

2001

-

-

Saint Lucia

3.24

1.67

1.38

1993

2002

2011

-

Saint Vincent and the Grenadines

2.73

2.14

1.76

1986

2004

-

-

Sint Maarten

2.74

2.39

2.67

1975

1987

2019

-

Suriname

3.22

2.69

2.23

1993

-

-

-

Trinidad and Tobago

2.39

1.61

1.53

1985

1994

-

-

Turks and Caicos Islands

3.18

1.91

1.45

1992

2006

2022

-

United States Virgin Islands

3.11

2.48

2.08

1981

2023

-

-

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

a Bonaire, Saba and Sint Eustatius.

B. The second demographic transition and new perspectives on low fertility rates

Various theories have been proposed to explain the persistence of fertility rates below replacement level (Balbo et al., 2013; Caldwell and Schindlmayr, 2003). One of the most influential among them is the theory of the second demographic transition (Lesthaeghe, 2010), which attributes this trend to cultural transformations characteristic of “post-materialist” societies. Such societies prioritize self-realization and individual autonomy (in contrast to traditional family-related obligations), along with greater acceptance of different lifestyles, more egalitarian relationships and non-normative individual life-course trajectories. There is also a lower aversion to change and to the dissolution of bonds, which fosters greater openness to more flexible lifestyles, diverse models of cohabitation, increased migration, weaker social cohesion, rejection of authority, more symmetrical gender relations, greater environmental awareness and a growing concern for the planet’s future. Collectively, these factors are thought to erode the altruistic rationale for having children (Lesthaeghe, 2010). In contrast to the theory of the first demographic transition, the theory of the second demographic transition places significant emphasis on culture and values, beyond macro-institutional changes or rational economic calculations.

The theory of the second demographic transition highlights a variety of new social issues, including those related to population ageing, integration of immigrants, lower marital stability, more complex households and high levels of poverty or exclusion in certain kinds of households (Lesthaeghe, 2014; Pérez Brignoli, 2022). In terms of nuptiality, the second demographic transition is associated with a decrease in the proportion of people who marry, a rise in the age at first marriage, an increase in cohabitation, a rise in divorce rates (including at younger ages) and a decline in remarriage following widowhood. The theory projects a rapid decline in fertility rates driven by the postponement of the first birth, accompanied by a higher mean age at first birth, sustained subreplacement fertility regardless of economic fluctuations, more efficient contraception, rising extramarital fertility (driven by rising fertility within cohabitation) and a growing share of childless couples.

Esteve et al. (2012) show that Latin America has several characteristics typically associated with the second demographic transition, such as falling fertility rates, increasing cohabitation and rising age at first marriage. However, they emphasize that, unlike Europe, these transformations are occurring in a context marked by deep structural inequalities and cultural particularities specific to Latin America. This means that, although the region demonstrates a number of global demographic patterns, its trajectory is unique and influenced by social, economic and cultural factors that shape how these changes unfold.

In general, the theory of the second demographic transition tends to generalize cultural processes and does not explain the heterogeneity of total fertility levels in countries with post-transitional demographic regimes. Furthermore, in stylized terms, two types of low-fertility regimes have emerged among countries with fertility below replacement level: those that have managed to stabilize their total fertility rate at around 2.1 children per woman and those that have very low fertility (around 1.5 children per woman). Explaining the reasons behind these differences between countries remains a challenge. The discussion generally centres on factors that facilitate the combination of child-rearing —particularly motherhood— with work and other social roles (Rindfuss and Choe, 2015).

As shown in table II.2, 55% of the world’s countries or territories have a total fertility rate below or equal to the replacement level (≤ 2.1 children per woman), while 28.0% register low fertility levels (≤ 1.5) and 10.6% have lowest-low fertility levels (≤ 1.3). Europe, North America and Latin America and the Caribbean exceed the global average in terms of the proportion of countries in these categories (with the exception that there are no countries or territories in North America with lowest-low fertility). In particular, 38% of countries or territories in Latin America and the Caribbean have low fertility levels and 12% have lowest-low fertility levels.

Table II.2

World regions: share of countries or territories with total fertility rate below or equal to 2.1, 1.5 and 1.3 live births per woman, 2024

(Percentages)

≤ 2.1

≤ 1.5

≤ 1.3

Africa

6.9

1.7

1.7

North America

100.0

40.0

0.0

Latin America and the Caribbean

76.0

38.0

12.0

Asia

55.1

20.4

18.4

Europe

96.1

62.7

17.6

Oceania

30.4

8.7

0.0

World

55.1

28.0

10.6

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

Note: The grouping of countries and territories follows the classification used by the United Nations Population Division, available at: https://population.un.org/wpp/. A total of 236 countries and territories were included: 58 in Africa, 5 in North America, 50 in Latin America and the Caribbean, 49 in Asia, 51 in Europe and 23 in Oceania.

One of the most influential theories for explaining the differences observed in post-transitional fertility levels across countries is that proposed by McDonald (2000), who argues that gender equity plays a crucial role in changes and differences in fertility levels. According to this perspective, decisions regarding childbearing are grounded in women’s expectations for their futures, shaped by the values and norms that define women’s roles in society, as well as their personal aspirations. The theory posits that very low fertility in advanced countries is the outcome of a conflict or inconsistency between a high level of gender equity in education and employment and sustained gender inequality within family-oriented institutions. In other words, while women have achieved greater equality in the public sphere, they continue to face significant disparities and burdens within the household, particularly in relation to domestic care. For fertility to remain at or return to levels close to replacement, there is a need for greater gender equality within the household —specifically, a more equitable distribution of reproductive and caregiving tasks. In this context, McDonald (2000) underscores the need to move towards greater gender equity within family environments, so that both the public and private spheres foster equitable conditions for women and men.

Brewster and Rindfuss (2000) also highlight the importance of facilitating balance between work and childcare responsibilities, underscoring the shift in the relationship between the total fertility rate and women’s labour force participation in 1996 (positive relationship), as compared to 1970 (negative relationship) in Australia, Canada, Japan, the United States and some European countries. The authors demonstrate that increasing the availability, accessibility, affordability and quality of childcare services is essential for improving the balance between work and caregiving. They emphasize the role of these institutions in supporting the dual responsibilities of work and caregiving, citing examples such as access to high-quality public and private childcare facilities, the existence of maternity and paternity leave benefits, flexible working hours to support childcare and the adaptation of workplaces to enable breastfeeding and infant care. Differences in the design and scope of work-policies to balance work and family life help to explain variations in fertility levels among developed countries. Where these policies are more robust and equitable, declines in fertility have been less pronounced.

In parallel, of the extensive literature on what has been termed the “motherhood penalty” shows that, in general, women with children do not experience the same labour market conditions as women without children (Kalabikhina et al., 2024). In Latin America and the Caribbean, women and girls bear a disproportionate burden of care work (women spend nearly three times as much time as men on domestic work and unpaid care work) and the region faces a chronic shortfall in investment, infrastructure and policies that recognize this work. The Economic Commission for Latin America and the Caribbean (ECLAC) has referred to this as a “care crisis” (Economic Commission for Latin America and the Caribbean [ECLAC], 2022a). In Brazil, for example, studies have shown that women with children still face significant disadvantages in the labour market (Guiginski and Wajnman, 2019), with such disadvantages being even more pronounced among women of lower socioeconomic status (Muniz and Veneroso, 2019).

Another theoretical approach linking gender equality and fertility is that of Goldscheider et al. (2015), which is based on the concept of the “gender revolution” and challenges the more pessimistic predictions associated with the second demographic transition. This theory posits that progress in men’s participation in domestic care tasks can contribute to increasing fertility levels. The gender revolution is conceptualized as occurring in two stages: the first involves the mass entry of women into the public sphere (via labour force participation) and the second entails the increased participation of men in the private sphere (household and childcare responsibilities). The delay in the development of this second stage is thought to have contributed to the very low fertility levels in a number of countries. However, as gender equality within the home advances, previously negative fertility trends begin to reverse.

Han et al. (2022) tested both theories and found that the evolution towards greater gender equality, as measured by the diffusion of egalitarian attitudes, carries more explanatory weight than the factors associated with ideational changes of the second demographic transition. Gender mainstreaming is particularly important for understanding recent fertility trends in Central, Eastern and Southern European countries. Applying this approach to the case of Brazil with data from 2000 and 2010, Castanheira and Kohler (2017) found that greater gender equality is associated with a higher probability of having a second child.

While addressing the decline in fertility —or even reversing this trend— requires a focus on gender equality in both the public and private spheres, it is also necessary to underscore other dimensions that warrant attention. Additional factors linked to disparities in posttransitional fertility levels across countries relate to differing labour market conditions. Generally, high levels of job insecurity and precarious employment, long working hours, lengthy commuting times and the absence of legislation that facilitates and creates flexibility for mothers’ reentry into the labour market are all associated with low or lowest-low fertility levels (Rindfuss and Choe, 2015, 2016). Beyond the labour sphere, Rendall et al. (2009) highlight a growing array of uncertainties across all dimensions of life (housing, intimate partner relationships, social protection, climate and planetary balance) that discourage young people from undertaking longterm commitments, particularly the lifelong commitment to having children.

The literature linking economic uncertainty to fertility trends in posttransitional contexts is noteworthy (Sobotka et al. 2011; Alderotti et al., 2021). These studies show that economic uncertainty is a key factor in fertility trends, although its effects vary depending on institutional contexts, access to resources and prevailing social norms. Broadly, the studies agree that economic downturns, such as the 2008 global financial crisis, have negatively impacted reproductive decisionmaking, prompting the postponement of childbearing or even permanent decreases in fertility levels. Sobotka et al. (2011) analyse this using data from developed countries, showing that fertility levels fell sharply during the recession among young people and in countries with more deregulated labour markets. They also emphasize that public policies —especially those that support the balance between work and family life— can mitigate these effects. In turn, Alderotti et al. (2021) delve into the role of persistent economic insecurity beyond episodic crises. Their analysis centres on the subjective perception of financial and labour instability as a critical determinant of fertility postponement, particularly among young women in Europe. They stress that even in countries with stronger welfare systems, uncertainty about the future can reduce the intention to have children, making stability a prerequisite for family planning.

In Latin America, persistent inequalities heighten the uneven impacts of economic uncertainty on fertility and often makes it more challenging for public policies to mitigate these effects. Adserà and Menendez (2011), for example, introduce important nuances, showing that although there is also a relationship between recession and declining fertility in the region, the mechanisms at play are contextspecific. High labour informality, lack of social protection coverage and structural inequalities result in fertility trends responding differently to uncertainty. The authors show that Latin American women, especially more educated and urban women, are more likely to postpone childbearing in times of crisis. However, this pattern may be less clear among more vulnerable populations, where pregnancies tend to be less planned and access to contraceptive methods remains limited. By contrast, in the case of Colombia, Davalos and Morales (2017) illustrate that economic crises are linked to falling fertility rates in the poorest departments between 1998 and 2013.

Castro et al. (2022), analysing 88 countries of the global South in the period 1986–2018, find that income inequality is positively associated with increasing dispersion in age at first birth, especially where the total fertility rate is below 2.5 children per woman. The authors identify two coexisting patterns: one marked by a uniform trend of early motherhood and another showing delayed motherhood with greater variation in the mean age at first birth. The transition to motherhood is a key milestone in adult life and can shape subsequent opportunities for education, labour market participation or migration, among others. Moreover, greater heterogeneity in fertility timing among those who postpone childbearing implies different life paths, not only compared with women who begin childbearing early, but also within that same group. This divergence in maternal age patterns can deepen inequalities of opportunity between these groups while simultaneously reflecting preexisting structural inequalities in access to education, employment and opportunities. The authors assert that studies of demographic change in the countries analysed should consider structural factors (poverty, lack of opportunity, extreme inequality) and how these may limit the range of possible demographic transitions.

Lastly, beyond structural conditions, recent studies suggest that reproductive decisions are also influenced by cultural factors related to contemporary childrearing practices and the high standards of investment in children, as well as the demands associated with certain socioeconomic standards or status. In Japan and the Republic of Korea, for example, where lowestlow fertility levels have persisted for decades, there is documented strong social pressure towards intensive parenting, where children’s success depends largely on parental effort, particularly that of the mother (Rindfuss and Choe, 2015, 2016). This parental selfpressure, coupled with the high direct and emotional costs of raising children, fuels the dilemma of raising well or not raising at all. In other words, for many people, the only acceptable way to have children is to provide optimal conditions, which is not always feasible today. Therefore, economic incentives or work-life balance policies, while necessary, may prove insufficient if they do not also address these particular social and cultural conditions. From this perspective, public policies must not only expand the provision of care services and gender equality but also enable diverse and sustainable forms of parenting over the long term.

C. The postponement of childbearing and the increase in the proportion of women with one child or no children

The postponement of childbearing reduces both the time available for and the biological possibilities of having more children (Esping-Andersen and Billari, 2015; Kohler et al., 2002). Consequently, this may result in a decline in higher-order births or lead to having only one child or none at all.

The postponement of childbearing has played a key role in the decline of fertility to low levels in developed countries (Kohler, Billari and Ortega, 2002; Sobotka, 2003, 2017b; Billari, 2008). This trend is so widespread that Kohler, Billari and Ortega (2002) coined the term “postponement transition” to describe the shift from an early to a late first-birth pattern in developed countries, which they argue represents a rational response to increased economic uncertainty among young people and the related expansion of higher education. The authors explain that the macro-level factors driving this uncertainty affect social interactions and institutions, all of which, in turn, lead to postponing childbearing at the individual level. Depending on the magnitude of postponement across all women, society at large may see significant reductions in fertility levels (see diagram II.1).

Diagram II.1

Theoretical framework for the transition to the postponement of childbearing

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Kohler, H. P., Billari, F. C., and Ortega, J. A. (2002). The emergence of lowest-low fertility in Europe during the 1990s. Population and Development Review, 28(4), 641–680. https://doi.org/10.1111/j.1728-4457.2002.00641.x.

Billari et al. (2006) distinguish three types of factors underpinning the postponement of childbearing: (i) ideational change and the second demographic transition; (ii) women’s increasing level of education; and (iii) increasing uncertainty during young adulthood and the emergence of the “later transition to adulthood”. Drawing on evidence from advanced countries, particularly in Europe, Sobotka (2017b) argues that many of the newly post-transitional countries are entering a long-term shift towards delayed childbearing. This transformation is expected to result in similar consequences for period fertility as those observed in Europe and other regions with a longstanding pattern of low fertility levels. Specifically, the postponement of childbearing is expected to drive period fertility rates in these countries well below cohort indicators of completed family size, with this gap persisting over several decades.

Lowest-low fertility has become increasingly significant not only in developed countries but also, more recently, in emerging economies. Figure II.2 shows the trajectories of countries and territories that experienced lowest-low fertility (≤ 1.3 children per woman) at some point between 1990 and 2024. According to the 2024 Revision of World Population Prospects,[3] a total of 41 countries and territories reached this threshold during the period. Figure II.2 presents a selected group of countries and territories: in the cases of Latin America and the Caribbean and Asia, all those that have reached lowest-low fertility levels are shown (with the exception of Montserrat in the Caribbean); in the case of Europe, 13 countries are included where fertility levels increased after reaching lowest-low levels and have not declined again since 2024, although they remain below replacement level.

Figure II.2

Latin America and the Caribbean, Asia and Europe (selected countries and territories): total fertility rate in countries and territories with lowest-low fertility at some point between 1990 and 2024

(Number of live births per woman)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

Note: In the graphs, only the trajectories of 28 countries and territories are presented for illustrative purposes. According to 2024 Revision of World Population Prospects, the following 41 countries and territories have had lowest-low fertility levels (≤ 1.3 children per woman) at some time between 1990 and 2024: Africa: Mauritius; Latin America and the Caribbean: British Virgin Islands, Cayman Islands, Chile, Curaçao, Montserrat, Puerto Rico and Saint-Barthélemy; North America: Saint Pierre and Miquelon; Asia: China, Hong Kong (China), Japan, Macau (China), Republic of Korea, Singapore, Taiwan Province of China, Thailand and United Arab Emirates; Europe: Andorra, Belarus, Bosnia and Herzegovina, Bulgaria, Czech Republic, Estonia, Finland, Germany, Greece, Hungary, Italy, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Russian Federation, San Marino, Slovakia, Slovenia, Spain and Ukraine. The graph for Europe includes the 13 countries that in recent years have remained above the level of 1.3 children per woman.

The data indicate that many European countries reached lowest-low fertility levels in the 1990s and 2000s. In subsequent years, their total fertility rates increased to approximately 1.5 children per woman, forming a U-shaped pattern. A similar pattern is observed in two territories in Asia: Hong Kong (China) and Macao (China). In contrast, other Asian countries and territories (Singapore, the Republic of Korea and Taiwan Province of China) have maintained lowest-low fertility for more than a decade. According to Goldstein et al. (2009), the partial recovery of fertility in parts of Europe and East Asia stems from a slowdown in the postponement of childbearing, combined with favourable economic conditions and the adoption of family-friendly public policies. In a similar vein, Bongaarts and Sobotka (2012) conclude that the increase in total fertility rates is largely attributable to a slowdown in the postponement of childbearing, rather than a rise in the total number of children per woman.

In Latin America and the Caribbean, some countries and territories have already reached lowest-low fertility levels. Chile, for example, reached this threshold in 2021, consolidating its position as one of the countries with the lowest total fertility rates in the region. Curaçao reached this level in 2019 and Puerto Rico in 2016. Although not yet at this threshold, other countries such as Costa Rica, Cuba and Uruguay are nearing it. The persistence of these trends could result in other countries, such as Argentina and Brazil, approaching this threshold in the coming decades.

Developing and middle-income countries with low fertility typically report younger ages at entry into motherhood and most only begin to show a shift towards later motherhood at the end of the 2000s, which may have resulted in a reduction of their total fertility rates (Bongaarts, 1999; Rosero-Bixby et al., 2009). Rosero-Bixby et al. (2009) noted in 2009 that Latin America was moving away from early and universal fertility. The authors showed a notable decrease in the proportion of young women having children, especially among those with higher levels of education, indicating a shift in social norms and reproductive patterns in the region (Rosero-Bixby et al., 2009).

The rise in the mean age at first live birth (hereinafter referred to as mean age at first birth) clearly reflects the trend towards delayed childbearing in the countries of the region (see box II.1 for the methodology used to calculate the mean age at first birth, based on vital statistics of the countries of the region). Figure II.3 shows a sustained upward trend in the mean age at first birth in all the countries analysed, particularly from 2011 onward. This pattern confirms the postponement of childbearing, which is widely documented in Latin America and the Caribbean, particularly among women under 25 years of age. However, the timing and scale of this postponement vary significantly across countries.

Figure II.3

Latin America and the Caribbean (12 countries and territories): mean age at first live birth, 1986–2022

(Years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean on the basis of UNdata statistics on live births by birth order and age of mother. https://data.un.org/Data.aspx?q=birth+order&d=POP&f=tableCode%3a58 and World Population Prospects 2024 population estimates by age. https://population.un.org/wpp/.

Box II.1

Estimation of the mean age at first live birth based on vital statistics data

The estimates presented in this edition of the Demographic Observatory allow for an analysis of the trends in the mean age at first birth in selected countries in Latin America and the Caribbean, differentiating between total births and first-order births. In both cases, to estimate the mean age at first birth by birth order (fx,p,t) , the methodology of Pardo et al. (2025) was applied, using data on live births by birth order and age of mother from vital statistics available in the UNdata database (https://data.un.org/). Specific fertility rates were calculated using 2024 Revision of World Population Prospects female population estimates as denominators. This approach is supported by Pardo et al. (2025), who validate the use of the 2024 Revision of World Population Prospects population estimates.

The mean age at first birth by birth order is calculated using the following formula:

where x corresponds to the woman’s age, p to the birth order (number of previous live births), and t to the time period observed.

Subsequently, the mean age is calculated as a weighted average of these rates:

It should be noted that most birth data were available only in five-year age groups. To disaggregate data into single ages, the penalized composite link model was applied, which smooths the distribution and produces a continuous approximation of births by age while preserving the general fertility structure, as described in Pardo et al. (2025).

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean on the basis of Pardo, I., Sacco, N., Acosta, E. and Castro, A. (2025). Fertility decline to low and lowest-low levels in Latin America. Population Research and Policy Review, 44 (9). https://doi.org/10.1007/s11113-024-09934-y.

In Chile and Uruguay, the mean age at first birth has risen over 27 in recent years, approaching patterns reported by European countries with very low fertility. These cases are associated with very low fertility levels, suggesting a significant delay in childbearing that may not be fully offset at older reproductive ages. Argentina and Costa Rica show similar levels, with mean ages at first birth close to 26 and 27 years, respectively. By contrast, Colombia, El Salvador and Mexico show lower mean ages at first birth, indicating that while there is a trend towards postponement, it is more moderate. These countries fall within the low fertility range and their trends suggest a balance between the postponement of childbearing and the continuation of more traditional reproductive patterns. Lastly, in Guatemala and Panama, where total fertility rates remain close to replacement level, the mean age at first birth is also relatively low, which may reflect a greater persistence of early motherhood.

Another key element for this analysis is the proportion of women without children across different age groups. This indicator can be calculated using data from population and housing censuses as well as demographic and health surveys and is available in the regional database on maternity (MATERNILAC) of the Latin American and Caribbean Demographic Centre (CELADE)-Population Division of ECLAC, accessible through CEPALSTAT. As shown in table II.3, the proportion of women without children has increased in most Latin American countries, particularly among those under the age of 25. This proportion has also grown among women aged 25–29 years and those aged 30 years and over, although with differences in magnitude across countries and cohorts. In all cases, the data point to a rising share of women without children, reflecting changes in the timing of childbearing in the region. While the pace of increase varies across countries, data from the 2020 census round provide a valuable opportunity to deepen the analysis of these trends and to update them based on the most recent information.

Table II.3

Latin America (18 countries): proportion of women aged 15 to 49 years old without children, by age group and census decade, 2000, 2010 and 2020

(Percentages)

Country

Age groups

Under 25 years

25–29 years

30 years and over

2000

2010

2020

2000

2010

2020

2000

2010

2020

Latin America

69.7

72.3

...

29.6

35.8

...

12.1

15.0

...

Argentina

73.1

73.4

81.2

36.7

39.6

44.9

12.9

15.7

18.3

Bolivia (Plurinational State of)

68.0

72.2

70.5

24.3

33.0

31.0

9.8

16.1

10.6

Brazil

69.8

74.3

78.7

30.8

39.9

47.1

13.1

16.9

22.1

Chile

72.5

…

78.7

32.6

…

44.1

12.9

…

15.6

Colombia

68.4

73.7

…

29.6

37.8

…

13.0

17.3

…

Costa Rica

70.2

74.2

…

26,7

36,7

…

10.7

14.3

…

Dominican Republic

66.9

63.5

…

28.0

22.2

…

16.0

7.9

…

Ecuador

65.4

65.6

74.2

25.7

26.4

33.0

12.4

13.1

11.5

El Salvador

68.8

81.8

…

26.0

48.6

…

10.6

27.3

…

Guatemala

65.7

69.3

…

23.0

28.5

…

10.4

12.3

…

Honduras

62.3

64.7

…

20.7

23.6

…

9.6

10.1

…

Mexico

70.5

70.2

74.2

27.6

29.6

34.9

10.0

11.3

14.7

Nicaragua

60.5

…

…

19.6

…

…

9.9

…

…

Panama

64.1

67.5

75.5

26.3

29.1

35.1

10.3

12.9

13.8

Paraguay

71.0

…

…

22.3

…

…

7.9

…

…

Peru

72.1

74.0

…

31.7

35.1

…

12.1

14.3

…

Uruguay

73.1

78.2

…

34.8

44.5

…

13.0

17.1

…

Venezuela (Bolivarian Republic of)

68.2

70.2

…

28.9

34.0

…

12.0

16.3

…

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean on the basis of the regional database on maternity (MATERNILAC). CEPASTAT. https://statistics.cepal.org/portal/cepalstat/dashboard.html?theme=1&lang=en&area_id=779.

Note: The census years for each country in each decade are as follows: 2000s: Argentina, 2001; Brazil, 2000; Bolivarian Republic of Venezuela, 2001; Chile, 2002; Colombia, 2005; Costa Rica, 2000; Dominican Republic, 2002; Ecuador, 2001; El Salvador, 1992; Guatemala, 2002; Honduras, 2001; Mexico, 2000; Nicaragua, 2005; Panama, 2000; Paraguay, 2002; Peru, 2007; Plurinational State of Bolivia, 2001; Uruguay, 1995. 2010s: Argentina, 2010; Bolivarian Republic of Venezuela, 2011; Brazil, 2010; Colombia, 2018; Costa Rica, 2011; Dominican Republic, 2010; Ecuador, 2010; El Salvador, 2007; Guatemala, 2018; Honduras, 2013; Mexico, 2010; Panama, 2010; Peru, 2017; Plurinational State of Bolivia, 2012; Uruguay, 2011. 2020s: Argentina, 2022; Brazil, 2022; Chile, 2017; Ecuador, 2022; Mexico, 2020; Panama, 2023; Plurinational State of Bolivia, 2024.

The distribution of the number of live births per woman has also changed significantly across censuses. As illustrated in figure II.4, there has been a notable shift in the distribution of live births per woman both at the beginning (age 20) and the end (age 49) of the childbearing period in Latin America in recent decades. Taken together, the data reflect a dual transition characterized by a postponement of childbearing and a reduction in the total number of children per woman.

Figure II.4

Latin America (16 countries): distribution of the number of live births per woman at the beginning and end of the childbearing period (20 years and 49 years), 2000, 2010 and 2020 census rounds

(Percentages)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean on the basis of the regional database on maternity (MATERNILAC). CEPALSTAT. https://statistics.cepal.org/portal/cepalstat/dashboard.html?theme=1&lang=en&area_id=779.

Note: Countries are grouped according to their total fertility rate in 2024.

Figures II.4A, II.4B and II.4C show a sustained increase in the proportion of women aged 20 without children in nearly all countries, pointing to a growing trend towards delayed childbearing. This trend is particularly evident in Argentina, Chile and Mexico, where the percentage of women without children at age 20 is considerably higher in the most recent census (2020 round) compared to previous decades. Conversely, the proportion of women with two or more children has declined, also reflected in a lower number of births among younger women. Figures II.4D, II.4E and II.4F show that, while the majority of women aged 49 have had children, the most recent censuses also report a slight increase in the proportion of women without children in this age group. At the same time, there has been a marked decrease in the percentage of women with four or more children, indicating a significant drop in high fertility rates. There has also been an increase in the proportion of women with only one or two children, reflecting a shift towards smaller family sizes in all countries with recent census data.

D. Changes in age-specific fertility rates in the countries of the region

Figure II.5 presents specific fertility rates by single age from 1990 to 2024 in the countries of Latin America, while figure II.6 shows the corresponding data for Caribbean countries and territories. In the case of Latin America, a marked decline in fertility is observed among younger age groups, particularly those aged 15–29, over the period in question. This trend is consistent with the postponement of childbearing and the decrease in adolescent fertility in many countries of the region, with a particularly noticeable drop between 2010 and 2024. Chile, Costa Rica and Uruguay are clear examples of this trend. In these countries, fertility has become increasingly concentrated in the 30–34 and 35–39 age groups, while births among younger women have declined substantially. In Chile, for example, the fertility rate for women aged 30–34 fell from 110 live births per 1,000 women in 1990 to 85 per 1,000 women in 2024, reflecting a more pronounced postponement of childbearing. By contrast, fertility patterns have undergone less significant changes in Guatemala, Honduras and Nicaragua. Although age-specific fertility rates among younger women have declined in these countries, the reductions have been more modest and overall fertility levels remain high. In Guatemala, for example, the age-specific fertility rate for the 20–24 age group stood at nearly 140 live births per 1,000 women in 2024, compared to over 180 per 1,000 women in 1990.

Figure II.5

Latin America (20 countries): age-specific fertility rate, by single age, selected years between 1990 and 2024

(Number of live births per 1,000 women aged 15–49 years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

Note: Countries are grouped according to their total fertility rate in 2024.

Figure II.6 presents age-specific fertility rates in the Caribbean between 1990 and 2024. Despite the subregion’s heterogeneity, most Caribbean countries and territories exhibit a shared trend of decreasing fertility rates across all age groups, with a progressive decline among younger women (aged 15–24), accompanied by a slight concentration of births among women aged 25–34. In Barbados, Martinique and Puerto Rico, the decline in adolescent fertility is particularly sharp, while births have shifted towards older age groups, suggesting a trend of delayed childbearing. For example, in Puerto Rico, the age-specific fertility rate for women aged 20–24 declined significantly between 1990 and 2024, while the rate for those aged 30–34 remained relatively stable in recent years. In contrast, Belize, Guyana and Saint Vincent and the Grenadines show signs of a more delayed postponement transition, with higher levels of early childbearing, although a slight decline in total fertility levels is also evident. In Belize, the specific fertility rate for the 20–24 age group remained high even in 2024, with levels close to 150 live births per 1,000 women, indicating a slower demographic transition.

Figure II.6

The Caribbean (27 countries and territories): specific fertility rate by single age, selected years between 1990 and 2024

(Number of live births per 1,000 women aged 15–49 years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables

Note: Countries and territories are grouped according to their total fertility rate in 2024.

E. Decline in adolescent fertility and the increase in the mean age at childbearing

As noted in chapter I, changes in age-specific fertility rates are closely linked to increases in the mean age at childbearing, which reflects the weighted average of fertility at childbearing age and provides an aggregate measure of the shift in births towards older ages. Figures II.7 and II.8 clearly show that the mean age at childbearing in Latin America and the Caribbean has risen steadily since 1990, averaging close to 28 years by 2024. This increase reflects a regional trend towards postponing childbearing. However, there are also significant differences among countries and subregions. Among Latin American countries, Chile, Uruguay and Argentina —in that order— have shown sustained and rapid increases in the mean age at childbearing, placing them above the regional average. The increase in Panama was particularly sharp between 2010 and 2024, reflecting a rapid shift in the timing of childbearing.

In contrast, Brazil registers a moderate trend, with steady increases in the mean age at childbearing, while the rise has been slower in Ecuador, suggesting a more gradual transition. Guatemala and the Plurinational State of Bolivia continue to register significantly lower levels, close to or even below 26 years in 2024, reflecting less postponement of childbearing and the persistence of more traditional reproductive patterns.

Figure II.7

Latin America (20 countries): mean age at childbearing, selected years between 1990 and 2024

(Years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

Note: Countries are grouped according to their total fertility rate in 2024.

Similarly, fertility patterns in the Caribbean vary significantly across countries. The Bahamas, Barbados and Trinidad and Tobago have maintained relatively high and sustained levels of mean age at childbearing over several decades, in some cases rising to more than 28 years. While the mean age at childbearing has increased more gradually in Belize, Jamaica and Saint Lucia, it has risen more notably in Curaçao and Puerto Rico to above 30 years and close to 28 years, respectively, in 2024 (see figure II.8).

Figure II.8

The Caribbean (18 countries and territories): mean age at childbearing, selected years between 1990 and 2024

(Years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

Note: Countries and territories are grouped according to their total fertility rate in 2024. Only countries and territories with a population of over 80,000 people in 2024 have been included.

An important factor associated with the increase in the mean age at childbearing in the region is the significant postponement of first births and the marked reduction in adolescent fertility over the past decade. This reflects a shift in reproductive timing and is closely linked to advances in sexual and reproductive health programmes (see box II.2).

Box II.2

Recent changes in contraceptive methods in the region and their potential link to falling fertility levels among adolescents and young people

In the region, adolescent fertility has declined significantly over the past decade, against the backdrop of government-led strategies and policies aimed at preventing adolescent pregnancy (Economic Commission for Latin America and the Caribbean [ECLAC], 2024, 2025). This is a noteworthy achievement, as until the early 2010s the region had not shown signs of a sustained decrease in adolescent fertility, which remained well above expected levels given the region’s overall fertility rates and human development indicators.

The key to understanding this decline lies in the proximate determinants of fertility. Available data indicate earlier sexual initiation, which would ordinarily be associated with higher levels of adolescent fertility. However, this did not occur. The explanation is likely linked to the use of contraceptive methods, warranting closer attention to such indicators. However, the commonly used measure of current use of modern contraception among adolescents has a major limitation: contraceptive use may begin only after a first birth, and as such, may not be a good predictor of adolescent pregnancy prevention. By contrast, the indicator measuring the use of modern contraception at sexual initiation avoids this problem of reverse causality (i.e. becoming a mother before starting contraceptive use) and also suggests a pattern of proactive prevention from first intercourse, potentially sustained throughout adolescence and beyond.

Few countries have series data on protected sexual initiation. Specialized surveys have focused on condom use, which is essential for sexual and reproductive health, but it is not the only contraceptive available. Nevertheless, condom use at first intercourse showed an upward trend in countries with available data in the 2010s, although the levels were far from representing the widespread protection required for a substantial reduction in adolescent fertility.

Chile and Mexico have national surveys that capture information on contraceptive use at first intercourse and identify the specific method used. These show that adolescent motherhood declined in both countries over the past 15 years, with a more rapid and pronounced fall in the case of Chile. The data presented in the table allow for at least two relevant conclusions regarding the effects of contraceptive protection from first intercourse on the reduction of adolescent motherhood: (i) there is a strong association between sexual initiation with modern contraceptive use and a significant drop in adolescent motherhood; and (ii) the reduction in adolescent motherhood is greater in Chile than in Mexico, which is linked both to Chile’s faster progress towards universal access to modern contraception at first intercourse and to the much higher prevalence of subdermal implant use, an effective and practical method for adolescents.

Chile and Mexico: proximate determinants of adolescent fertility, 2009–2023

Survey year

Percentage of women aged 15–19 who are mothers

Percentage of women aged 15–19 who are sexually active

Percentage of women aged 15–19 who used modern contraception at first intercourse

Percentage of women aged 15–19 who used subdermal implants at first intercourse

Chile

2009

10.7

46.4

58.2

...

2015

9.3

45.7

67.1

1.9

2022

2.4

40.0

93.5

9.2

Mexico

2009

11.7

25.1

36.2

Not available

2018

12.2

30.0

58.8

0.1

2023

7.7

32.1

68.9

0.1

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of National Institute for Youth. Encuesta Nacional de Juventudes. https://www.injuv.gob.cl/encuestanacionaldejuventud National Institute of Statistics and Geography. Información Demográfica y Social. https://www.inegi.org.mx/programas/enadid/2023/.

In Uruguay, the government launched a programme in 2014 to provide subdermal contraceptive implants free of charge to women accessing public health services. Ceni et al. (2021) found that the availability of these implants accounted for one third of the decline in fertility levels among adolescent and young women between 2016 and 2018. Other countries of the region have also implemented this policy, though analyses of its impact on fertility outcomes are still pending. To further understand the determinants of fertility reduction in these age groups, it is important to continue research in other countries of the region where adolescent fertility has fallen sharply.

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean [ECLAC], on the basis of ECLAC (2024). The Challenge of Accelerating the 2030 Agenda in Latin America and the Caribbean: Transitions towards Sustainability. Summary (LC/FDS.7/4); ECLAC (2025). Latin America and the Caribbean in the Final Five Years of the 2030 Agenda: Steering Transformations to Accelerate Progress (LC/FDS.8/3); Ceni, R., Parada, C., Perazzo, I. and Sena, E. (2021). Birth collapse and a large‐scale access intervention with subdermal contraceptive implants. Studies in Family Planning, 52(3), pp. 321–342; and Rodríguez, J. (2024). La reproducción en la adolescencia en América Latina: tendencias, desigualdades, determinantes y políticas. Presentation at the XI Congress of the Latin American Population Association (ALAP), for information from Chile’s national youth surveys and the National Survey on Demographic Dynamics (ENADID) of Mexico.

Figure II.9 shows the relationship between changes in the total fertility rate and in the adolescent fertility rate by country between 2014 and 2024 (difference between the rates in 2014 —the year in which the region reached the replacement level— and in 2024). Argentina and Chile stand out for the significant reductions in both rates. Uruguay and Costa Rica also show marked declines in both indicators. In the Dominican Republic, the adolescent fertility rate has decreased notably, while the decline in total fertility has been more moderate. In contrast, Caribbean countries such as Antigua and Barbuda and Barbados show only minimal changes, likely because their rates were already quite low in 2014. Over this 10-year period, the declines in both fertility indicators were more pronounced in Latin America than in the Caribbean.

Figure II.9

Latin America and the Caribbean (38 countries and territories): decline in the total fertility rate and adolescent fertility rate between 2014 and 2024

(Number of live births per woman)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, Population estimates and projections, 2024 revision. https://www.cepal.org/en/population-estimates-and-projections-excel-tables.

1. [1] A total fertility rate (TFR) of 3 children per woman is used as it represents an intermediate level; 2.1 serves as the reference for replacement-level fertility, while the thresholds of 1.5 and 1.3 correspond to low and lowest-low fertility, respectively. The latter two values were selected both for their frequent use in academic literature and their distinct demographic implications if sustained over the long term. For example, Toulemon (2011) illustrates how different TFR levels affect the time required for a population to halve in size under stable population conditions (i.e. constant growth rate). With a TFR of 2 children per woman, the population would take 530 years to halve; with a TFR of 1.9, 230 years; with 1.5, 64 years; and with 1.3, just 44 years. Kohler et al. (2002) used the threshold of 1.3 children per woman to define lowest-low fertility, as sustained fertility at this level could lead to a rapid decline in population size. The threshold of 1.5 children per woman was first proposed by Bourgeois-Pichat (1976) as indicative of low fertility.

2. [2] Includes Panama, which had a total fertility rate of 2.106 children per woman in 2024.

3. [3] https://population.un.org/wpp/

III. The effect of postponement on fertility rates in the region

As observed in chapter II, the sharp drop in fertility in the region over the past decade is closely linked with the decline in fertility among adolescent and young women. In the literature, declining fertility is associated with longer deferral or postponement of motherhood among those age groups. This chapter focuses on the implementation of demographic methods to measure the effect of postponement on the period total fertility rate (the “tempo effect”). It also includes an analysis of the decline in cohort fertility to evaluate the extent to which postponement may affect the total number of live births at the end of the childbearing period.

A. Cohort fertility and period fertility: complementary approaches for analysing reproduction

In this section, fertility in Latin America and the Caribbean is analysed from the standpoint of period and cohort measurements, emphasizing their importance as complementary but significantly different instruments for interpreting reproductive trends and planning accordingly.

The total fertility rate measures annual fertility using birth and female population data and reflects fertility in a given year. The total fertility rate is quite sensitive to the timing of births: when these are postponed, for example, the period total fertility rate falls, even if the number of children women have over their lifetimes remains the same. One of the indicators used to obtain a more accurate measurement of the average number of children born per woman in a calendar year is the tempo-adjusted total fertility rate. Meanwhile, the completed fertility rate measures the average number of children born per woman in her lifetime and is also a more stable indicator not subject to timing distortions, although it can only be calculated once the childbearing period has ended (see box III.1).

Box III.1

Calculation of period, cohort and tempo-adjusted fertility rates

The most widelyused indicator for the measurement of fertility is the total fertility rate, whose main advantage is its timeliness, as it can be calculated using the birth and female population information of a given year or period. Its disadvantage, however, is that it provides only a snapshot of fertility and fails to reflect the experience of a real group of women throughout their lives, rendering this indicator prone to distortions from shocks and changes at the time of births. One alternative is to calculate the completed fertility rate, which measures the average number of children born per woman in her lifetime based on the experience of real cohorts of women. This indicator is not subject to tempo distortions and tends to be more stable than period fertility measurements. However, because it can only be calculated once the cohort’s childbearing years have ended, it cannot elucidate fertility trends among younger women in recent years. Another alternative is to adjust for the tempo effect which, when not equal to zero, yields a figure that differs from the total fertility rate. This measurement is known as the “tempo-adjusted total fertility rate”.

Total fertility rate (TFR): The average number of children a woman would bear if she were subject to the age-specific fertility rates of a given year throughout her life. It is calculated as the sum of the age-specific fertility rates from 15 to 49 years and is expressed as the number of children per woman.

where SFRx(t) represents the specific fertility rate for age group x at time t; Nx(t) is the number of births in age group x at time t; and Px(t) is the female population in age group x at time t.

Completed cohort fertility rate (CFR): Completed cohort fertility is calculated using the age-specific fertility rates of each cohort.

where SFRx(c) represents the specific fertility rate for age group x of cohort c; Nx(c) is the number of births in age group x of cohort c; and Px(c) e is the female population in age group x of cohort c. This is a synthetic indicator that estimates the cohort’s average number of children on the basis of the specific rates observed for that cohort in different periods. This figure is not necessarily the same as the average number of children of the real cohorts observed at a given point in time, owing mainly to mortality. For the age of 49 years, that rate reflects the completed cohort fertility rate.

Tempo-adjusted total fertility rate: The purpose of the tempo-adjusted total fertility rate is to account for the postponement of births. It can provide a more nuanced understanding of fertility trends, particularly in societies undergoing shifts in age at childbearing. The method proposed by Bongaarts and Feeney (1998) is based on adjusting the standard total fertility rate using information on the mean age at childbearing. It can be applied in two ways, depending on data availability:

•Total adjusted fertility rate, when only the total fertility rate and mean age at childbearing are available for all births. In this case, the simplified formula is used:

where MAC(t) is the mean age at childbearing at time t and r(t) is the rate of change in the reproductive calendar.

•Adjusted birth order-specific fertility rates, when data disaggregated by birth order are available. In this case, the total birth order-specific fertility rates (TFRᵢ) are adjusted using the rate of change of the mean age at childbearing for each birth order. In this case, the following formula is used:

where the adjusted total fertility rate is the sum of the adjusted birth order-specific fertility rates:

Given that data disaggregated by birth order are not available for all countries and periods analysed, both methods were used in this study depending on data availability, comparing the results and smoothing the series using moving averages to avoid large fluctuations.

Smoothing (moving averages): Replaces each value in the time series by the average of a given number of surrounding years. Two time windows were used:

•Three-year centred moving average (mm-3):

•Five-year centred moving average (mm-5):

Given that mm-5 cannot be applied at either end of the series (owing to the lack of contiguous data), a hybrid approach was adopted (5/3/1) to conserve the entire series:

•Central years: five-year moving average

•Second-last year: three-year moving average

•Final year: direct observation (no smoothing)

This approach makes it possible to maintain trend stability without sacrificing temporal coverage.

Implementation of smoothing:

•To adjust the mean age at childbearing, the five-year moving average was used, with projections until 2026 to obtain a smoothed value until 2024.

•To adjust by birth order, the 5/3/1 approach was used.

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Bongaarts, J. and Feeney, G. (1998). On the quantum and tempo of fertility. Population and Development Review, 24(2), 271–291. https://doi.org/10.2307/2807974; Goldstein, J. R., Sobotka, T. and Jasilioniene, A. (2009). The end of “lowest‐low” fertility? Population and Development Review, 35(4), 663–699. https://doi.org/10.1111/j.1728-4457.2009.00304.x; and Jasilioniene, A., Jdanov, D. A., Sobotka, T., Andreev, E. M., Zeman, K., Shkolnikov, V. M. and Rodríguez, G. (2015). Methods protocol for the Human Fertility Database. Max Planck Institute for Demographic Research. https://www.humanfertility.org/Docs/methods.pdf.

Note: The authors would like to thank Ignacio Pardo (University of the Republic, Uruguay) and Tim Riffe (University of the Basque Country, Spain) for providing the methodology and files used to calculate the tempo-adjusted total fertility rate applied in the Human Fertility Database (HFD). The files are available at: https://www.demogr.mpg.de/en/publications_databases_6118/publications_1904/mpidr_technical_reports/.

Figure III.1 shows the change in the cohort fertility rate by age and birth cohort in Latin America and the Caribbean from 1935 to 2005. For those aged 49 years, that rate reflects the completed fertility rate (see box III.1). There is an evident decline in the average number of live births of the cohorts over time. The averages for the oldest cohorts (1935–1950) are higher, at around 5 children per woman, with births concentrated between the ages of 20 and 30. As the cohorts advance, the average number of births per woman gradually declines. The trends are lower for generations born from 1985 onward, with a gentler slope, reflecting fewer children and postponement of motherhood. Although older ages are not yet included in the curves for the most recent cohorts (2000 and 2005), a lower average is already observed among younger ages. The same trends are evident across Latin America and the Caribbean.

Figure III.1

Latin America and the Caribbean: cohort fertility for birth cohorts from 1935–2005, by age

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. [online] https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Figure III.2 shows the completed fertility rate (or total cohort fertility rate) relative to the period total fertility rate. Taking previous studies (such as Sobotka, 2003) as a reference, cohort fertility for a specific year is found by calculating the year of that cohort’s mean age at childbearing. Over time, both indicators fall steadily, revealing a continuous decline in the average number of children per woman in Latin America and the Caribbean. In the early 1960s, the completed fertility rate was systematically below the total fertility rate, suggesting that women of childbearing age at the time ended up having fewer children than anticipated, on average, according to the rates for the period. However, beginning in the 2000s, the two measurements tend to converge, and from 2018 onward, the period total fertility rate is below the completed fertility rate.

Figure III.2

Latin America and the Caribbean: total fertility rates and cohort fertility rates, 1963–2024

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Note: The cohort measures refer to the year in which each cohort reached the average mean age at childbearing. It is important to consider that the completed fertility rate estimated on the basis of specific fertility rates does not necessarily correspond to the actual fertility of the birth cohort. Instead, it reflects the fertility of that cohort’s survivors who reside in the country, in each period analysed.

Figure III.3 shows a sustained downward trend in all countries, in both the period total and total cohort fertility rates, reflecting the advance of the demographic transition in the region. In some countries, such as Guatemala, Haiti, Honduras and the Plurinational State of Bolivia, the rates begin at very high levels (more than 6 children per woman), and the decline is more gradual. By contrast, levels were lower from the outset of the period under study in Argentina, Chile, Cuba and Uruguay and the decrease was steadier and occurred earlier. In some cases, such as in Argentina, Cuba and Uruguay, the average for the period fluctuates, reflecting short-term changes in fertility, which are not so evident in the cohort measurement, where changes tend to be more moderate.

Figure III.3

Latin America (20 countries): period total and total cohort fertility rates, 1960–2024

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Note: Countries are grouped by their total fertility rate in 2024.

Figure III.4 shows similar trends in Caribbean countries and territories. However, there are notable differences in initial fertility levels, speed of decline and size of gap between the period and cohort estimates. In Belize, Dominica, Guyana, Saint Lucia and Saint Vincent and the Grenadines, fertility was high at the beginning of the observation period (more than 5 or 6 children per woman), and the decline has been steady, albeit steeper in some decades than in others. By contrast, the historically low fertility levels in Aruba, Barbados and Puerto Rico have rapidly converged towards the replacement rate, or even lower. In most cases, the period rates tend to be higher than the cohort rates in the early decades, suggesting the presence of the tempo effect.

Figure III.4

The Caribbean (27 countries and territories): period total and total cohort fertility rates, 1960–2024

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Note: Countries and territories are grouped by their total fertility rate in 2024.

B. The tempo effect on total fertility rates

The two factors used to measure fertility are tempo (the timing of birth) and quantum (the total number of children). Postponement of childbearing may lead to underestimation of the intensity of period fertility, by lowering the total fertility rate, in what is known as the “tempo effect”. This effect is proportional to the increase in the mean age at childbearing. The experience of several countries has shown that lowest-low period total fertility rates could be explained by the postponement of fertility to a more advanced age (Goldstein et al., 2009; Bongaarts and Sobotka, 2012. However, low fertility cannot be fully explained by the tempo effect, as the tempo and quantum effects interact, and the total fertility rate may remain below the replacement level even when the tempo effect disappears.

Some developed countries have witnessed a rising mean age at first birth and mean age at childbearing since the 1970s (Balbo et al., 2012). As mentioned in chapter II, this process is generally referred to as the postponement of childbearing. This transition towards postponement of first births to later ages has been a core phenomenon in recent decades (Kohler et al., 2002).

Various studies have shown that real fertility levels —or the average number of children born to women by the end of the childbearing period— are not as low as suggested by period fertility rates (Bongaarts and Feeney, 1998; Kohler et al., 2002), prompting some authors to posit that lowest-low fertility could be partially influenced by temporary effects, such as postponement of childbearing. For example, Sobotka (2004) analysed European countries with total fertility rates below 1.3 children per woman from the 1990s to the early 2000s and concluded that these levels had been partly driven by the tempo effect. Without that change in the reproductive calendar, rates would have remained above 1.4 children per woman. Although it cannot be stated with certainty that the currently low levels are temporary in all cases, the postponement effect calls into question interpretation of these figures as indicative of a lasting change without further analysis. Sobotka (2017b) argues that there is no clear threshold for the stabilization of the period total fertility rate. Postponement of childbearing is a key driver of low and unstable fertility trends and shapes the total fertility rate for decades, and many emerging post-transitional countries are expected to experience similar declines in the coming decades.

The tempo effect can significantly influence quantum: postponement and quantum are clearly interrelated, as age at first birth influences the total number of children a woman will have. The tempo effect on total fertility rates refers to a possible rate distortion caused by changes in the reproductive calendar, in other words, when women decide to have children —delaying or advancing childbearing— rather than by a reduction in the total number of children women will have in their lifetimes. This effect is critical in demographic analyses, as failing to consider it can lead to erroneous conclusions about fertility trends. For example, if many women decide to postpone childbearing in a given period, there will be fewer births in that period, even if the number of children they have in their lifetime remains the same. This temporary delay leads to period fertility rates that appear lower than they actually are. This idea has been developed over many years and was formalized by Bongaarts and Feeney (1998), who proposed a method for adjusting period total fertility rates and eliminating tempo-effect distortions, based on adjusting the components by birth order and considering changes in the mean age at childbearing for each order. A simplified method can be used when information by birth order for the average age of fertility is unavailable

(see box III.1).

In Latin America and the Caribbean, the tempo effect is important owing to the sociocultural shifts that are transforming reproductive trends. Factors such as women’s increased participation in education and work, urbanization, and access to contraceptive methods have contributed to the choice of many to postpone childbearing. These changes have reduced total fertility rates in the region, and it is important to consider how much of this decline can be attributed to the tempo effect. Cabella and Pardo (2016) suggest the use of more nuanced fertility indicators in the countries of Latin America and the Caribbean to identify how much of the shift in total fertility rates results from changes in intensity and how much from calendar changes. For example, the health and economic crisis generated by the coronavirus disease (COVID-19) pandemic may have incentivized a delay in fertility to a more advanced age, leading to a momentary decline in the total fertility rate, recorded nine months following the onset of the pandemic (see Economic Commission for Latin America and the Caribbean [ECLAC], 2022b).

Figure III.5 illustrates the variation in the mean age of fertility between 2000 and 2024, revealing a particularly marked growth trend over the last decade. While the mean age remained relatively stable —at around 26.8 years— over the early years of the period analysed, the trend began shifting in 2012, and the mean age then increased steadily, reaching approximately 27.4 years in 2024. This trend reflects the postponement of childbearing in the region.

Figure III.5

Latin America and the Caribbean: mean age of fertility, 2000–2024

(Years)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Figure III.6 illustrates the change in the total fertility rate in Latin America and the Caribbean between 2000 and 2023, contrasting the period estimate with the tempo-adjusted total fertility rate.[1] Both curves trend downward throughout the period under study, reflecting steadily declining fertility levels in the region. The tempo-adjusted total fertility rate is nonetheless systematically higher than the period fertility rate, especially from 2012 onward. This growing divergence highlights the influence of the tempo effect —an increase in age at first birth and the postponement of birth to later ages— which tends to produce underestimates of real fertility in period rates.

Figure III.6

Latin America and the Caribbean: period total and tempo-adjusted total fertility rates, 2000–2023

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

From 2010, the tempo-adjusted total fertility rate stabilizes at around 2.2 children per woman, until 2017; thereafter, it drops precipitously, approaching the period rate. The period total fertility rate also declines steadily, to around 1.85 children per woman in 2023.

Both curves are clearly trending downward in all Latin American countries (see figure III.7). The magnitude of the tempo effect was particularly evident in recent decades, when the tempo-adjusted total fertility rate was higher than the period fertility rate in Colombia, the Dominican Republic, Mexico, Paraguay and Peru, suggesting that observed fertility could be affected by a change in the reproductive calendar. In Argentina, Cuba and Uruguay, where the demographic transition occurred earlier, the two measures differ less, although there are moments when the tempo effect generates noticeable deviations. In Chile, although fertility has also fallen to very low levels in recent years, the gap between the observed total fertility rate and the tempo-adjusted rate is wider, suggesting an intensification of the tempo effect against a backdrop of widespread postponement of childbearing.

Figure III.7

Latin America (20 countries): period total and tempo-adjusted total fertility rates, 2000–2023

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-

archivos-excel.

Note: Countries are grouped by their total fertility rate in 2024.

The trends observed in Caribbean countries and territories (see figure III.8) are more uneven than those in the countries of Latin America. In most cases, as in Belize, Jamaica, Saint Lucia, Saint Vincent and the Grenadines and Suriname, the adjusted total fertility rate tends to be systematically higher than the period total fertility rate, indicating a considerable tempo effect. This suggests that the observed period rates could be underestimating real fertility. By contrast, in Aruba, Barbados, Martinique and Puerto Rico, where the demographic transition occurred sooner and trends are more stable, the gap between the two measures is less marked. Irregular oscillations are also observed in some territories with smaller populations or high mobility linked to migration, such as the Cayman Islands, French Guiana

and Montserrat.

Figure III.8

The Caribbean (27 countries and territories): period total and tempo-adjusted total fertility rates, 2000–2023

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel.

Note: Countries and territories are grouped by their total fertility rate in 2024.

In addition to the simplified method based on total fertility rate and mean age at childbearing, when information disaggregated by birth order is available, more precise adjustments can be made, also as suggested by Bongaarts and Feeney (1998) (see box III.1). Using this second method, the adjusted total fertility rate is calculated as the sum of the tempo-adjusted birth order-specific fertility rates, considering the change in the mean age at birth for each specific order. This approach allows for more in-depth analysis of how postponement varies by birth order and offers a more robust approximation when reproductive calendars diverge significantly between the first child and subsequent children. However, the use of this approach is subject to the availability of age- and birth order-specific data, which are not present in all sources of statistics in the region.

The two approaches were compared to assess the sensitivity of the results to the adjustment method used. As shown in figure III.9, the comparison reveals that while the overall adjusted fertility trends are consistent across both methodologies, adjustment by birth order more accurately reflects changes to the reproductive calendar, especially in the context of a rapid increase in the mean age at childbearing. Moreover, the adjusted fertility time series were smoothed to reduce the year-on-year volatility stemming from statistical fluctuations or minor variations in the mean age. The use of centred moving averages means that the observations on either end of the time series are lost. More specifically, smoothing over a five-year period precludes estimation of the first two and last two years of a series, which is problematic when the aim is to preserve recent information that is highly relevant for analysis. For this reason, a 5/3/1 methodology was used (see box III.1).

Figure III.9

Chile: comparison of observed total fertility rate and tempo-adjusted and smoothed fertility rates, 1992–2022

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel; Max Planck Institute for Demographic Research. Human Fertility Database (HFD). https://www.humanfertility.org/Country/Country?cntr=CHL, for birth orders from the period 1992–2020; and National Institute of Statistics of Chile. Vital statistics, for birth orders from 2021 and 2022.

Note: To allow comparison of the different series shown, the observed total fertility rate is calculated directly on the basis of Chilean vital statistics, with the female population, by age, from World Population Prospects 2024 as the denominator. This differs from figure III.7A, where the observed total fertility rate is taken directly from World Population Prospects 2024 estimates.

In the case of Chile, the observed total fertility rate increasingly diverges from the adjusted fertility rates beginning in 2010, reflecting the effect of the postponement of childbearing on period total fertility rates. The observed total fertility rate trends steadily downward to below 1.3 children per woman. This steep decline, however, may not necessarily reflect a drop in the final number of children that women will bear in their lifetimes. Rather, it is influenced by the displacement of births to more advanced ages, as illustrated in the smoothed, birth order-adjusted total fertility rate. Adjusted total fertility rate curves are systematically higher than those of observed total fertility rates, especially from 2010 onward, when postponement of childbearing intensifies and fertility falls significantly, mainly after 2014.

With regard to the sensitivity of results to adjustment methods, in Argentina, even though both methodologies enable partial correction of the effect of postponement of childbearing, birth-order adjustment offers a solution that is more sensitive to reproductive calendar fluctuations, and thus better captures year-on-year increases and decreases. In particular, smoothing birth order-adjusted figures over five years yields a more stable curve that enables underlying trends to be more clearly identified while continuing to reflect the tempo effect in more recent years. Figure III.10 shows that, while the observed total fertility rate declines sharply to below 1.5 children per woman, the smoothed five-year birth order-adjusted total fertility rate, for example, is more stable, remaining above the replacement threshold throughout the period. This difference suggests that a considerable proportion of the observed drop in fertility could be the result of changes in the reproductive calendar, in particular postponement of the first birth to a later age.

Figure III.10

Argentina: comparison of observed total fertility rate and tempo-adjusted and smoothed fertility rates, 1996–2022

(Number of live births per woman, ages 15–49)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean. Population estimates and projections, 2024 revision. https://www.cepal.org/es/pagina/estimaciones-proyecciones-archivos-excel; National Institute of Statistics and Censuses of Argentina. Vital statistics, for birth orders for the period 1996–2022.

Ultimately, studies on the tempo effect and the postponement of fertility are paramount for population projections (see box III.2). These studies enable a distinction to be made between structural changes in fertility and timing distortions arising from changes to the reproductive calendar, supporting a better understanding of population trends by incorporating these dynamics into population projection scenarios.

Box III.2

Tempo effect considerations in fertility projection scenarios

When women defer childbearing, births are concentrated at older ages, which can artificially reduce the observed total fertility rate in the periods during which births are postponed without implying an actual decrease in the total number of children per cohort. In such a context, below-replacement fertility does not necessarily mean that fertility has declined in structural terms but instead may point to distortions due to changes in the timing of births (Bongaarts and Feeney, 1998). This mismatch between period and cohort fertility is particularly relevant in Latin America and the Caribbean, where the age upon birth of a first child has steadily increased in many countries and territories.

This situation poses significant challenges in establishing population projection scenarios, since conventional methodologies use the period fertility rates as input. However, if there are significant tempo effects on the total fertility rate, the results of the projection may overestimate the pace of fertility decline, generating artificially alarmist scenarios. Incorporating tempo-adjusted measurements makes it possible to distinguish between real declines and simple shifts in timing, enhancing the understanding of projected scenarios.

One recent and illustrative example was the coronavirus disease (COVID-19) pandemic. In many countries in Latin America and the Caribbean, the total fertility rate plummeted between 2020 and 2021, partly because of the postponement of childbearing owing to economic, health and social uncertainty. Although in certain contexts, fertility bounced back somewhat in subsequent years, the episode brought to light how external disruptions can intensify the tempo effect and complicate the interpretation of short-term trends. For this reason, taking these recent events into consideration is essential to avoid exaggerating potentially temporary shifts.

In sum, incorporating the tempo effect into population projection scenarios means more than adjusting the total fertility rate at a given point in time. It also implies recognizing the tempo component of reproductive calendars and its interaction with cohort trends. By taking the tempo effect into account, it becomes possible to mitigate the risk of overestimating the speed of fertility decline in projections, by developing demographic scenarios that reflect the potential duration of the effect.

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Bongaarts, J. and Feeney, G. (1998). On the quantum and tempo of fertility. Population and Development Review, 24(2), 271–291. https://doi.org/10.2307/2807974.

1. [1] Annex A1 (available online at https://bit.ly/CEPAL_OD2025) includes a folder with the files required to replicate the results of the estimates of the tempo effect presented in this chapter, using R software.

IV. Socioeconomic differentials in fertility and their proximate determinants

As described in previous chapters, apart from the overall trend in fertility rates approaching or even falling below the replacement level, the fertility transition in the region has varied from country to country in terms of onset date, speed, and pre-transitional and current levels. There is also variation within countries, associated with socioeconomic inequalities between territories and population groups.

Since the first global studies on this subject, the region has exhibited pronounced fertility differentials between urban and rural areas and between subnational geographical areas and socioeconomic levels. According to a 1978 global study, based on the World Fertility Survey,[1] the region recorded the largest socioeconomic fertility gaps in the world (United Nations, 1978). At the beginning of the present century, reproductive inequality was still very high, with greater gaps in early timing of fertility —mainly adolescent fertility— than in intensity of fertility (Economic Commission for Latin America and the Caribbean [ECLAC], 2006).

By the end of the 2000s, Latin America and the Caribbean was still the most unequal region in the world in both the early timing and intensity of fertility, and comparative estimates in 2010 were consistent with that finding: between the poorest and richest quintiles, the total fertility rate differential was 2.7 times, and the adolescent fertility rate differential was over 4 times. In Africa, although absolute fertility levels were higher, the differentials between the top and bottom income quintiles were smaller (1.8 times for the total fertility rate and 2.5 times for the adolescent fertility rate). Asia registered the lowest levels and narrowest differentials (1.9 times for total fertility and 2.3 times for adolescent fertility), which could be associated with higher levels of coverage and equity in access to sexual and reproductive health services (Rodríguez, Di Cesare and Páez, 2017).

These gaps are linked mainly to the historical concentration of resources that has excluded vast segments of the population from economic and social development, which in pre-transition demographic contexts persisted well into the twentieth century, both in rural areas and in marginal urban areas. This is related to a specific combination of intermediate fertility variables among women in excluded and disadvantaged groups: early sexual debut, patterns of early unions, lack of information, and restrictions on access to effective and timely contraception (Guzmán et al., 2006; United Nations, 1978).

Until the early 1980s, a significant chunk of the literature in Latin America argued that obstacles to the demographic transition, such as social inequality and the structurally heterogeneous development model —with low levels of industrialization and technology and high levels of informality— were insurmountable for groups excluded from development but not for groups who were included and who enjoyed better living conditions and opportunities. This narrative attributed persistent high fertility rates among the poor to the survival strategies that they employed based on functionality from an economic perspective. If true, this would mean that reducing fertility would be difficult without structural transformations in their subsistence conditions (Guzmán, 1997).

According to other studies, the main obstacles to the transition were the cultural and institutional factors that encouraged large families, reinforced the idea that reproduction and domestic work constituted women’s central role, and actively discouraged the exercise of sexual and reproductive rights, including access to fertility regulation methods. These obstacles would most hinder the demographic transition among the very groups that had historically been most disadvantaged (Guzmán, 1997).

Available data show that fertility declined —rapidly, in some cases, and among a range of social groups— owing mainly to the following structural changes that, despite persistent inequality, affected broad swathes of the population: greater access to education for women, especially at secondary and higher levels; access to contraceptive methods; women’s participation in the labour market; urbanization; and evolving lifestyles. However, there are also documented factors that hamper or complicate the reduction of inequality in the intensity and early timing of fertility, including: the persistence of the structural socioeconomic inequality matrix that disproportionately affects excluded groups (ECLAC, 2016); gender norms that reinforce the idea of motherhood as the only path to recognition or life purpose; and the insufficiency of specific public policies or a focus on controlling rather than empowering younger people.

Reducing the socioeconomic inequality affecting reproductive trajectories does not equate to all women or all social groups having the same number of children; rather, it means differences in fertility levels resulting from preferences and decisions, not imposition, discrimination, exclusion or lack of opportunities; in other words, differences would not be the product of sexual and reproductive rights violations. In that regard, this chapter offers an updated look at fertility differentials and intermediate variables, which are fundamental not only for understanding how social and territorial inequality affects reproductive trajectories but also for guiding action in this area.

A. Social and territorial differentials in fertility

In this chapter, territorial and socioeconomic differentials (or gaps) in fertility and its intermediate variables are calculated as the ratio between the rates of the two categories compared in each dimension (in the case of area of residence, rural and urban; in the case of education level, none and higher; and in the case of socioeconomic quintile, first and fifth).

According to the specialized surveys available for this study, territorial (urban versus rural), education and socioeconomic gaps in the total fertility rate and in the adolescent fertility rate have persisted since the 1980s, and total and early fertility levels have been higher among women with the worst living conditions, in particular those in rural areas, those with less education and those in the lowest socioeconomic quintile (see tables IV.1 and IV.2). For the seven countries included in the study,[2] the following observations can be made: (i) in the period of analysis, total fertility rates declined significantly in all the socioeconomic groups considered, and the most recent surveys show low or lowest-low fertility among women with higher education and women in the highest income quintile; (ii) the total fertility rate differential between urban and rural areas is smaller relative to the other two dimensions of comparison, given that no country has a rural rate that is double the urban rate (with the exception of Peru, in the 1986 and 2000 surveys), whereas in several countries, both the rate in the low education group and the rate in the poorest socioeconomic quintile are triple the rates in the respective higher categories; (iii) adolescent fertility rate differentials are higher than total fertility rate differentials; and (iv) more recently, there is evidence of a decrease in socioeconomic fertility differentials.

Table IV.1

Latin America (7 countries): total fertility rate, by area of residence, education level and socioeconomic quintile, and differentials, 1986–2023

(Number of live births per woman aged 15–49 years and ratio between the two estimates being compared)

Country

Year and survey

Total fertility rate

Area of residence

Education level

Socioeconomic quintile

Rural

Urban

Differential

No education

Higher education

Differential

Quintile I

(lowest)

Quintile V

(highest)

Differential

Bolivia

(Plurinational State of)

1989 Demographic and Health Survey

6.6

4.0

1.7

6.4

2.0

3.2

...

2003 Demographic and Health Survey

5.5

3.1

1.8

6.8

2.1

3.2

6.7

2.0

3.4

2023 Survey on Demography and Health

2.9

1.9

1.5

4.1

1.4

2.9

3.4

1.2

2.8

Colombia

1995 Demographic and Health Survey

4.3

2.5

1.7

5.0

1.8

2.8

5.2

1.7

3.1

2005 Demographic and Health Survey

3.4

2.1

1.6

4.5

1.4

3.2

4.1

1.4

2.9

2015 Demographic and Health Survey

2.6

1.8

1.4

3.9

1.6

2.4

2.8

1.3

2.2

Dominican Republic

1986 Demographic and Health Survey

4.8

3.1

1.5

5.2

2.2

2.4

...

1996 Demographic and Health Survey

4.0

2.8

1.4

5.0

1.9

2.6

5.1

2.1

2.4

2019 Multiple Indicator Cluster Survey

2.6

2.3

1.1

3.1

2.0

1.6

3.3

1.9

1.7

Guatemala

1987 Demographic and Health Survey

6.4

4.0

1.6

6.8

3.1

2.2

...

1998/1999 Demographic and Health Survey

5.8

4.1

1.4

6.8

2.8

2.4

7.6

2.9

2.6

2014/2015 Demographic and Health Survey

3.7

2.5

1.5

4.6

1.6

2.9

4.9

1.9

2.6

Haiti

1994/1995 Demographic and Health Survey

5.9

3.3

1.8

6.1

1.9

3.2

7.0

2.3

3.0

2000 Demographic and Health Survey

5.8

3.4

1.7

6.1

2.0

3.1

6.8

2.7

2.5

2016/2017 Demographic and Health Survey

3.9

2.1

1.9

4.9

1.2

4.1

5.4

1.6

3.4

Mexico

1987 Demographic and Health Survey

6.0

3.3

1.8

6.1

2.0

3.1

...

1997 National Demographic Trends Survey

3.9

2.6

1.5

4.2

2.1

2.0

...

2023 National Demographic Trends Survey

2.1

1.4

1.5

2.4

1.4

1.7

...

Peru

1986 Demographic and Health Survey

6.3

3.1

2.0

6.6

1.9

3.5

...

2000 Demographic and Health Survey

4.3

2.2

2.0

5.1

1.8

2.8

5.5

1.6

3.4

2022 Demographic and Family Health Survey

2.8

1.7

1.6

4.6

1.5

3.1

...

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Demographic and Health Surveys. https://www.statcompiler.com/en/; Multiple Indicator Cluster Surveys. https://mics.unicef.org/; National Institute of Statistics and Geography of Mexico. Demographic and Health Survey. https://www.ine.gob.bo/index.php/censos-y-banco-de-datos/censos/bases-de-datos-encuestas-sociales/; National Demographic Trends Survey. https://www.inegi.org.mx/programas/enadid/2023/; and National Institute of Statistics and Informatics of Peru. Demographic and Family Health Survey. https://proyectos.inei.gob.pe/endes/.

Table IV.2

Latin America (7 countries): adolescent fertility rate, by area of residence, education level and socioeconomic quintile, and differentials, 1986–2023

(Number of live births per 1,000 women aged 15–19 years and ratio between the two estimates being compared)

Country

Year and survey

Adolescent fertility rate

Area of residence

Education level

Socioeconomic quintile

Rural

Urban

Differential

No education

Higher education

Differential

Quintile I

(lowest)

Quintile V

(highest)

Differential

Bolivia

(Plurinational State of)

1989 Demographic and Health Survey

156

67

2.3

141

22

6.4

...

2003 Demographic and Health Survey

124

68

1.8

152a

37

4.1

...

2023 Survey on Demography and Health

88

35

2.5

65

11

5.7

...

Colombia

1995 Demographic and Health Survey

137

74

1.9

167a

13

12.8

180

24

7.5

2005 Demographic and Health Survey

128

79

1.6

192a

26

7.4

155

37

4.2

2015 Demographic and Health Survey

118

62

1.9

208a

29

7.2

130

21

6.2

Dominican Republic

1986 Demographic and Health Survey

126

86

1.5

264

22

12.0

...

1996 Demographic and Health Survey

160

87

1.8

274

16

17.1

234

30

7.8

2019 Multiple Indicator Cluster Survey

110

66

1.7

162b

33

4.9

145

28

5.2

Guatemala

1987 Demographic and Health Survey

159

90

1.8

196

39

5.0

...

1998/1999 Demographic and Health Survey

139

86

1.6

210

43

4.9

182

32

5.7

2014/2015 Demographic and Health Survey

112

65

1.7

180

13

13.8

141

40

3.5

Haiti

1994/1995 Demographic and Health Survey

92

58

1.6

145

32c

4.5

105

25

4.2

2000 Demographic and Health Survey

108

66

1.6

192

43c

4.5

101

54

1.9

2016/2017 Demographic and Health Survey

70

35

2.0

189

32c

5.9

105

19

5.5

Mexico

1987 Demographic and Health Survey

127

72

1.8

216

10

21.6

...

1997 National Demographic Trends Survey

...

165

27

6.1

...

2023 National Demographic Trends Survey

70

37

1.9

117

23

5.1

...

Peru

1986 Demographic and Health Survey

138

54

2.6

132a

17

7.8

...

2000 Demographic and Health Survey

118

45

2.6

147

23

6.4

163

23.0

7.1

2022 Demographic and Family Health Survey

83

32

2.6

...

...

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Demographic and Health Surveys. https://www.statcompiler.com/en/; Multiple Indicator Cluster Surveys. https://mics.unicef.org/; National Institute of Statistics and Geography of Mexico. Demographic and Health Survey. https://www.ine.gob.bo/index.php/censos-y-banco-de-datos/censos/bases-de-datos-encuestas-sociales/; National Demographic Trends Survey. https://www.inegi.org.mx/programas/enadid/2023/; and National Institute of Statistics and Informatics of Peru. Demographic and Family Health Survey. https://proyectos.inei.gob.pe/endes/.

a Refers to women with no education or with some primary education.

b Refers to women with some primary education.

c Refers to women with secondary education.

With regard to the total fertility rate, the differentials between rural and urban areas and between socioeconomic quintiles decreased in almost all countries between the base year or period and the most recent reference year or period for which data were available, except Haiti, where differentials for all three dimensions increased, and Guatemala, where the differential in education levels increased. Nevertheless, the data in table IV.1 are insufficient to determine the most recent regional trend in fertility differentials, much less the extent to which they result from the exercise of free and autonomous reproductive preferences as opposed to the socioeconomic and territorial inequalities that continue to affect reproductive trajectories in

the region.

Adolescent fertility rates, meanwhile, fell in all countries included in the analysis in both urban and rural areas. Urban-rural differentials, however, increased in four of the seven countries, remained stable in two and decreased in one (see table IV.2). While the adolescent fertility rate did not necessarily fall in all socioeconomic quintiles, the rate differential between education levels decreased in five of the seven countries (increasing only in Haiti and Guatemala) and the differential between the lowest and highest socioeconomic quintiles decreased in three of the four countries with available data (increasing only in Haiti).

In summary, according to data from specialized surveys of seven countries of the region, fertility levels declined significantly in all groups, and the differentials between urban and rural areas and socioeconomic quintiles also trended downward. Figures for the adolescent fertility rate, specifically, are less consistent: rates did not systematically decline for all socioeconomic groups, and differentials increased between rural and urban areas but decreased between the top and bottom socioeconomic quintiles. However, given the limited number of countries considered in the analysis, its results cannot be generalized. Broader and more representative studies are therefore needed to gain a more accurate and comprehensive understanding of these regional trends.

Typically, analysis of reproductive inequality at the territorial level has focused primarily on the urban-rural distinction. This makes sense, given the availability of a body of information regarding differences in reproductive behaviours between urban and rural areas, and also because all theoretical approaches to this subject have considered urbanization to be an enabling factor in the demographic transition. However, analysing the trend in differentials presents a methodological challenge, as the relative weight and social position of urban and rural areas change over time. A more substantive limitation is found in the lack of homogeneity and the presence of major social inequalities in rural and urban environments, together with specific cultural factors that influence reproductive decisions and behaviours.[3] What happens in large cities is particularly consequential in a region in which 80% of the population lives in urban areas and at least one third lives in large cities where the socioeconomic inequalities are enormous.

Table IV.3 shows the total fertility rate and the adolescent fertility rate for five metropolitan areas in countries of the region, disaggregated by ad hoc socioeconomic quintile.[4] The following conclusions regarding levels, trends and underlying socioeconomic gaps can be drawn from this information: (i) total and adolescent fertility fell in the twenty-first century in all five metropolitan areas examined (except adolescent fertility in Lima, which did not change); (ii) in the five metropolitan areas, the most recent total fertility rate is below 3 children per woman in all socioeconomic quintiles, with the exception of Guatemala City, where the poorest quintile has a rate slightly above 3 children per woman (i.e. the fertility transition cut across all socioeconomic quintiles); (iii) in three of the five metropolitan areas (Bogotá, Mexico City and Santiago), the total fertility rate dropped below the replacement level in the 2010s and declined further following the outbreak of the coronavirus disease (COVID-19) pandemic; (iv) in all five metropolitan areas, the highest socioeconomic quintile has a lowest-low total fertility rate (below 1.3 children per woman), according to the most recent estimate; (v) in all the metropolitan areas except Guatemala City, the decrease in the total fertility rate was smaller than the decrease in the adolescent fertility rate; (vi) in all the metropolitan areas, the adolescent fertility rate differential was greater than the total fertility rate differential; (vii) the all-round decline in the total fertility rate did not eliminate socioeconomic differentials (which increased slightly in three cities, remained unchanged in one and decreased in the other) across the board; and (viii) the adolescent fertility rate fell in all socioeconomic quintiles but to a lesser degree in the lower quintiles, resulting in an increase in the differential in four of the cities that was particularly significant in three (see table IV.3).

Table IV.3

Latin America (5 selected cities): adolescent fertility rate and total fertility rate, by ad hoc socioeconomic quintile, and differentials and trends, 2000s and 2010s

(Number of live births per 1,000 women aged 15–19 years and 15–49 years and ratio between quintiles)

City

Census

Fertility rate

Quintile I

(lowest)

Quintile II

Quintile III

Quintile IV

Quintile V

(highest)

Total

Differential

(quintile I/quintile V)

Guatemala City

2001

AFR

121

106

53

26

9

71

13.4

TFR

4.9

3.6

2.6

2.3

2.0

3.2

2.4

2018

AFR

85

75

32

19

6

51

14.2

TFR

3.3

2.4

2.0

1.7

1.3

2.2

2.5

Lima

2007

AFR

63

52

33

18

5

38

12.6

TFR

2.6

2.4

2.3

2.0

1.41

2.2

1.9

2017

AFR

62

49

27

13

5

35

12.4

TFR

2.6

2.4

2.1

1.9

1.1

2.1

2.3

Valley of Mexico Metropolitan Area

2010

AFR

96

83

30

16

5

54

19.2

TFR

2.7

2.5

2.2

1.8

1.3

2.2

2.1

2020

AFR

69

54

28

10

2

39

34.5

TFR

2.4

2.2

1.89

1.6

0.93

1.9

2.6

Greater Santiago Metropolitan Area

2002

AFR

86

57

41

13

4

40

21.5

TFR

2.9

2.3

2.4

2.1

1.0

2.1

2.8

2017

AFR

71

49

20

3

1

28

71.0

TFR

2.3

2.3

1.6

1.6

0.8

1.8

3.0

Metropolitan Area of Bogotá

2005

AFR

113

74

54

21

10

56

11.3

TFR

2.9

2.3

1.95

1.67

1.12

2.1

2.6

2018

AFR

43

54

29

5

1

35

43.0

TFR

2.2

2.0

1.3

1.8

1.1

1.6

1.9

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Rodríguez Vignoli, J. and San Juan, V. (2023). El descenso de la fecundidad y la maternidad adolescente en América Latina y su desigualdad socioterritorial: el caso de cinco grandes ciudades. Revista Latinoamericana de Población, 17. https://doi.org/10.31406/relap2023.v17.e202308.

Note: Adolescent fertility rate, AFR; total fertility rate, TFR.

B. Socioeconomic gaps in the postponement of childbearing

Analysing the percentage of women who are mothers provides information not only on childbearing, including early childbearing, but also on the postponement of first-order birth and nulliparity (i.e. childlessness) at different ages. The decline in fertility during the demographic transition was driven by the decline in the number of higher-order births rather than by an increase in the proportion of women without children (see chapter II). However, recent data should be analysed for signs of a widespread and marked delay in first-order birth and an increase in the proportion of women without children in the region, as lowest-low fertility tends to be associated with both.

1. Childbearing by age and household socioeconomic quintile

This section presents an examination, based on household surveys of a limited and not necessarily representative sample of countries,[5] of levels and differentials in childbearing in four age groups: (i) the 15–19 age group, in which childbearing is associated with structural inequalities and other well-documented adversities (ECLAC, 2025); (ii) the 20–24 age group (early youth) and the 25–29 age group (late youth), in which childbearing data make it possible to analyse the occurrence or postponement of childbearing in youth; and (iii) the 40–44 age group, in which these data facilitate a historical analysis of childbearing and its opposite, final nulliparity, as this cohort reached its reproductive peak around the turn of the century, when it was almost universally the case that women had at least one child.

In the 15–19 age group, figure IV.1 shows a sharp drop in childbearing since the 2010s, confirming the aforementioned decline in adolescent fertility (ECLAC, 2025), which has been cross-cutting from a socioeconomic perspective, as adolescent childbearing has decreased in all income quintiles (or well-being quintiles, in the case of Peru). However, in five of the six countries, the decline was more pronounced in the richest quintile, resulting in an increase in differentials between 2010 and the most recent year considered. In two countries (Chile and Mexico), the differential shrank in the second part of the period of analysis, and in a third (Plurinational State of Bolivia), the differential stabilized.

Figure IV.1

Latin America (6 countries): proportion of women aged 15–19 who are mothers, total and by poorest and richest socioeconomic quintiles (I and V), and differentials (quintile I/quintile V), 2010–2023 (approximate years)

(Percentages and ratio between quintiles)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Household Survey Data Bank (BADEHOG); Demographic and Health Survey, 2010 and Demographic and Family Health Survey 2014/15 and 2024, for Peru.

a In Peru, quintiles refer to well-being. The indicator includes women in their first pregnancy.

b In Uruguay, the trend, though upward, is impossible to calculate, because there were no mothers in this age group in the richest quintile in 2023. The upward trend line in this case is symbolic.

In summary, figure IV.1 shows a widening of adolescent childbearing gaps in some countries and a recent narrowing in others, which could be associated with successful policies that have ensured sexual and reproductive rights for groups of adolescents historically excluded from sexual and reproductive health services and from access to efficient, timely and quality contraception.

The percentage of mothers in the 20–24 age group fell less sharply than in the 15–19 age group in the five countries analysed, except in Chile, where the drop was more pronounced (see figure IV.2). Data from the 2020s show that in Guatemala, almost half of women aged 20–24 were already mothers, and in two other countries (Plurinational State of Bolivia and Mexico), the proportion was more than one third. In Chile and Uruguay, meanwhile, the most recent survey data show that the proportion is 20%, suggesting a longer postponement of first-order birth for a broad majority of women.

Figure IV.2

Latin America (5 countries): proportion of women aged 20–24 who are mothers, total and by poorest and richest socioeconomic quintiles (I and V), and differentials (quintile I/quintile V), 2011–2023 (approximate years)

(Percentages and ratio between quintiles)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Household Survey Data Bank (BADEHOG).

Regarding differentials in the postponement of childbearing in early youth, the most recent survey data show that in four of the five countries, 45% or more of young women aged 20–24 in the poorest quintile have already become mothers (the exception is Chile, where the proportion is just one third, according to the 2022 data), which represents a significant drop from 2010. Among the same age group in the richest quintile, the proportion, according to the most recent survey, is 10% or less in all the countries (except in Guatemala, where it reached 25%), and declined steadily during the period of analysis. Because this percentage decreased more in the richest quintile than in the poorest, the differential in childbearing among young women aged 20–24 increased considerably in Chile and also rose in the Plurinational State of Bolivia and Mexico. In Guatemala, meanwhile, the differential remained stable, and in Uruguay, it fell sharply (see figure IV.2). These differences and low fertility levels highlight the need to research the underlying factors associated with initiation or postponement of childbearing in each socioeconomic group, not only to understand the current trends but, more crucially, to design policies in accordance with the needs of each group, with the aim of closing gaps in the exercise of sexual and reproductive rights for all women.

The percentage of mothers in the 25–29 age group decreased by a relatively modest amount between 2010 and the most recent year of analysis, except in Chile, where the drop was more pronounced (see figure IV.3). Despite this trend, data from the 2020s show that in the Plurinational State of Bolivia, Guatemala and Mexico, a broad majority of women aged 25–29 have already become mothers. In Chile and Uruguay, half the women in this age group have not had children, indicating a greater postponement of first-order birth. Postponement among women in this group may have more to do with factors hindering the realization of their reproductive rights; women who wish to have children may be unable to do so owing to, for example, incompatibility with other activities and plans, financial constraints or biological difficulties.

Figure IV.3

Latin America (5 countries): proportion of women aged 25–29 who are mothers, total and by poorest and richest socioeconomic quintiles (I and V), and differentials (quintile I/quintile V), 2011–2023 (approximate years)

(Percentages and ratio between quintiles)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Household Survey Data Bank (BADEHOG).

Among young women aged 25–29 in the poorest socioeconomic quintile, 80% or more have already become mothers (except in Chile, where the proportion was around 78% in 2022). This figure does not represent a significant change with respect to 2010. In contrast, among young women in this age group in the richest socioeconomic quintile, the percentage decreased significantly in the 2010s, and in the most recent year considered, motherhood was an infrequent condition: the proportion did not exceed 30% in any country except Guatemala, where it reached 43% in 2022. These trends translate into a sustained increase in the differential in childbearing in youth in the five countries, but more detailed analysis of determinants in each country according to their territorial and social contexts is needed (see figure IV.3).[6]

In the 40–44 age group, the percentage of mothers not only did not fall but even increased in some cases (see figure IV.4). Indeed, 85% of women in this age group are mothers according to the most recent survey data. Among women in the richest quintile, the percentage of mothers is lower, but the differential between the richest and poorest quintiles is much smaller than in the other age groups analysed. Moreover, in the richest quintile, the percentage of mothers increased in several countries, reducing the differential. Only Chile experienced a clear increase in the differential as a result of the decrease in the percentage of mothers in the richest quintile (73% in 2022). This makes it very likely that final nulliparity will surpass 20% in this quintile, a level that for several decades has characterized groups with lowest-low fertility.

It is worth mentioning that the differential in this age group is smaller than in adolescence or even early youth, because final nulliparity is more likely to be associated with an inability to fulfil reproductive ideals and intentions, currently more common among women in higher socioeconomic quintiles.

Figure IV.4

Latin America (5 countries): proportion of women aged 40–44 who are mothers, total and by poorest and richest socioeconomic quintiles (I and V), and differentials (quintile I/quintile V), 2011–2023 (approximate years)

(Percentages and ratio between quintiles)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Household Survey Data Bank (BADEHOG).

C. Differentials in reproductive ideals

Aspirations regarding fertility are fluid and may change over time, influenced by personal experiences, intimate relationships, social norms and economic conditions, as well as by factors relating to the individual and their environment that vary by gender, among other elements (Iacovou and Tavares, 2011). In addition, the availability and acceptability of contraceptive methods play a crucial role in the fulfilment of reproductive intentions (Yeatman and Sennott, 2024).

Reproductive preferences are the subject of extensive debate regarding how they impact fertility levels and trends and how they are measured (United Nations Population Fund [UNFPA], 2025a; Yeatman and Sennott, 2024; Ní Bhrolcháin and Beaujouan, 2019; Santelli et al., 2009; Fernández, Pardo and Pedetti, 2019). The concept of “reproductive ideals”—that is, generic and abstract statements about the number of children one would like to have, even if there is no intention or planning to realize that ideal— is criticized precisely because it is not connected to decisions. However, it continues to be used as a benchmark for projecting future fertility trends (Sobotka, 2020). Specialized and general surveys are used for measuring reproductive ideals because they are suited to the simplicity of collecting data for this indicator, making it possible to capture, albeit imperfectly, ideals and expectations regarding childbearing and number of children.[7]

In the past, specialized demographic and health surveys consistently showed fertility levels above reproductive ideals, both nationally and within each socioeconomic group, and these differentials were sometimes larger among women living in poorer conditions than among those who were better off (United Nations, 1978).

In light of the considerable declines and greater socioterritorial convergence in fertility levels, it is worth analysing trends and differentials in reproductive ideals by socioeconomic status. Table IV.4 shows the figures available for four countries at two points in time, with the base year in the 1990s and the most recent year in the 2010s (unfortunately not the current decade). All cases exhibit similar patterns and trends. Reproductive ideals have varied little in recent decades, and their slight decline would appear to be associated more with structural transformations, such as progress in education. In contrast, fertility has declined steadily, resulting in a convergence between reproductive ideals and fertility rates.[8] This pattern suggests that cultural changes surrounding reproductive ideals preceded the observed adjustment in reproductive behaviour, and that this adjustment was made possible by increased availability of and access to sexual and reproductive health services and effective contraceptive methods. It should also be noted that in Colombia and Guatemala, differentials in the most recent year (2015) show fertility falling slightly short of reproductive ideals.

Table IV.4

Latin America (4 countries): ideal number of children and total fertility rate, by socioeconomic quintile,a selected years

(Average number of children and number of live births per woman aged 15–49 years)

Country

Year and survey

Indicator

Total

Socioeconomic quintile

I

(lowest)

II

III

IV

V

(highest)

Bolivia (Plurinational State of)

1994 Demographic and Health Survey

Ideal

2.5

2.5

2.5

2.4

2.5

2.6

Total fertility rate

4.6

7.2

6.7

5.0

3.7

2.4

2016 Demography and Health Surveyb

Ideal

2.1

2.1

2.3

2.0

2.1

Total fertility rate

2.9

4.6

4.0

3.1

2.0

Colombia

1990 Demographic and Health Survey

Ideal

2.6

3.0

2.8

2.5

2.4

2.4

Total fertility rate

2.8

4.9

3.4

2.8

2.3

1.7

2015 Demographic and Health Survey

Ideal

2.2

2.6

2.2

2.1

2.0

1.9

Total fertility rate

2.0

2.8

2.3

1.9

1.5

1.3

Guatemala

1995 Demographic and Health Survey

Ideal

3.6

4.6

4.4

3.9

3.2

2.8

Total fertility rate

5.1

8.0

6.9

5.6

3.9

2.4

2014/2015 Demographic and Health Survey

Ideal

3.3

4.1

3.7

3.4

2.9

2.6

Total fertility rate

3.1

4.9

3.9

3.0

2.5

1.9

Peru

1996 Demographic and Health Survey

Ideal

2.5

2.8

2.5

2.4

2.4

2.4

Total fertility rate

3.5

6.6

4.6

3.4

2.6

1.7

2012 Demographic and Health Survey

Ideal

2.3

2.5

2.4

2.3

2.3

2.3

Total fertility rate

2.6

4.0

3.1

2.5

2.0

1.7

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of information from STATcompiler and reports from the Demographic and Health Survey, 2016, of the Plurinational State of Bolivia.

a The total fertility rate measures the number of live births per woman aged 15–49 over the last three years, while the ideal number of children (ideal) reflects women’s reproductive preferences (lifetime expectation) at the time of interview.

b In this case, the data in the socioeconomic quintile columns correspond to quartiles of education level: I = none; II = primary education; IV = secondary education; and V = higher education.

In three of the four countries analysed in table IV.4, there were no significant differences between the reproductive ideals of the different socioeconomic groups; the exception is Guatemala, where the ideal number of children among women in the lowest quintile was significantly higher than in the highest quintile in both the base year and the most recent year considered.

Although differentials between the observed fertility rate and the ideal number of children have narrowed in all quintiles, there is significant polarization. On the one hand, fertility rates among women in the poorest quintile, though closer to ideal figures than before, continue to be higher than desired, reflecting the continued (if less acute) impact of structural inequality factors on the effective exercise of reproductive rights. On the other hand, among women in the richest quintile, differentials are consistently negative: in all the countries studied, this group’s observed fertility rate was below its reproductive ideals. This, too, points to a gap in the exercise of reproductive rights, just in the other direction. In Colombia and Guatemala (2015), this pattern is observed in the top three quintiles, and in Peru (2012), the top two.

This scenario clearly shows that socioeconomic inequality influences opportunities to fully exercise reproductive rights, with differentiated effects on each social group’s ability to meet reproductive expectations. From a public policy perspective, this diagnosis highlights the need to apply differentiated and specific approaches: measures aimed at removing structural barriers to access to sexual and reproductive health services should be strengthened for the most vulnerable groups, while for the higher income groups, it is essential to address factors related to work-life balance and to undertake critical analysis of the institutional, cultural and social contexts in which reproductive decisions are made.

D. Socioeconomic inequalities and their impact on intermediate variables

1. Sexual activity and union

Among young women in the poorest socioeconomic quintile, sexual debut occurs at an earlier age compared with other quintiles, which is consistent with the differentials in the total fertility rate and, above all, the differentials in the adolescent fertility rate and in adolescent childbearing discussed above. In general, in the twenty-first century thus far, sexual activity has increased (Gayet and Júarez, 2025) and the age of sexual debut has decreased (Rodríguez Vignoli and San Juan, 2020), which is not in line with the downward trends in the total fertility rate and the adolescent fertility rate. Therefore, sexual activity and debut can hardly be considered a relevant variable to explain these trends and social gaps.

The proportion of women in some form of union, meanwhile, has tended to decrease in adolescence and young adulthood since 2000, with some ups and downs and a gentler decline overall (Hailu and Beyene, 2025; ECLAC, 2023b), which is consistent with the downward trends in the total fertility rate and the adolescent fertility rate. Socioeconomic differentials in unions follow an irregular pattern, although a comparison of data for 2000 and 2023 shows a narrowing in adolescence and in the 20–24 age group and a slight widening in the 25–29 age group (see figure IV.5).

Figure IV.5

Latin America (18 countries):a proportion of women in some form of union, total and by poorest and richest socioeconomic quintiles (I and V), and differentials (quintile I/quintile V), 2000, 2010, 2017 and 2023

(Percentages and ratio between quintiles)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Household Survey Data Bank (BADEHOG).

a Cuba and Haiti are not included.

2. Contraceptive protection

For decades, there has been a sustained increase in women’s use of modern contraceptive methods, which have become the primary means of exercising reproductive rights and avoiding unwanted pregnancies. This has been the most decisive intermediate variable in the decline in total fertility and, more recently, adolescent fertility, as well as postponement of childbearing (Cardona et al., 2025).

There has been a global decrease in the socioeconomic differential in modern contraceptive use, which has contributed to the reduction of total fertility rate differentials between and within countries (Cardona et al., 2025). A narrowing of the socioeconomic differential in the use of modern contraceptives is also observed among women in some form of union in several countries of the region (see figure IV.6), with an inarguably decisive impact on shrinking total fertility differentials.

Figure IV.6

Latin America (7 countries): proportion of women aged 15–49 who are in some form of union and use modern contraception, by poorest and richest socioeconomic quintiles (I and V), and differentials (quintile I/quintile V), 1990 and 2020 (approximate years)

(Percentages and ratio between quintiles)

Source: Latin American and Caribbean Demographic Centre-Population Division of the Economic Commission for Latin America and the Caribbean, on the basis of Demographic and Health Surveys. https://www.statcompiler.com/en/; Multiple Indicator Cluster Surveys. https://mics.unicef.org/; National Institute of Statistics and Geography of Mexico. Demographic and Health Survey. https://www.ine.gob.bo/index.php/censos-y-banco-de-datos/censos/bases-de-datos-encuestas-sociales/; National Demographic Trends Survey. https://www.inegi.org.mx/programas/enadid/2023/; and National Institute of Statistics and Informatics of Peru. Demographic and Family Health Survey. https://proyectos.inei.gob.pe/endes/.

Note: DFHS, Demographic and Family Health Survey; DHS, Demographic Health Survey; NEFHS, National Epidemiology and Family Health Survey; MICS, Multiple Indicator Cluster Survey; SDH, Survey on Demography and Health.

Until the early 2010s, adolescents —in particular those of low socioeconomic status— faced considerable difficulties in accessing appropriate and effective contraceptive methods from the time of sexual debut (Rodríguez, Di Cesare and Páez, 2017). This was reflected in the adolescent fertility rate’s resistance to decline and in the widening of the socioeconomic differential. However, recent rapid and significant increases in access to relevant and effective contraception for adolescents of low socioeconomic status from the time of sexual debut could be helping not only to improve the exercise of reproductive rights and prevent unwanted pregnancies but also to reduce social gaps in adolescent fertility.

1. [1] See https://wfs.dhsprogram.com/.

2. [2] Tables IV.1 and IV.2 only include countries that have at least two specialized surveys conducted in the 1980s, 1990s or 2000s and an additional survey corresponding to the most recent available date in the 2010s or 2020s (ranging from 2014 to 2023, depending on the country).

3. [3] Rural areas that are home to Indigenous communities, for example, are shaped by their ancestral heritage, including cultural patterns and practices that are essential to their identity and collective functioning.

4. [4] Both rates were calculated applying the relational Gompertz model, using census microdata. Ad hoc socioeconomic quintiles were calculated on the basis of two variables: years of schooling of the head of household, and household overcrowding. For further details, see Rodríguez Vignoli and San Juan (2023).

5. [5] These countries are the only ones in the region that systematically include a survey question on number of children born and also have data available in the Household Survey Data Bank (BADEHOG) of ECLAC. In figure IV.1, Peru is additionally included, with data from the 2010 Demographic and Health Survey and the 2014/2015 and 2024 Demographic and Family Health Survey; in this case, quintiles do not refer to income but rather to well-being.

6. [6] In Uruguay, the differential remained constant at a very high level throughout the entire period but increased in the most recent year considered.

7. [7] For example, survey data from the Institute for Youth of Chile show that, between 2018 and 2022, the proportion of women who wanted to become mothers decreased from 64.8% to 55% (National Institute for Youth of Chile, 2022). However, it is well established that these statements are not immutable (Yeatman and Sennott, 2024).

8. [8] The total fertility rate is a period indicator, while the “ideal number of children” expresses a preference over the life cycle of a cohort. They are not strictly comparable and may be affected by calendar effects (postponement) and changes in composition within quintiles; the comparison is used for descriptive purposes only, to guide the interpretation of patterns.

V. Public programmes and policies in a low-fertility context

This chapter focuses on policies related to the context of low fertility, in particular on those termed “family policies”, and discusses whether they contribute to enabling women to have the number of children they wish during their lifetime, in line with the main international and regional rights instruments.

In a context of demographic transformation and persistent inequalities, several countries around the world —especially in Europe— have begun to implement programmes and policies to reduce the barriers that people, especially women, face in making reproductive decisions. With these measures, governments seek not only to protect the right to decide, but also to address broader challenges, such as population ageing and increasing pressure on social protection, health, employment and care systems. One of the reasons for such measures is the gap between the number of children that individuals and families consider ideal and the number they actually manage to have. This discrepancy not only suggests possible dissatisfaction in relation to total family size, but may also be evidence of structural limitations that hinder the realization of reproductive aspirations (McDonald, 2006; Gietel-Basten et al., 2022).

Cutting across all these factors is the structural difficulty in reconciling childcare responsibilities with working life, particularly in the absence of public policies to facilitate a balance in this respect. The lack of adequate parental leave, flexible working hours or accessible and quality childcare services represents a daily obstacle for many women and families (Gauthier and Philipov, 2008).

Similarly, the disconnect between women’s increased labour market participation and the stagnant state of redistribution of responsibilities in the domestic sphere (McDonald, 2000; Esping-Andersen, 2013) do much to perpetuate a hostile setting for work-life balance (Mills et al., 2011). As a result, faced with the prospect of assuming a double or triple role (in the productive, reproductive, domestic and caregiving spheres, and sometimes also in the community), without the support of adequate institutional policies leads many women to postpone or forgo motherhood.

Against this backdrop, family policies should aim to create conditions in which people can make free, informed and viable reproductive decisions in supportive social and institutional environments. This implies not only reducing the economic and work-related costs associated with childrearing, but also changing the cultural norms and social arrangements that make it difficult to reconcile reproductive and professional life today, especially for women (Cabella and Nathan, 2018).

Family policies have gained importance in Latin America and the Caribbean, as they have in various European settings. They aim to create conditions in which people can balance work responsibilities with parenting, access adequate childcare services with the institutional support to ensure their children’s well-being. These policies encompass a broad range of strategies, including cash transfers, paid parental leave, access to childcare services, tax incentives and flexible working arrangements (Pardo and Varela, 2013; Gauthier and Gietel-Basten, 2024).

A. Financial support for families with children

Direct financial support for families is one of the most common strategies adopted in the battery of family policies in response to low fertility. This support is intended to alleviate childrearing costs through cash transfers, grants upon children’s birth or monthly allowances for each child born into the home. However, several studies have found that transfers tend to have modest or even no effects on fertility levels (Pardo, Pedetti and Soto, 2025). According to Gauthier and Philipov (2008) and Mills et al. (2011), financial support, whether direct or indirect, may accelerate the timing or avoid postponement or births (tempo effect), rather than significantly increase the total number of children per woman (quantum effect).

These effects of these types of incentives can often be more visible in lower-income social sectors, as they reduce the immediate economic pressure associated with parenthood. However, these supports alone are not sufficient to reverse sustained low fertility trends, as they do not address other structural and social factors that condition reproductive decisions. To be effective, they must be complemented by measures to address the multiple dimensions that affect current reproductive behaviours, including the balance between work and family life, as well as reducing the direct costs of childcare.

B. Parental leave

Another key pillar of family policies concerns parental leave, which is a workers’ right in most countries of the world. However, the duration of parental leave, the amounts involved and to whom they are available vary widely. In some cases, leave is exclusively for mothers (maternity leave); in others, leave is also extended to fathers (paternal leave), and in some contexts, shared or transferable leave is offered to both parents (parental leave). Parental leave allows mothers and fathers to take temporary absences from work for the birth or adoption of their children, without losing their labour rights. However, several studies have shown that unless parental leave is designed with a gender focus, it can have contradictory effects on equity. Instead of promoting co-responsibility, it may reinforce the idea that childcare is primarily a female responsibility and thereby worsen the penalization of women in the labour sphere. Where this occurs, maternity can translate into loss of income, fewer opportunities for advancement and reduced long-term economic security, while entrenching the burden of household and childcare almost exclusively within the female population (Gauthier and Gietel-Basten, 2024; England and Folbre, 1999; McDonald, 2006).

To prevent the responsibility for caregiving from continuing to fall disproportionately on women, the literature recommends that leave be structured equally between women and men, establishing non-transferable periods for each parent —especially fathers— to increase its uptake. Leave must be adequately remunerated for both parents, as men tend not to make use of it when it entails a significant loss of income (Gauthier and Gietel-Basten, 2024).

Gauthier and Philipov (2008), Mills et al. (2011) and Pardo, Pedetti and Soto (2025) agree that the availability of leave alone is not sufficient. The information available suggests that leave is more likely to have a positive effect on fertility when it is long enough to allow mothers to recover and adapt initially to having children, but not so long as to adversely affect their careers. Although parental leave represents a valuable tool in child and maternity support policies, its transformative potential thus depends largely on how it is designed, on the assurance of being able to re-enter employment and, above all, on a cultural change to underpin an equitable distribution of family responsibilities.

C. Care services

Childcare services also play a crucial role in family policies by facilitating mothers’ return to work and ensuring an appropriate setting for children’s development. England and Folbre (1999) argue that care services should be understood not as a mere aid to families, but as a social investment that redistributes the costs of care work. From this point of view, childcare should be assumed not solely by families with children, but also by the State and society as a whole. This approach is shared by other authors, who believe that care policies should be built into universal social protection systems and should include not only access to services, but also the time devoted by families themselves and the necessary resources, promoting gender equality and intergenerational solidarity (Esping-Andersen, 2011; EU-LAC Foundation, United Nations Entity for Gender Equality and the Empowerment of Women, Economic Commission for Latin America and the Caribbean, INMUJERES (Mexico) and Global Alliance for Care, 2023).

Childcare services thus not only underpin the structure of family policies, but also represent a key strategy for promoting gender equality, ensuring children’s rights and avoiding women being forced to give up their professional development. Within Latin America, the experience of Brazil, documented by Castanheira (2024), shows that the policy of expanding public childcare centres increased female labour participation, especially by married mothers without complete secondary education.

Recent studies have also shown that the availability of childcare services has positive effects on fertility, especially where these policies are built into a co-responsibility framework and are not limited to ad hoc or welfare measures. However, Gauthier and Gietel-Basten (2024) caution that, if these effects are to be sustainable, it is necessary not only to expand coverage, but also to ensure the quality, continuity and professionalization of childcare.

D. Flexible work arrangements

Lastly, policies to promote flexible organization of work time —through options such as adaptable schedules, remote work or reduced working hours— have become increasingly important as tools to facilitate the reconciliation of family and professional life. However, as England and Folbre (1999) warn, the existence of flexible arrangements does not in itself ensure an equitable redistribution of care responsibilities, nor does it eliminate the penalties that women in particular face in the labour market.

These measures can often end up forcing women to adapt to rigid working arrangements, increasing the burden of reconciling work and family rather than transforming the institutional conditions that generate this additional stress. This criticism is backed up by Mills et al. (2011), who point out that, although work flexibility can reduce certain barriers to female participation in employment and sometimes foster a slight increase in fertility, its effectiveness depends largely on the type of employment, the related level of social security and its institutional underpinning.

Gauthier and Gietel-Basten (2024) and Fent et al. (2013) point out that flexibility can have ambivalent effects, by facilitating access to employment, but also worsening precarious working conditions unless it is accompanied by guarantees such as stability, social security and institutional co-responsibility. In this regard, the challenge for the region lies not only in expanding flexible work options, but also in ensuring that these policies are equitable, applicable in all sectors and designed from a gender perspective that does not entrench existing inequalities. The value of these measures, like parental leave, transcends their impact on fertility, as they can contribute significantly to women’s economic autonomy, to the well-being of families and to a fairer distribution of care responsibilities.

E. Family policies in the countries of the region

Several Latin American and Caribbean countries have public policies that, although not designed specifically to improve conditions for fertility, are important for supporting families, especially in contexts of socioeconomic vulnerability. As may be seen in table V.1, which gives a non-exhaustive selection of the initiatives in place by type of measure, there is considerable variation in the region in terms of the type, coverage and focus of family policies. Although some countries have begun to develop more comprehensive modalities —combining financial support, parental leave, care services and work reconciliation measures— policies often remain fragmented, focused on vulnerable populations and unrelated to any long-term strategy. This diversity reflects not only the different institutional capacities and policy priorities of governments, but also the tensions between welfare, social protection and gender equality approaches. In this regard, in addition to looking at whether policies exist, it is essential to consider whether they are coordinated with other policies and to analyse their potential in contexts of persistent inequalities.

Table V.1

Latin America: examples of family policies

Country

Laws and policies

Type of measure

Main features

Remarks

Argentina

Maternity leave

Parental leave

Guarantees income for pregnant women who have an employment contract, for the duration of their maternity leave.

Universal Child Allowance

Cash transfer

Monthly child allowance for families without formal employment or with low income.

This is not a policy to foster conditions for reproduction, but it improves child welfare in contexts of poverty.

Birth allowance

Cash transfer

Covers financial needs relating to the birth

of a child.

For children between 2 months and 2 years old.

Childcare rooms

in the workplace

Childcare

All establishments with 100 employees or more must provide childcare facilities for children between 45 days and 3 years of age.

Bolivia (Plurinational State of)

Maternity leave

Parental leave

Provides mothers with the opportunity to spend more time with their newborns and foster proper care during the postpartum period.

For women insured by social security.

Brazil

Maternity leave

Parental leave

120 days of absence from work, retaining employment and salary.

Maternity leave may be extended for a further 60 days if the employer is part of the corporate social responsibility programme Empresa Cidadã.

Bolsa Familia programme

Cash transfer

Provides monthly payments, with additional amounts for each child, fostering food security and school retention.

Focused on poverty reduction.

National Programme for the Restructuring and Acquisition of Equipment for the Early Childhood Education Public School Network (Proinfância)

Childcare

Ensures children’s access to day-care centres and schools and seeks to improve physical infrastructure within the early education network.

Intended to improve the supply and quality of education, in compliance with goal 1 of the country’s National Education Plan.

Chile

Postnatal parental leave and flexible working hours

Parental leave

Allows postnatal leave to be extended to 24 weeks, with the option of splitting it with the father.

The take-up by men is low.

Chile Crece Contigo

(“Chile Grows with You”)

Childcare

A comprehensive child protection system that includes biopsychosocial support during pregnancy and the early months after birth, free nurseries and kindergartens.

Entitlement to a nursery place

Childcare

Supports women’s participation in the labour sphere by allowing them to perform their work while their children are cared for and attended to.

Colombia

Shared parental leave

Parental leave

18 weeks of paid maternity leave. Paternity leave was extended from 8 days to 2 weeks.

Families in Action

Cash transfer

Provides cash transfers to poor households,

on the condition that children attend school and health check-ups.

Focused on poverty reduction.

Community Welfare Homes

Childcare

Early childhood care in adapted homes, managed by community mothers.

Limited coverage, aimed at vulnerable populations.

National Family Day

Flexible working arrangements

Benefit that gives employees a half-yearly paid day off to spend with their family.

As of July 2026, this benefit will cease to be a right for workers in the formal sector owing to the gradual reduction of working hours in the country.

Costa Rica

Law to regulate teleworking

Flexible working arrangements

Regulates teleworking as a formal modality with labour rights.

Limited application in the public sector and some private companies.

Ecuador

Maternity leave

Parental leave

Every working woman is entitled to a 12-week paid leave of absence.

Honduras

Maternity leave

Parental leave

Right to a 70-day leave of absence, 4 weeks before delivery and 6 weeks after delivery, without affecting the mother’s employment and labour rights.

Mexico

Estancias Infantiles

mothers’ support programme

Childcare

Childcare subsidy for working mothers

in the informal sectors or students.

Panama

Paternity leave

Parental leave

Affords paid paternity leave as of the child’s birth.

Maternity leave

Cash transfer

Payment during maternity leave for formal workers affiliated to the social security system.

Focused on formal employment; coverage is not universal.

Peru

Maternity leave

Parental leave

All pregnant workers are entitled to 98 calendar days of leave.

Maternity leave

Cash transfer

Cash payment during maternity leave, with immediate entitlement.

Mothers must be affiliated to Social Health Insurance (EsSalud).

Uruguay

Shared parental leave

Parental leave

Mothers have 14 weeks of paid leave and fathers have 10 days. The mother and father may distribute leave time between them in a flexible manner.

Integrated National Care System

Childcare

Childcare services for children from birth to age 3.

Source: Economic Commission for Latin America and the Caribbean [ECLAC]. Non-contributory Social Protection Programmes Database in Latin America and the Caribbean. https://dds.cepal.org/bpsnc/ptc; Regional Monitoring Platform of the Montevideo Consensus on Population and Development. https://consensomontevideo.cepal.org/en; Figueroa, N. and Vila, J. (2024). Programas de protección social no contributiva en América Latina y el Caribe: revisión metodológica de la estimación de tendencias de cobertura e inversión. Project Documents (LC/TS.2024/119). ECLAC; and Proinfância, https://www.gov.br/fnde/pt-br/acesso-a-informacao/acoes-e-programas/programas/proinfancia.

F. Effects of family policies on fertility

Several studies show that family policies can have positive effects on fertility, as is the case with expanded childcare services or increased parental leave, but the impact is usually modest and highly dependent on the social, institutional and regulatory context in which policies are implemented (Gauthier and Gietel-Basten, 2024; Bergsvik et al., 2021). In addition, Fent et al. (2013) show that social ties, cultural norms and peer influence mechanisms also affect reproductive decisions, amplifying or limiting the effects of policies depending on the social structure. In this regard, as Pardo, Pedetti and Soto (2025) argue, it is not only a matter of implementing measures aimed at encouraging fertility, but of bringing together a coherent set of policies that support the overall well-being of families with children, even if their direct effect on birth rates is acknowledged to be limited.

European experiences, especially those of France, Poland, Sweden and the United Kingdom, offer valuable lessons on how comprehensive, sustained and coherent policies can influence reproductive behaviour. However, these experiences should be interpreted and analysed critically, since the context of Latin America and the Caribbean may differ from those countries —in general, the region has higher levels of labour informality, sharper gender inequalities and lower levels of institutional coverage, among other factors—, which may make policies less effective or even counterproductive (Pardo, Pedetti and Soto, 2025).

In this connection, policies should be conceived not as isolated interventions, but as part of a social protection system with multiple objectives: to support families, reduce inequalities, ensure rights and enable people to fulfil their reproductive aspirations freely and in a setting of well-being. This implies developing comprehensive models to coordinate economic, labour, educational and cultural measures, in accordance with State commitments made by virtue of various international and regional instruments (Cabella and Nathan, 2018). These include the Convention on the Elimination of All Forms of Discrimination against Women (1979), which states that States shall ensure equality between men and women in all areas and shall adopt legislative and other measures to eliminate and prohibit all forms of discrimination against women, promoting their full participation in all aspects of life and supporting or ensuring, as the case may be, the necessary services for this purpose; the Programme of Action of the International Conference on Population and Development (1994), which represents a shift towards an approach focused on people’s well-being and autonomy; the Beijing Platform for Action (1995), which includes measures to harmonize work and family responsibilities among the steps that governments should take to ensure the full participation of women; the Montevideo Consensus on Population and Development (2013), a regional offshoot of the Programme of Action of the International Conference on Population and Development, which recognizes these rights as fundamental and promotes the inclusion of care in social protection systems in a context of gender equality across the diverse areas of people’s lives; and, finally, the 2030 Agenda for Sustainable Development (2015), whose Sustainable Development Goals explicitly link health, gender equality and decent work as pillars of inclusive and sustainable development.

Taking these instruments as a starting point, the priority should be comprehensive models that bring together sexual and reproductive health services, sexuality education, equitable parental leave, accessible childcare systems and family-friendly labour policies. Isolated policies are unlikely to bring about sustained structural change; the impacts depend largely on coherent coordination and the integration of policies within a broad regulatory framework, with adequate financing and sustained political will. Natalist approaches that reinforce gender stereotypes and inequalities must be avoided; instead, policymaking should adopt a rights-based approach that actively involves both men and women in childrearing.

It is also essential to leverage existing institutional capacities and to reformulate regulatory frameworks and financing modalities in line with the principles of equity and inclusion. Evaluation mechanisms should be aligned with a gender and human rights perspective, using both period and cohort indicators to assess policies from the point of view of sustainability and coverage. Regardless of the type of indicators used, updated information and knowledge on reproductive behaviours are essential for understanding not only the numerical trends, but also the structural and sociocultural underpinnings of low fertility. This includes factors such as gender inequalities, shifts in life aspirations, barriers to reconciling work and family, and material conditions that make it difficult to fulfil reproductive wishes. A comprehensive understanding of these matters is essential to build more effective policies that are focused on rights and adapted to the diverse realities of the population.

Finally, much stronger intersectoral coordination between population, gender, child, health, education and employment policies is needed to avoid fragmented measures and to devise a coherent and effective response to current and future reproductive challenges. Progress towards more inclusive and transformative policies can only be made if reproductive autonomy and gender equality are anchored at the heart of public agendas, in the recognition that the goal, rather than increasing fertility, is to ensure that everyone can choose how many children they wish to have and when.

VI. Conclusions

Latin America and the Caribbean is at an advanced stage of demographic transition, characterized by increasingly lower fertility rates and significant changes in reproductive patterns. Since the mid-twentieth century, the total fertility rate has fallen steadily across nearly all countries and territories of the region, to an average of 1.8 children per woman in Latin America and 1.5 children per woman in the Caribbean in 2024. This shift has occurred at a remarkable pace compared with other regions of the world and stems from the interplay of multiple factors, including rising education levels, urbanization, increased access to contraception and greater gender equality.

The steady decline in fertility has been interpreted from various theoretical perspectives. The first demographic transition has traditionally been explained through the lens of structural factors such as modernization, economic growth, urbanization, higher education levels and access to contraception. However, as fertility rates have continued to fall, even dropping below the replacement level, greater attention has been given to approaches associated with what has been termed the “second demographic transition”. Key features of this transition include greater gender equality, shifts in cultural values, increased individual autonomy, postponement of family formation, growing rates of cohabitation and evolving patterns of marriage and childbearing.

The different perspectives may be seen as complementary, rather than mutually exclusive. While structural factors help to explain the initial phase of the demographic transition, approaches focusing on gender, “post-materialist” values and institutional barriers provide essential tools for analysing current trends. While not all countries of the region are fully experiencing a second demographic transition, many of the trends observed —such as postponement of childbearing, increasing cohabitation and fertility rates below replacement level— reflect processes that, though shaped by this broader framework, unfold in specific contexts marked by persistent inequalities and limited social protection systems.

A central aspect of this shift has been the postponement of childbearing, which has delayed the age at first birth and lowered fertility rates among younger women. This phenomenon has significantly impacted the total fertility rate, making it necessary to incorporate complementary indicators such as mean age at childbearing, cohort fertility and tempo-adjusted rates to more accurately interpret fertility trends. At the same time, the adolescent fertility rate has declined steadily, although it remains high relative to other regions. This reveals the coexistence of two parallel dynamics: fertility postponement among young women with higher levels of education and greater access to opportunities, and persistent early fertility among adolescents in contexts marked by inequality, structural barriers and limited access to sexual and reproductive health services. This dual reality highlights the social inequalities that continue to shape reproductive patterns across the region.

Countries such as Chile, Costa Rica and Uruguay are approaching lowest-low fertility rates, while fertility remains at the intermediate level in Guatemala, Haiti and the Plurinational State of Bolivia. However, disaggregating fertility data by education level and socioeconomic quintile reveals that women in higher socioeconomic quintiles tend to reflect low or lowest-low fertility rates even in countries with overall intermediate rates. At the same time, data from countries with available information point to a widening gap in reproductive rights: women in lower socioeconomic quintiles tend to have more children than their stated reproductive ideals, while those with higher levels of education and income often have fewer.

These differences reflect not only structural inequalities in access to sexual and reproductive health services, education, formal employment and work-life balance policies, but also the coexistence of diverse cultural, social and normative patterns that influence reproductive trends. Adolescents and women in vulnerable situations or residing in rural areas continue to face barriers to autonomously exercising their reproductive rights. Even in urban areas —especially among lower- and middle-income groups— major obstacles persist, including job insecurity, a lack of support networks, limited availability of public care services and labour market demands that hinder work-life balance. These challenges are compounded by prevailing cultural and social norms that impose idealized models of motherhood and fatherhood, creating tensions and constraints in reproductive decision-making, even among individuals with higher levels of education and income. Understanding this demographic, territorial, cultural and socioeconomic diversity is key to designing tailored policy responses that address the structural factors shaping reproductive behaviour in the region.

In light of these challenges, public policies should adapt to the new demographic context. It is essential to ensure that individuals can exercise their right to freely and responsibly determine how many children they wish to have, in alignment with their educational, professional and personal aspirations. Achieving this requires comprehensive policy frameworks that advance gender equality, expand the availability and quality of care services, eliminate workplace barriers that penalize mothers and ensure universal coverage of sexual and reproductive health services.

Lastly, accurate monitoring of fertility trends requires robust and comparable information systems. High-quality administrative records, surveys and censuses are critical to accurately estimate demographic indicators, identify persistent inequalities and guide the design of effective public policies. Likewise, strengthening of vital statistics systems, together with the use of methodological tools for adjustment, estimation and projection, not only enables the analysis of current trends but also enhances the capacity to anticipate future ones. In a context of persistently low fertility levels, population projections are an increasingly fundamental tool for sustainable development planning in Latin America and the Caribbean.

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Table of Contents

Maintitle

Copyright

Foreword

Introduction

I. The fall in fertility in the context of the first demographic transition

II. Post-transitional demographic regimes in the countries of the region

III. The effect of postponement on fertility rates in the region

IV. Socioeconomic differentials in fertility and their proximate determinants

V. Public programmes and policies in a low-fertility context

VI. Conclusions

Bibliography