Keywords
Mortality, fertility decline, demographic dividend
Mortality, fertility decline, demographic dividend
Rapid reductions in fertility and mortality during the last half-century have resulted in dramatic changes to the population age structures of many countries, which economists have argued have been demonstrably conducive to economic development1. Countries with a high proportion of their population in working ages are better able to use their resources for economic development due to reduced expenditures related to caring for child and elderly dependents. The efficient utilization of the economic opportunities that result in part from a favorable demographic transition is termed “the demographic dividend”.
The association between fertility and mortality declines and the demographic transition has been extensively studied and well documented, but their relationship with economic development has not been systematically investigated in the health literature2. A comprehensive demonstration of its health and economic benefits strengthens the advocacy for fertility decline through programs that directly influence fertility levels, such as meeting women’s need for family planning.
Such an investigation links several sustainable development goals (SDGs). Fertility decline results in a smaller total population, which alleviates the burden on earth’s life-support system imposed by a global population set to rise to 9 billion by 20503. Women empowered to adapt voluntary measures to reduce fertility will benefit themselves, their children, and the local and global economy and environment4.
Over two centuries ago, Malthus argued that unconstrained population growth would lead to catastrophic consequences because the amount of many production factors, such as land, is fixed5. Solow subsequently proposed that even reproducible factors would be swamped by rapid population growth6. The variation in population growth rates is an important factor in explaining differences in long-term economic performance across countries. The implications of the theories proposed by Malthus and Solow, as well as others, are pessimistic for countries with sustained high fertility rates. According to this framework, fertility decline results in a smaller total population, which in turn increases the ratio of fixed and reproducible factors to labor.
Additionally, lower fertility levels are also associated with higher investments in human capital, another important production factor7,8. Moreover, lower fertility means that women’s time spent on bearing and caring for children declines and may translate into a higher female labor participation rate, which independently contributes to the economy9.
At the aggregate level, fertility also significantly impacts the population age structure. Lower fertility implies fewer children and a lower child dependency ratio, defined as the ratio of children (i.e. aged 0–14 years) to the working age population (i.e. aged 15–64 years). Holding other factors constant, such as the labor participation rate, a larger proportion of working age population can lead to greater output per capita.
Empirical studies have identified a strong correlation between a favorable population age structure and rapid economic growth10,11. It has been estimated that as much as one-third of the economic growth in the “East Asia Miracles” economies of Hong Kong, Singapore, South Korea, and Taiwan, from the early 1960s to 1990s, was derived from their rapid fertility transitions1. Figure 1 compares the population pyramids of Nigeria and South Korea. In 1960 their population age structures were similar, with the dependency ratio (population aged 0–14 and 65+ years divided by the population aged 15–64 years) being 80 and 87 in Nigeria and South Korea, respectively. According the World Bank, the GDP per capita (constant 2011 US$) was 50% higher in Nigeria than South Korea in 1960. Fifty-five years later, the dependency ratio had decreased to 37 in South Korea while it increased to 88 in Nigeria. During the same period, the GDP per capita rose to $24,871 in South Korea, a 26-fold increase. The increase was less than 2-fold in Nigeria in constant dollars.
Figure 2 illustrates the relationship between economic growth and the ratio of children to working age population in 120 low- and middle-income countries (LMICs) in Asia, Latin America and the Caribbean (LAC), Northern Africa, and sub-Sahara Africa (SSA). The vertical axis is the change in GDP per capita during the period 1990 to 2015. GDP is based on purchasing power parity (PPP) and is measured in constant 2011 international dollars. The horizontal axis is the child dependency ratio in 2015. We use 1990 as the starting year, instead of 1960 that is used in subsequent sections, since PPP-converted GDP data only first became available in the World Bank database in 1990. High-income countries are excluded since most of them had completed their demographic transitions long before 1990. The inverse relationship between economic growth and the ratio of youth to working age population during the past two decades is consistent with findings from previous studies12. This helps justify our use of the child dependency ratio as the indicator with which to investigate the relationship between mortality, fertility, and economic development. During the 25-year period considered, the increase in GDP per capita was greater in those countries that had achieved a lower child dependency ratio by 2015. A linear regression analysis of the change in GDP per capita against the 2015 child dependency ratio shows a satisfactory goodness of fit with R2 = 0.44. The slope of the linear fitted line is -109 (95% CI: -134,-85), In other words, each one- unit change in 2015 child dependency ratio is associated with 109 fewer international dollars in 2015 GDP per capita.
We obtained data on the fertility, mortality, and population age structure for 201 countries during the decades 1960 to 2015 from World Population Prospects (WPP), the 2017 Revision. This is the 25th round of official United Nations (UN) population estimates, published in June 2017 by the Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat13. The economic data were obtained from the International Comparison Program Database of the World Bank.
Dependency ratios are used as indicators of the population age structure. Similar to the child dependency ratio defined above, the aged dependency ratio is the ratio of the number of elders (65 years and above) to the working age population. The total dependency ratio equals the sum of child and aged dependency ratios. As a commonly-used fertility measure, total fertility rate (TFR) is the number of children a woman would have over her lifetime if she were to experience the observed period age-specific fertility rates.
CCM is a demographic projection method used by the UN to generate WPP estimates. It employs a transition matrix to predict population by age from one period to the next. Following WPP 2017, our projections were made for five-year intervals. The basic equation for the CCM is
where Pt is a column vector whose elements are the age-specific population at calendar time t; Mt,t+5 is a transition matrix constructed from the age-specific fertility and mortality.
All 201 countries included in the WPP 2017 database are used in this study. Among them, 187 countries have data on GDP per capita (PPP, constant 2011 international $) in the World Bank’s International Comparison Program Database. The majority of the figures and tables which follow below are based on countries in 4 regions (Asia, LAC, Northern Africa, and SSA) that are relevant to this study. Population projections for the following three scenarios were made using Stata 14: what would the 2015 dependency ratio be if, during the period from 1960 to 2015, there had been (1) neither a fertility nor mortality reduction; (2) no fertility reduction; (3) no mortality reduction? Based on these estimates we further assessed what the GDP per capita would be in 2015 under these three scenarios.
Globally, child and total dependency ratios declined significantly from 1960 to 2015, with large country-level and regional variations. The declines in SSA are the smallest among the five regions - the median change in both child and total dependency ratios is close to zero. On the other hand, Asia and LAC have experienced dramatic changes in both fertility levels and dependency ratios, with median changes in the range of 30 to 40 units.
The decompositions of the contributions from fertility and mortality declines to the change in dependency ratios were conducted at both regional and country levels. Table 1 and Table 2 show the results from country-level and regional-decomposition, respectively. Mortality decline was considered in the estimations since it is an important determinant of population age structure. However, our discussion is mainly on fertility for two reasons. First, as illustrated in Table 1 and Table 2, the effect of mortality decline is smaller than that of fertility change. Second, no government, including those facing a tremendous challenge of population aging, have ever proposed slowing mortality decline to make the population age structure more conducive to economic development14.
The contribution of fertility decline to the change in the dependency ratio was smallest in SSA than in any other region. The 2015 child dependency ratio was 80 in SSA and would have been 96 had there been no fertility decline from 1960 to 2015. In other words, every 100 working age population in SSA would have to support 16 more children without the fertility declines that transpired in SSA countries. In Asia, the observed 2015 child dependency ratio was 36 and would have been 90 had there been no fertility decline. The fertility transition in the LAC region similarly reduced the child dependency ratio to 38, which would have been 92 had there been no fertility decline. The results are 52 vs. 102 in Northern Africa, meaning the fertility almost halved the burden of children on working age population.
These results are illustrated in Figure 3. We simulated how much higher the dependency ratios would be if mortality and/or fertility had been constant in the decades from 1960 to 2015. The percentage change in the child dependency ratio was positive and large in the constant fertility scenario in Asia and the LAC regions. The results underscore how notably fertility declines have reduced the child dependency ratio during the period 1960–2015. On the other hand, the percentage change in the child dependency ratio is negative for the constant mortality scenario, but the size of the change is marginal. The combined impact of mortality and fertility changes is positive for all of these five regions, but their size is substantially greater in Asia and LAC than in SSA.
S1 = scenario 1, constant mortality and fertility; S2 = scenario 2, constant fertility; S3 = scenario 3, constant mortality.
Figure 4 shows a clear positive relationship between fertility levels in 1960 and the contribution of 1960–2015 fertility declines to 2015 total dependency ratios. This implies that previously high-fertility countries have catching up and they have a large potential to alter dependency ratio through fertility decline.
From the analyses conducted here, with the exception of most SSA and several Asian countries, a higher TFR in 1960 is associated with a larger contribution by fertility decline to the change in the child dependency ratio. The majority of high-fertility Asian countries have significantly reduced their TFR, resulting in smaller dependency ratios.
There are several direct and indirect economic implications resulting from the changes in population age structure and consequences for the dependency ratio. By definition, GDP per capita can be broken down into GDP per worker and the proportion of working age population in the total population. By definition GDP per capita can be expressed as,
where Yit is the gross domestic product (GDP) in country i in year t. yit is GDP per capita, Pit is the total population, and Wit is the number of workers. zit is the product per worker and wit the share of workers in the country at time t. In the present study, the number and proportion of workers are proxied by the working age population. Consequently, an increase in GDP per capita may be attributable to the change in either productivity per worker or the proportion of workers in the population.
This approach is a simplification of the actual change in GDP per capita, which can be affected by a variety of socio-economic, geographic, institutional and international factors15,16. The approach has been used in previous studies17. An increased total dependency ratio means a reduced proportion of working age population, which, assuming a fixed worker productivity, indicates a lower GDP per capita.
We simulated the GDP per capita that would have occurred had one factor not changed assuming that worker productivity did not change from 1960 to 2015. The gap between the actual and hypothetical values can be interpreted as the impact of the change in population age structure on GDP per capita. It is easy to show that,
where denotes the GDP per capita in country i in year t had there been no fertility decline; denotes the observed GDP per capita, i.e. from the World Bank database; and denote the total dependency ratio under those two scenarios.
As seen in the last three columns in Table 1 and Table 2, GDP would be much lower in most of the countries if the fertility decline between 1960 and 2015 had not occurred. Global GDP would decrease from the actual $106,422 billion to $87,406 billion without the fertility decline. The regional reductions are $12,390 billion in Asia, $1,706 billion in LAC, $484 billion in Northern Africa, and $321 billion in SSA. The estimated contributions are comparable to those of other studies. Bloom and Williamson (1998) and Bloom and Finlay (2009) suggested that the demographic transition accounted for between one fourth and two fifths of the “economic miracle” in East Asian Tigers’ economies1,17. A study projected that the demographic dividend could increase GDP per capita by about 11–32% in selected SSA countries over 2010–2040 under the UN’s low-fertility projection18. Those estimates vary, mainly because they cover different periods in time.
The estimation from this approach disregards the correlation between worker productivity and population age structure. Some studies have found that an increasing proportion of working age population is associated with improved worker productivity. Several mechanisms have been proposed to explain the association. As discussed above, an increased proportion of working age population, mostly brought about by rapid fertility decline, can be associated with an increased female labor participation rate9. Declining fertility also encourages greater savings within the working age population for retirement14. These behavioral changes promote the accumulation of financial and human capital, which will result in improved productivity per worker. Due to these associations between the proportions of working age population and worker productivity, the estimations of the impact of population age structure on GDP per capita presented here are conservative.
Although this paper has used widely recognized population data from the UN and World Bank and applied well-established demographic projection methods, it nevertheless is subject to limitations. Particularly, we assessed the changes in fertility, mortality, and dependency ratios for the decades from 1960 to 2015, a somewhat extended period of time during which many countries may have experienced short-term demographic and socioeconomic fluctuations. Our analysis cannot account for the impact of short-term variations on dependency ratios. As discussed above, the assumed independence of population size and age structure and worker productivity may be an oversimplification.
This study fills an important gap in the current literature on population welfare and reproductive and family health in LMICs. In PubMed we located about 500 articles published in English from Jan 1, 1990 to June 30, 2017 that included terms “fertility decline” or “mortality decline” in the titles or abstracts. But only 7 of them had “demographic dividend” in the titles or abstracts. Admittedly, many studies on the demographic dividend are published in the economic literature and thus may or may not be included in the PubMed database. However, our search results indicate that the demographic dividend perspective, which is appealing to policy makers, has not penetrated the health literature, and has not been fully utilized as evidence of the importance of improved reproductive, maternal and child health.
This study is the first to retrospectively assess the contribution of fertility and mortality declines to the change in national dependency ratios over the past five decades. It has also estimated the economic consequences of these demographic changes. Contrasting SSA to Asian and LAC countries sheds new light on the historical relationship between fertility, mortality and economic development. A favorable dependency ratio has enabled many Asian and LAC countries to realize the demographic dividend and to transform their predominantly rural agrarian economies into urban industrialized ones. During this period of development, many millions of people worldwide have been lifted out of poverty and their health substantially improved.
Assessing the contribution of fertility decline to the change in population age structure and GDP per capita provides a strong argument for expanding reproductive, maternal and child health interventions. Our study estimated the contribution of fertility declines, by far the more dominant factor, to the change in dependency ratios in 201 countries over the past five decades. Lower dependency ratios for countries as a whole as well as for individual households offer the opportunity to reallocate scarce resources toward better education, health care and nutrition. Improved health benefits for youth also confer stronger physical and cognitive performance with social and economic consequences that can disrupt poverty cycles.
The past half-century has been characterized by rapid demographic transitions and historically unprecedented economic growth in most parts of the world, with the exception of the SSA region. The population age structures in Asia and LAC experienced dramatic changes during the period 1960–2015. At the same time, countries in these regions were transformed from mostly rural agrarian economies with high fertility and mortality to largely urban industrialized ones with low fertility and mortality. In contrast, most SSA countries have lagged in their demographic transitions and economic development.
Based on a decomposition analysis of 201 countries, we found that fertility decline from 1960 to 2015 played a large role in changing the population age structure and lowering dependency ratios. Over this period, fertility decline contributed greatly to the reduction of the child dependency ratio in Asia and LAC while in contrast, its contribution in SSA was minor. The main reason is that fertility declined in SSA countries only marginally. The TFR in SSA fell from 6.67 in 1960 to 5.10 in 2015. During the same period, the TFR in LAC decreased from 5.89 to 2.14, and in Asia the change was from 5.81 to 2.20. The difference in the demographic transitions among these regions is consistent with the variation in their economic development.
Countries with slow fertility declines will need to accelerate the transitions in order to achieve a dependency ratio favorable for realizing a demographic dividend. Satisfying unmet need for family planning and providing full and voluntary access to a range of contraceptive methods have proven to be effective measures to reduce fertility. The implication of our study for policymakers is that expanding and intensifying the provision of effective reproductive, maternal, and child health interventions, particularly contraceptive access and nutrition enrichment, can accelerate ongoing fertility and mortality declines that contribute to population health as well as economic productivity and poverty alleviation. The induced benefits cover all three layers of the new paradigm of sustainable development - earth's life-support system, society, and economy. To ensure reaching the demographic dividends, governments of SSA countries should also encourage investments in human capital and ensure adequate employment, along with increased gender equity and nutrition19.
All data used in the study are freely available online (no registration needed). Below are links to access the datasets:
The 2017 Revision of World Population Prospects: https://esa.un.org/unpd/wpp/
International Comparison Program Database of the World Bank: http://www.worldbank.org/en/programs/icp
Bill and Melinda Gates Foundation [OPP117_01].
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Competing Interests: No competing interests were disclosed.
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Competing Interests: No competing interests were disclosed.
Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
Partly
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Partly
References
1. May J, Turbat V: THE DEMOGRAPHIC DIVIDEND IN SUB-SAHARAN AFRICA: TWO ISSUES THAT NEED MORE ATTENTION. Journal of Demographic Economics. 2017; 83 (01): 77-84 Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Demography (JM) and economy (VT)
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