3 Demographics 3 Demographics

Contact at AFI team is Jakkie Cilliers
This entry was last updated on 24 August 2022.

In this entry, we describe how the demographic dividend affects development outcomes. We then discuss the structure of the Demographic scenario and its potential impact on key development outcomes.

Summary

  • The demographic dividend can be presented in several ways, all rooted in the ratio of working-age persons to dependants. 
  • An increasing ratio of the working-age population to dependants boosts economic growth as more working-age persons contribute to economic activity. However, Africa is experiencing a slow demographic transition driven to a large extent by its large youthful population and low levels of urbanisation.
  • Lower child mortality rates, higher incomes, urbanisation, education and the availability of contraception all reduce fertility rates
  • Europe and Japan are experiencing slow economic growth partly because of their large elderly population. Sub-Saharan Africa is now the only region in the world where a high child dependency burden contributes to slow growth in income levels. 
  • Lower fertility rates are generally associated with higher levels of income, education and urbanisation.
  • Our Demographic scenario shows that a rapid uptake of contraceptive use and lower child and maternal mortality rates can have a large impact on fertility and the potential to improve Africa’s economic outlook, although the impact of COVID-19 means that fewer resources will be dedicated to family planning and reproductive health services.
  • Sub-Saharan Africa needs to reduce  its high population dependency structure to benefit from the attendant economic, social and political effects.

All charts for Theme 3

Introduction

Until around the middle of the 17th century, the size of a country’s labour force and the suitability of the land for agriculture were the main engines of growth, even if they seldom made a difference to citizens’ average incomes. However, the technological breakthroughs of the 18th and 19th centuries transformed the economic structures of the previous centuries by shifting some elements of production from manual labour to machines.

The industrial revolution saw productivity soar in Europe and North America, although it generally remained stagnant in the rest of the world. This was the start of the ‘great divide’ that saw Europe, and eventually North America, come to dominate the world and overtake countries such as China, previously one of the largest economies. This is a global order that has held until very recently.[1M Roser, 2019, Economic Growth]

With industrialisation, population structures changed. People moved to cities to work in factories and birth rates declined, thereby increasing the number of people of working age relative to dependants. The industrial revolution, and the associated population effects, largely bypassed Africa for many reasons related to its geography, including the continent’s high disease burden, and, more recently, the impact of slavery and colonialism.

Population growth and age structure are critical components of economic growth, particularly at lower levels of development. Once population growth starts to drop below replacement levels, economies struggle to grow. However, steady improvements in income per capita are possible if countries compensate for their smaller labour forces by investing more in the quality of their human endowment, capital and technology.

Except for a few countries in North Africa, the Seychelles, Mauritius and South Africa, Africa is likely to realise its demographic dividend only after 2050. In much of the continent, countries’ youthful populations are a drag on improvements in income, service delivery and education – not to mention increasing carbon emissions and the effect on global warming associated with a larger population.

Organisations such as the African Union (AU) like to emphasise the benefits of Africa’s youthful population. The AU Commission has spent considerable resources reviewing progress with the 2006 African Youth Charter [2African Union Commission, 2006, African Youth Charter] and its 2009–2018 Plan of Action [3African Union, 2011, African Youth Decade 2009-2018 Plan of Action] to put forward a roadmap [4African Union Commission, 2017, AU Roadmap on harnessing the demographic dividend through investment in youth, Addis Ababa: African Union.] aimed at unlocking the potential of the continent’s youth as part of its focus on investment in this demographic. The basic premise was that Africa’s youthful population would ensure fast economic growth and that, as a general notion, rapid population growth was positive for development. However, the Charter, Plan of Action and roadmap all skirt the need for a more rigorous analysis of the demographic dividend. In fact, Africa’s very high fertility rates are a severe constraint on development across much of the continent. Until fertility rates are significantly reduced, even the most spectacular economic growth rates will not be sufficient to reduce poverty and improve livelihoods substantially. Although trends are heading in the right direction, much more urgent action is required to speed up the demographic transition in almost all of Africa’s low- and lower middle-income countries.

At current rates of fertility, there are so many children that require schooling, healthcare and education that it is impossible to improve the human capital of those already in the system. The result perpetuates poverty.

There are several ways to conceptualise this challenge, [5These depart from the UNPD’s definitions in that a favourable ‘demographic window’ is described to open when the proportion of children (0–14 years) is less than 30% and the proportion of seniors (+64 years) is less than 15%. A median age of 25.6–40 years is used. R Cincotta, 2017, Opening the Demographic Window: Age Structure in Sub-Saharan Africa.] with all of them speaking to the ratio of working-age persons to dependants:

  • A fertility rate of between 2.1 and 2.8 children per female in her reproductive years eventually ensures an optimal relationship between the potential labour force and dependants. If the ratio drops below 2.1 children per woman, the population starts to shrink. This reduces the potential labour force and eventually presents a large elderly population, as is the case in Japan, which is expensive to support. If the ratio reaches above 2.8 children per woman, the economy has to expand very rapidly to account for the additional people to feed, educate and keep healthy. In 2019, Niger had a total fertility rate of almost seven children to every fertile woman and is one of 46 countries in Africa that exceeds the boundary.
  • The median age divides a population into two equal groups. A country where the median age is above 25.5 years but below 41 years typically has a large enough working-age population to look after its dependants, children and the elderly. In 2019, the only African countries with a median age above 25.5 years were Mauritius, Seychelles, Tunisia, Morocco, Libya, Algeria and South Africa.
  • A third measure is the ratio of working-age people to dependants. Intuitively, if there are more working-age people producing an income, there is more to be shared with the children and the elderly who depend on them. When the ratio gets to 1.7 and above, countries generally enter their demographic dividend.

Chart 1 and 2 presents the population pyramids for Denmark and Bolivia in 2019. With a ratio of 1.8 working age persons to every dependant Denmark will exit its demographic sweet spot in 2025 as its population ages whilst Bolivia, with a ratio of 1.6 working age persons to every dependant, will enter its potential demographic sweet spot in 2023 as the median age of its young population increases.

Having a large working-age population alone is, of course, insufficient. Better productivity requires potential workers to be well fed, literate and sufficiently educated and to have a job. Also, measures of dependency based on age alone can be misleading since ‘cultural questions such as an acceptable age of retirement, delaying work for education, and the role of women in the labor force vary greatly by country and across time. Average teenagers in rural Sudan, who end their education after seven years to work on the family farm, contribute much earlier and differently over the life course than average urban South Koreans who spend time consuming education for another decade into their mid-twenties.’[6H Ritchi and M Roser, 2019, Age structure]

For labour to contribute to growth requires a facilitating job environment such as the opportunity to open a business. If that does not exist, such as in most North African countries, where various barriers inhibit economic opportunity, persons of working age have to eke out survival in the informal, and often illicit, sector.

According to Richard Cincotta, about 85% of countries that pass through the demographic window attain the upper middle levels only after entering the demographic window, and virtually none (with the exception of North Korea, a very exceptional state) remain in the lowest category. In addition, countries with a population under five million and resource-rich states (and some high-remittance earners) often do better than their age structures might indicate.

To improve incomes, developing countries have to work hard to reduce fertility rates; literally no country in the world has modernised socially and economically while fertility rates have remained high. We see 45 million Africans being born every year, a number that will increase to 55 million annually by 2043 and, by 2063, have marginally reduced to 52 million per year. By 2043, Africa’s total population will therefore have increased from 1.3 billion in 2019 to 2.2 billion. It is currently on course to reach 3 billion by 2063.

The impact of the well-known youthful structure of the African population, with a median age just shy of 20 years (i.e. half the African population is younger than 20), is a population pyramid that has a very broad base and quickly narrows with each age group. This is well illustrated by comparing the 2019 population pyramid of Niger (Chart 3) with that of Mauritius (Chart 4), the African country with the highest median age.

It is no coincidence that the levels of education attained are so much higher in Mauritius than in Niger. With fewer schools to build and teachers to train every year, Mauritius is able to spend its resources on better education of the children already in the schooling system, making sure that the quality of education improves with each passing year. In contrast, the large cohort of children below 15 years of age in Niger means that the country is unable to educate, feed and provide opportunities for them all. The country will remain poor unless, among other things, it manages to reduce the rate at which its population is growing.

The importance of a high (or at least increasing) ratio of working-age people (15–64 years) to dependants for contributing to economic growth at low- and even middle-income levels of development has been shown by a large body of research. According to the World Bank, in East Asia one-third of the increase in economic growth during its economic miracle can be attributed to a growing labour force. A substantial portion of the remainder is achieved by the determined pursuit of export-oriented policies that provide productive employment for its rapidly expanding population.[7D Canning, R Sangeeta and YS Abdo (eds), 2015, Africa’s Demographic Transition: Dividend or Disaster? Washington DC: World Bank, pp. 6–7]

How well countries capitalise on the demographic dividend window has a lot to do with appropriate policy and the strength of institutions. Literacy and quality basic education are obvious additional requirements. The effects are observed first in maternal and child health (largely household managed), then in education (needing both parental and government investment), then in the economy (needing government policy) and then in governance (needing leadership). Each phase implies more determined government effort as a country progresses along this chain.[8E-mail communication with Richard Cincotta, 19 May 2021.]

Comparison of demographic dividends

The ratio of working-age people to dependants in Africa started to improve from 1.1 in the late 1980s to the current ratio of 1.3. In other words, whereas there were 11 people of working age supporting 10 dependants in 1987, there are 13 people of working age for every 10 dependants today. When the continent gets to a ratio of 1.7, forecast to be by around 2051, it will enter a window of particularly rapid income growth through the contribution of labour to economic growth (as opposed to capital and technology). This is forecast to last for about two decades in the Current Path forecast, with a peak of around two persons of working age to every dependant shortly after 2070. The ratio is then expected to decline, and, if labour is still as important as it is today, rates of economic growth will decline unless capital and technology can compensate for the decline in the relative size of the labour pool.

The ratio of working-age persons to dependants has markedly contributed to the improvements in prosperity in Japan, China and the so-called Asian Tigers since the 1960s. China and the Asian Tigers peaked at an extraordinarily high ratio of 2.8 in 2010 and 2013, respectively. The benefit of a continually growing pool of working-age persons is also seen in the economies of the USA and Nordic countries, where the ratio did not peak as swiftly and as high as the levels of China and the Asian Tigers but increased gradually and then remained in modest positive territory (i.e. above 1.7) for an extended period. This has led to steady economic growth and improvements in productivity, which eventually earned these countries high-income status.

Currently, 56% of Africa’s population fall in the standard working-age bracket (15–64 years of age), translating to a ratio of 1.3 working-age persons for every dependant. The portion in sub-Saharan Africa, excluding South Africa, is at 54.5%. Compare that with the ratio in the rest of the world, where 67% of the total population is of working age, equating to two persons of working age to every one dependant. The 0.7 difference between the ratios is significant given the large numbers involved.

The impact of the demographic dividend

Economic growth is determined by the contributions from labour, capital and technology. At low levels of development, labour contributes most to economic growth; at high levels of development, technology is the biggest contributor. Therefore, especially in developing regions, the larger the labour pool relative to dependants (children and the elderly), the faster the economy can grow.[9This is also known as the first dividend as opposed to the so-called second and third dividends, which are the result of savings and investments and improvements in productivity, respectively.]

The rapidly increasing size of the labour force relative to dependants in Japan, China and the Asian Tiger countries was key to their rapid economic growth and development.[10The dependency ratio is the inverse of the demographic dividend. If the labour force increases in size relative to dependants, it causes the dependency ratio to decrease (or the demographic dividend to increase), in which case economic growth is very likely to follow. So, a dependency ratio of 1:1 means that every worker has to support one dependant. In a country such as South Korea, which had a dependency ratio of 0.39 in 2018, each person of working age only had to support one-third of a dependant. Japan bottomed out at a dependency ratio of 0.43 in 1992. China and the Asian Tigers bottomed out at 0.36 in 2010 and 2013, respectively. All these countries experienced their periods of most rapid economic growth in the years during which their dependency ratios were declining.] Today, several decades later, they all face the opposite problem: a slowdown in growth because a shrinking workforce (as a portion of the total population) has to support a growing elderly population.

Fast growth in the working-age population does not automatically translate to rapid economic growth as facilitators such as food sufficiency, literacy and basic education, an export orientation and a governing elite committed to growth also need to be present. Yet it still has some interesting benefits. For example, smaller families mean that fewer additional schools are needed, and the ratio of teachers to pupils can improve more readily. As a result, parents and the state can invest more resources in those children. Eventually, governments will need to provide fewer additional houses and water and electricity connections and can invest in higher technology, research and other measures necessary to maintain improvements in productivity, even as the size of the working-age population starts to decline later and the elderly population starts to displace children as dependants.

The size of the labour force does not, of course, exactly correlate with the number of people in the working-age bracket (15–64 years) as many would still be getting an education or would not have a job. But the essential relationship holds even after accounting for these differences. However, the reality is that for many Africans, having a ‘job’ is actually all about surviving in the large informal sector where there is no job security, benefits or, indeed, decent work.

Africa’s slow demographic transition

Globally, the size of the working-age population relative to dependants peaked by around 2010. The world will be able to emerge from this structural period of slower growth only through advances in technology, including capitalising on the digital economy and the fourth industrial revolution – factors explored further in the Leapfrogging theme.

Most of Africa still finds itself in the early stages of the demographic transition. The shift from high mortality and fertility rates to low mortality and fertility rates has started, but it is progressing gradually and slower than it historically did in other regions.

Africa is expected to reach a ratio of 1.7 between working-age people and dependants by 2051. By 2063, the ratio is forecast to be 1.9. For the next three decades, Africa’s dependent youth population will therefore remain a drag on economic growth, although to a lesser extent with every passing year.

Generally, countries (and regions) that have been unable to rapidly progress through the demographic transition and get to the demographic dividend ratio of 1.7 are characterised by severe poverty and large disease burdens (as governments do not have the resources to combat illnesses) as well as high fertility and mortality rates that structurally constrain their ability to reduce poverty and improve livelihoods. The rapid increase in the number of children offsets the increases in income from economic growth and prevents the accumulation of savings, resulting in low capitalisation in the economy.

There are many reasons for Africa’s comparably slow demographic and urban transition:

  • Historically, low population density – a function of Africa’s high disease burden – translated to low levels of urbanisation and lower rates of income growth. Some of these aspects are explored in the theme on health.
  • In more recent generations, the continent has also not been able to raise the quality and attainment of education, roll out the use of modern contraceptives quickly enough or transition to economies where child labour is no longer required.[11In the least developed countries, one in four children (aged 5–17) is estimated to be involved in child labour. International Labour Organization, 2015; International Labour Organization, 2018, Women and Men in the Informal Economy: A Statistical Picture, Geneva: International Labour Office; World Report on Child Labour 2015: Paving the Way to Decent Work for Young People, Geneva: International Labour Office.]
  • Africa has also not been able to produce sufficient job opportunities to provide meaningful work for its growing population.

Most African countries are experiencing slow income growth because their populations are very young, although the picture is heterogeneous:

  • In a country such as Tunisia, fertility rates are approaching the level at which population size first stagnates and then starts to decline unless there is a significant young net inward migration or changes in fertility rates.[12A rate of 2.1 children per woman is generally accepted as the replacement fertility rate. Without inward migration, populations start to decline below this rate.]
  • Many other countries, such as Mozambique, appear to be stalling in their transition by maintaining very high levels of fertility.
  • A third group (including Ethiopia) is achieving a rapid reduction in previously very high fertility rates. Because of investments in basic healthcare and family planning, Ethiopia will achieve the 1.7 demographic dividend ratio a decade before other low-income countries in Africa.[13See: P Eloundou‐Enyegue, S Giroux and M Tenikue, 2017, African Transitions and Fertility Inequality: A Demographic Kuznets Hypothesis. Population and Development Review, 43(S1), pp. 59–83.]

Urbanisation in Africa

Africa’s youthful population and low levels of urbanisation stand out against a global backdrop of aging populations. Africa is the only region globally where the size of the working-age population as a portion of the total population is still increasing, and it is the least urban continent, although South Asia is more rural. Both are changing but later than other regions.

Historically, urbanisation is associated with growth and development. An analysis by the McKinsey Global Institute (2010) found that the shift from rural to urban employment could account for 20–50% of productivity growth in Africa.[14C Roxburgh et al., 2010, Lions on the Move: The Progress and Potential of African Economies, Brussels: McKinsey Global Institute, p 19.] Yet, by historical standards, urbanisation is lagging in Africa. At the time of independence in the early 1960s, fewer than one-fifth of Africans could likely be classified as urban. As shown in Chart 6, that number had increased to around 27% by 1980, to 35% by 2000, and should, by around 2039, reach 50%. In contrast, the rest of the world crossed the halfway mark shortly after the turn of the century. Africa is likely to get to the two-thirds mark only by around 2070, compared with 2042 for the rest of the world. The impact of climate change may, of course, accelerate this process.

East Africa is the most rural part of the continent and will likely remain so with levels of urbanisation currently almost 30% lower than in North Africa, the most urban region. West Africa is experiencing the most rapid rates of urbanisation (average rates are currently roughly on par with Central Africa) and will, after the middle of this century, likely approach rates of urbanisation seen in North or Southern Africa. Currently, Gabon, Libya, Djibouti, Equatorial Guinea, Algeria and São Tomé and Príncipe are the most urbanised countries. South Sudan, Rwanda, Malawi, Niger and Burundi are the least urbanised, with less than 20% of their populations considered urban.

However, contrary to the historical experience in much of the rest of the world, Africans currently do not move to urban areas in response to existing job opportunities in the manufacturing sector (which would increase productivity) but rather to escape the destitution and poverty of rural existence. (The movement of labour from rural subsistence agriculture to low-end services in the informal, urban sector is explored in the theme on jobs. Consequently, poverty is urbanising, and urban slums and informal settlements are expanding.[15M Ravallion, S Chen and P Sangraula, 2007, New Evidence on the Urbanization of Global Poverty. World Bank Research Digest, 1(4), pp. 26–28.] Sharp income inequalities in many African cities also mean that the economic growth reduces poverty to a limited extent. As a result, Africa has more urban poor than any other region.

Africa’s urban population growth is the fastest globally, although from a low base. Each year, urban Africa grows by an estimated 20 million people. By 2030, that number will be close to 25 million, and by then Africa will host six of the world’s 41 megacities. Cairo, Lagos, Kinshasa, Johannesburg, Luanda and Dar es Salaam will have more than 10 million inhabitants each, and 17 African cities will have a population of more than five million each.[16A Leke, M Chironga and G Desvaux, 2018, Africa’s overlooked business revolution] The African Economic Outlook 2016 predicted that Africa could see its slum population triple by 2050.[17AfDB/OECD/UNDP, 2016, African Economic Outlook 2016: Sustainable Cities and Structural Transformation, Paris: OECD Publishing]

The move from rural subsistence farming to urban informal employment in low-end services is positive in that it is moderately growth enhancing. However, the nature of Africa’s urbanisation is a significant drag on economic transformation: it is easier and less expensive to provide bulk services such as clean water, sanitation and electricity to people in denser settlements than to a population spread out across large rural areas. Paul Collier [18P Collier, 2016, African Urbanisation: An Analytic Policy Guide, London: International Growth Centre.] succinctly summarised the challenge and opportunity:

At its best, urbanisation can be the essential motor of economic development, rapidly lifting societies out of mass poverty. At its worst, it results in concentrations of squalor and disaffection which ferment political fragility. To date, African urbanisation has been dysfunctional, the key indication being that cities have not generated enough productive jobs. 

The management of its urban areas will present African leadership with immense challenges. Urbanisation has powerful socio-political implications, and it has become an important consideration in explaining the rise of populism in the West and in Africa, where urban areas are first to turn away from support of the governing party, evident in cities as diverse as Algiers, Addis Ababa, Harare and Johannesburg. Like elsewhere in the world, African urbanites also tend to be more politically engaged than people in rural areas. Inevitably, it is in the capital cities that support first goes to opposition parties.

Whereas urban populations are more cosmopolitan and often younger, rural populations are generally older and politically more conservative.[19P Auerswald and J Yun, 2018, As population growth slows, populism surges, The New York Times] Consequently, there is usually a marked difference in attitude between rural and urban people. ‘The young, regardless of where they live, tend to associate more with urban outlooks,’ write Auerswald and Yun.[20P Auerswald and J Yun, 2018, As population growth slows, populism surges, The New York Times]

Relationship between income growth and socio-demographic factors

Countries with high child mortality rates also tend to have high fertility rates, and a reduction in child mortality supports a virtuous cycle that is key to reducing fertility rates. As children’s health and survival improve, family demand for more children slowly declines. Smaller family size improves maternal and child education in a positive, reinforcing manner. As female education improves, and as child mortality declines, women have fewer children, which in turn allows for healthier and better-educated children. At the secondary level, female education has a particularly strong impact on reducing the average number of births per woman.

The result is that fertility rates are closely associated with education and income levels, as well as with urbanisation. In Ethiopia, for example, the fertility rate based on 2016 data was 6.4 children for poor women and 2.6 for wealthy women. The corresponding numbers in Tanzania for the same year were 7.5 and 3.1.[21The averages are for the top and bottom quintiles. Institute for Health Metrics and Evaluation, 2019, Global health data exchange] Geographically speaking, fertility rates in capital cities such as Accra and Addis Ababa are close to replacement levels, whereas those in rural parts of the Democratic Republic of the Congo are close to seven children per woman.[22D Canning, R Sangeeta and YS Abdo (eds), 2015, Africa’s Demographic Transition: Dividend or Disaster? Washington DC: World Bank, p. 18.]

Life expectancy in many African countries is also low. Whereas life expectancy in North Africa was estimated at almost 75 years in 2019 – roughly a year longer than the global average – it was 64 years in sub-Saharan Africa – nine years less than the global average, partly owing to the impact of HIV/AIDS and the continent’s high disease burden. In 2019, 24 African countries had a life expectancy below 64 years – the final year at which people are typically assumed to still be of working age.

The peak and length of the demographic dividend

A lengthy demographic dividend is an important explanation for the dynamism and growth of the US economy over an extended period: it entered its demographic dividend shortly before 1930 and will exit it only around 2026. As in Sweden, the USA has been able to attain high levels of income in this period. However, these numbers are now in a steep decline, in part owing to the clamp-down on inward migration and reductions in fertility.

In contrast, China will spend only around 50 years in this fortunate window (from about 1984 to 2037), roughly half that of the USA. This partly explains why China is unlikely to ever approximate income levels of the USA, reflected in the oft-repeated mantra that China will grow old before it gets rich.

Development takes time. Eventually, India will spend around 60 years in the demographic high-growth range, having only recently attained a ratio of 1.7 working-age persons to dependants. However, while China experienced a peak demographic dividend ratio of 2.8, India will likely peak at about 2.2 by around 2037. By this metric, India could experience a modest degree of income to catch up with China but only in the second half of the 21st century.

Nigeria is set to progress to the 1.7 ratio only by about 2060 in the Current Path forecast. It is expected to peak within 30 years at a ratio of 2.0 and to exit the favourable demographic window early in the next century. Given this long-term horizon, it is virtually impossible to speculate responsibly on Nigeria’s long-term future growth prospects, also because the region is expected to experience significant impacts from climate change at a time of significant technological advances. But what is sure is that current demographic forecasts condemn Nigeria to only moderate income growth and even then, only over extended time horizons.

The level at which countries achieve their peak demographic dividend – and how long they stay there – can have a significant impact on prosperity over long time horizons. The longer a country remains within this demographic window the better – although it is important to consider that the contribution of labour to growth declines over time owing to the effect of labour-saving technology.

A peak demographic dividend ratio of 2.8 (as seen in China in 2010) delivers more rapid economic growth than a peak of 2.2 (as expected for India by 2036) or a peak of 2.0 (forecast for Nigeria by 2084). This is because the size of the potential labour force relative to dependants is larger. China’s peak of 2.8 contributed significantly to its economic growth rate of almost 11% in 2010. According to the International Futures (IFs) Current Path forecast, India is projected to grow at 4.8% between 2030 and 2040 and Nigeria at less than half that in the 2090s, which is partly explained by its low peak of 2.0.

Looking to the end of this century, the ratio of working-age persons to dependants is set to contract in all regions except in sub-Saharan Africa, where it will peak at a ratio slightly below 2 by around 2075. At that point, Africa will have a population of 3.5 billion people (of whom 3.2 billion will be living in sub-Saharan Africa).

A different way to express this metric is that 67% of the population of sub-Saharan Africa will be of working age by 2075, whereas the average for the rest of the world is expected to be 60% by that time. The difference of seven percentage points suggests that sub-Saharan Africa will grow faster than global averages but not by much. Also, because Africa will achieve a relatively low worker-to-dependants ratio, it will very likely grow at quite modest rates along the Current Path forecast. None of this is good news for a continent that aspires to catch up with global income averages.

The potential benefits of reducing fertility rates

The trend line in Chart 8 shows that lower fertility rates are generally associated with higher levels of income in Africa.

Generally, a decline in fertility follows a decline in child mortality with a time lag of several years as parents come to no longer expect to lose as many children as they did previously.[23M Roser, 2017, Fertility rate] The provision of basic infrastructure for water and sanitation and advances in primary healthcare reduce infant mortality and eventually lead to lower fertility rates.

The need to have many children relates not only to the expectation that some children could die before reaching adulthood but also to families’ need for labour in economies dominated by employment in the agricultural sector (a characteristic of many poor and developing countries).

The level of female education is perhaps the most important driver in reducing fertility rates, further enhanced by women’s increased participation in the labour force, which is closely linked to improved female education and steady improvements in gender parity.[24M Roser, 2017, Fertility rate] For example, women who are better educated have more employment opportunities and are likely to want fewer children. Educated parents are also more likely to be better informed about modern contraceptives and the benefits of lower fertility rates with regard to educational opportunities. In contrast, fertility rates tend to be higher in regions where women have a lower social status, lower levels of decision-making opportunity and fewer opportunities outside the household.

Although the Middle East and North Africa are generally not considered progressive regions with regard to gender parity (with the limited exception of Tunisia), girls in these regions were about 5% more likely to be enrolled in primary school in 2015 than girls in sub-Saharan Africa. However, from an economic productivity perspective, the investment in female education in North Africa is largely wasted, with the female share of the total labour force being roughly half that in sub-Saharan Africa (24% versus 43%).

The use of modern contraceptives is a more immediate driver of total fertility rates than education, although poor access to education among women constrains uptake. Research suggests that the average gap between actual and desired fertility could be as high as two children per woman in sub-Saharan Africa,[25D Canning, R Sangeeta and YS Abdo (eds), 2015, Africa’s Demographic Transition: Dividend or Disaster? Washington DC: World Bank, p. 19.] pointing to a large pent-up demand for the provision of modern contraceptives. Data from the UN Population Division forecast that in 2018 the unmet demand for modern contraceptives in low-income Africa would have been 28% and 25% in lower middle-income African countries, with large country-to-country variations. In 2017, estimates for the unmet need for family planning in Africa for women of reproductive age (15–49 years) and who were married or in-union ranged from 12% (Zimbabwe) to 41% (DR Congo).[26United Nations Department of Economic and Social Affairs, 2018, Estimates and projections of family planning indicators 2018]

It is true, as alluded to in the introduction to this theme, that cultural factors across Africa may promote higher rates of fertility, with the dominant preference in Africa appearing to remain for big families. Although sub-Saharan Africa is currently the poorest performing region when it comes to the uptake of contraception use, things are rapidly changing, with all ten countries that showed fastest improvement in uptake between 2010 and 2019 being in this region (Malawi, Lesotho, Kenya, Sierra Leone, Liberia, Burkina Faso, Senegal, Uganda, Madagascar and Mozambique). Pessimism about Africa’s potential to reduce its fertility rates may thus be misplaced, with seven of the ten biggest decreases in total fertility rates globally between 2010 and 2019 also seen in sub-Saharan Africa (Uganda, Malawi, Sierra Leone, Ethiopia, Kenya, Chad and Somalia). [27United Nations Department of Economic and Social Affairs, 2020, World fertility and family planning 2020]

Constructing the Demographic Dividend scenario

This section explores the impact of a Demographic scenario, which could set the continent on a demographic trajectory quite different from that in the Current Path forecast. Owing to the slow-moving nature of demographic dynamics, the forecast projects to 2063, the final year of the AU’s Agenda 2063, and includes global comparisons to the end of the century. Although we consider the key policies that would lead to reasonable reductions in total fertility rates, we do not ask how these policies are motivated or assess the inevitable socio-political challenges that would be required.

The following are considered to be key strategies to effectively reduce total fertility rates in Africa:
Large-scale roll-out of modern contraceptives in sub-Saharan Africa (total fertility rates in North Africa are already very low). In 2019, only 31% of fertile women in sub-Saharan Africa were estimated to have been using modern contraceptives, ranging from 69% in Kenya to below 5% in Chad. Leadership, particularly through extensive community engagement, can change this.

  • Reducing under-five and maternal mortality [28Maternal mortality rate is a measure of the number of women who die while pregnant or within 42 days of the termination of pregnancy.] from communicable diseases. A high under-five mortality rate is an important driver of high levels of desired fertility, as high child mortality rates translate to families having more children. In sub-Saharan Africa, maternal mortality is set to decline from 480 deaths per 100 000 live births in 2019 to 189 by 2043, according to the Current Path forecast. However, country numbers differ significantly, ranging from more than a thousand deaths per 100 000 live births (South Sudan and Chad) to only 39 deaths per 100 000 live births (Cape Verde).

  • Improving female empowerment.[29IFs still uses the Gender Empowerment Measure (GEM) for its history and forecasts, although GEM has now been discontinued and replaced by the Gender Inequality Index (GII) as used by the UN Development Programme.] Women’s decisions about the number of children they want to have are generally considered the deep driver of changes in fertility rates. However, changes in social norms usually take longer to affect fertility than other measures.

In our Demographic scenario, we include contraception use and a reduction in child and maternal mortality but do not simulate measures related to improved gender equality, as shown in Chart 9. (Gender equality is included in the scenarios on governance and education as a proxy to emulate improvements in inclusivity.) These two interventions result in a reasonable but aggressive reduction in fertility and allow for the positive impact on human capital and the associated contribution to economic growth to be explored.

Chart 9: Modelling the Demographic scenario
Chart

Further assumptions in the Demographic scenario:

  • For contraception use, we do not apply interventions for Namibia, South Africa, Botswana, Libya, the Seychelles and Mauritius as these countries already show high levels of contraceptive use and relatively low total fertility rates. Lower middle-income countries and low-income countries in North Africa receive an ambitious push in contraceptive use, while low-income sub-Saharan African countries receive the most aggressive push, such that contraceptive use among fertile women in Africa is, on average, 15% higher in the Demographic scenario than in the Current Path forecast, increasing from approximately 52% to 67%. On average, even low- and lower middle-income Africa would need to achieve contraceptive usage rates of more than 65% by 2043, as opposed to rates closer to 50% on the current path (this could be achieved despite countries such as Chad, Sudan, South Sudan and Angola achieving usage rates under 40% in our scenario).
  • We push aggressively on improvements to basic healthcare to reduce child and maternal mortality rates. Again, our interventions are most aggressive in low-income countries and least aggressive in middle-income countries, with some upper middle-income countries also receiving a more moderate treatment. In the Demographic scenario, interventions are likely to reduce maternal mortality from 174 to 105 deaths per 100 000 live births across Africa and under-five mortality from 40 to 33 deaths per 1 000 live births across Africa.

As shown in Chart 8, the impact of our interventions would result in a total fertility rate of about 3.3 children per fertile woman across Africa by 2033 (as opposed to 3.7 in the Current Path forecast) and about 2.7 per fertile woman by 2043 (as opposed to 3.2 in the Current Path forecast). In both low- and lower middle-income Africa, the targeted rate would likewise be 2.7 children per woman by 2043, while fertility rates approximate replacement rate in upper middle-income Africa by 2033.

Chart 11 presents Africa’s total population to 2063 in the Current Path forecast and the Demographic scenario compared with the medium-variant population forecast from the UN Population Division.

Given the momentum behind Africa’s youthful population, the impact of the Demographic scenario on the size of the world’s population would be substantial. In the Current Path forecast, the global population is expected to peak at 10.6 billion people by around 2090. In the Demographic scenario, the peak is expected to be about a decade earlier, at roughly 10.1 billion people, which has considerable positive implications for global sustainability.

By the end of the century, Africa’s population is expected to have grown to 3.2 billion people in the Demographic scenario (constituting 32% of the global population) and be close to its peak. In contrast, the Current Path forecasts the population to be approximately 3.8 billion people by this time (constituting 36% of the global population) and still be several decades away from a peak for the continent.[30Forecasts over extended time horizons are very uncertain. Forecasting to 2043 is already stretching our understanding of how human and natural systems interact, and things will certainly be very different by 2063 and even more so by 2100.]

Impact of the Demographic Dividend scenario on Africa’s economy

Chart 12 shows the impact of the Demographic scenario on Africa compared with that of the Current Path forecast. We focus on sub-Saharan Africa in our analysis, bearing in mind that North Africa is much further along in the demographic transition and benefits little from the Demographic scenario. The chart also includes a forecast for the world excluding Africa, showing that the ratio of working-age persons to dependants peaked in 2012. We include this to show that, outside of Africa, the size of the working-age population relative to dependants is now declining, although it differs from region to region, implying that these regions have to first compensate for that decline with more capital and technology to maintain current levels of productivity.

The Demographic scenario advances the onset of sub-Saharan Africa’s peak demographic dividend by eight years (from 2077 to 2068) and increases the ratio of persons of working age to dependants from 2.0 to 2.2. In the Demographic scenario, sub-Saharan Africa gets to the 1.7 ratio in 2043 and exits in 2095, about the same period as it spends in this favourable window in the Current Path forecast. However, because the peak ratio is higher, incomes are expected to grow more rapidly in the Demographic scenario. Although the total size of the economy of sub-Saharan Africa would be slightly smaller, as one would expect with a smaller population, GDP per capita is expected to be more than US$556 higher by 2063 than in the Current Path forecast – for a population of 2.4 billion people.

With more people of working age and fewer children to educate, less basic infrastructure to build and slowing population growth, the improvements cascade across various indices of human well-being. For example, 43.3 million fewer people are expected to be living below the extreme poverty line (US$1.90) in sub-Saharan Africa by 2043 and 34.6 million fewer people by 2063.

Chart 11 shows that in the Demographic scenario, countries for which GDP per capita improves most tend to be those with more aggressive reductions in total fertility rates.

Countries such as Ethiopia, Zambia, Uganda, Rwanda, Madagascar and Zimbabwe are forecast to experience an improvement of 4.7–6.8% in GDP per capita relative to predictions in the Current Path forecast by reducing fertility rates by at least 0.5 by 2043. Strikingly, Malawi is set to benefit most, with its GDP per capita expected to increase by more than 8% with a reduction in fertility rate of only 0.3. This demonstrates that for some countries even a small reduction in fertility rate could create substantial increases in welfare. 

In dollar terms, the gains are also significant (and generally increase), as can be seen in Chart 12. Equatorial Guinea, Gabon and Nigeria are set to benefit most, with each accruing over US$1 000 more per person by 2063. Notably, a number of countries (e.g. Kenya, Swaziland, Rwanda, Ethiopia, Algeria, Zimbabwe and Egypt) benefit significantly by 2043, receiving over US$200 extra in GDP per capita, although the impact of the scenario dissipates by 2063 as these countries are already making strides towards the demographic dividend; the scenario largely accelerates the achievement of these gains.

Impact of the Demographic Dividend scenario on Africa’s population structure

Charts 15 and 16 show the effects of the Current Path and Demographic scenarios on population structure and education by 2063 for sub-Saharan Africa. In the Demographic scenario (chart 16), the region has a more mature population structure, with a distinctive bulge along the midriff, compared with the more youthful structure seen in the Current Path forecast (chart 15).

By 2048, about 6.5 million more Africans would be enrolling for upper secondary education in the Demographic scenario compared to the Current Path. The median years of adult education in sub-Saharan Africa would also have increased by six months (to 7.7 years), with a concomitant impact on labour productivity. All these effects are due to the impact of reduced fertility.

The pyramids for Nigeria (Chart 17 and 18) show similar trends as that of sub-Saharan Africa as a whole. The beginnings of a population transition emerge as Nigeria begins to move from the less-developed pyramid shape (Chart 17) to the more oval shape of a more developed demography (Chart 18).

COVID-19 and the Demographic Dividend scenario

The COVID-19 pandemic will likely present a challenge to Africa as it seeks to benefit from the demographic dividend, despite the continent’s youthful population likely having spared it from the death rates seen in countries with older populations. 

The acute focus of healthcare systems on fighting the pandemic likely means that fewer resources will be dedicated to family planning, reproductive health services and healthcare for new mothers and infants. In addition, disruptions to academic programmes and teachers having been affected directly by the disease compromise educational quality, another variable in fertility rates. Government-imposed restrictions on movement, as well as fear of catching the disease, have been cited by fertile adults in Africa as a reason for not obtaining contraception during the pandemic. The global economic downturn associated with the pandemic will likely mean that government revenue, and thus capacity to implement fertility-reducing programmes, could be overstretched for years to come. 

It is then unsurprising, in the wake of these disruptions, that the rate of unwanted teen pregnancies has increased during the pandemic owing to an interruption in family planning services as well as the typical impact that economic downturns have on fertility. It is likewise concerning that an increase in incidents of gender-based violence were reported during the pandemic, implying women’s social emancipation (the deep driver of fertility rates) may also be under threat. [31South African Department of Social Development, 2020, Demography and COVID-19 in Africa: Evidence and policy responses to safeguard the demographic dividend; B Onyango, 2020, The impact of COVID-19 on the demographic dividend pillars in Africa, presentation as part of the webinar ‘The impact of COVID-19 on the African continent’s prospects of harnessing a demographic dividend’, 11 November 2020]

Conclusion: Working towards Africa’s demographic dividend

This theme explains how the very high fertility rates currently seen in much of Africa are a drag on development. Although Africa’s demographic profile has started to improve since the late 1980s, the ratio of working-age persons to dependants has improved only slowly. According to current expectations, sub-Saharan Africa will achieve a demographic dividend only in the second half of the 21st century, at which point the contribution of a larger labour force to economic growth is likely to have reduced significantly in favour of the contribution from technology.

Although a large body of literature supports the idea that the empowerment of women can improve overall development outcomes, we did not include it as a factor in our Demographic scenario; instead, we include an intervention on gender empowerment in the scenarios on democracy and education. Similarly, the enhancing effect of investing in basic infrastructure for the provision of clean water and improved sanitation on the demographic dividend and realising its potential through increased job opportunities are discussed separately.

Africa needs disproportionately higher rates of fertility decline in countries with fast-growing populations (which have to date had a less-than-average rate of fertility decline). The interventions modelled in this theme will require governments, especially those in low- and lower middle-income countries, to make family planning a high priority on their developmental agenda. This applies most pertinently to Niger, Somalia, the DR Congo, Chad, Mali, Angola, Nigeria, Burundi, Burkina Faso, The Gambia and Uganda. In all these countries, the total fertility rate exceeded five children per woman in 2019. In an additional 25 countries, the average fertility rate is between four and five children per woman. That rural fertility rates are significantly higher than those in urban areas and differ according to income complicate these dynamics.

From a societal perspective, Africans need to engage candidly and robustly in public discussions and scholarly analysis on the economic, developmental and emissions implications of the continent’s largely youthful population. Changes in fertility reflect shifts in social and cultural norms that may take time, yet even a slow start to the fertility transition can rapidly pick up momentum. Political leadership in discussing gender inequality, fertility and family size is vital, as are public media campaigns that demonstrate the health and economic benefits of smaller families.

There are additional benefits of advancing Africa’s demographic dividend, including the prospect for less political turbulence with a declining youth bulge (proportion of the population between 15 and 29 years), the lower chance of experiencing a violent political transition and the increasing likelihood of being a liberal democracy as median age increases. Whereas the youth bulge in the rest of the world peaked at around 42% in 1980, Africa only gets to the 42% mark by about 2040.

Although the impact of the Demographic scenario is significant, it is insufficient to reverse the Current Path forecast of growing divergence in average incomes between Africa and the rest of the world. The continent requires a consort of structural transitions to improve its development prospects, as discussed elsewhere in this website.

Endnotes

  1. M Roser, 2019, Economic Growth

  2. African Union Commission, 2006, African Youth Charter

  3. African Union, 2011, African Youth Decade 2009-2018 Plan of Action

  4. African Union Commission, 2017, AU Roadmap on harnessing the demographic dividend through investment in youth, Addis Ababa: African Union.

  5. These depart from the UNPD’s definitions in that a favourable ‘demographic window’ is described to open when the proportion of children (0–14 years) is less than 30% and the proportion of seniors (+64 years) is less than 15%. A median age of 25.6–40 years is used. R Cincotta, 2017, Opening the Demographic Window: Age Structure in Sub-Saharan Africa.

  6. H Ritchi and M Roser, 2019, Age structure

  7. D Canning, R Sangeeta and YS Abdo (eds), 2015, Africa’s Demographic Transition: Dividend or Disaster? Washington DC: World Bank, pp. 6–7

  8. E-mail communication with Richard Cincotta, 19 May 2021.

  9. This is also known as the first dividend as opposed to the so-called second and third dividends, which are the result of savings and investments and improvements in productivity, respectively.

  10. The dependency ratio is the inverse of the demographic dividend. If the labour force increases in size relative to dependants, it causes the dependency ratio to decrease (or the demographic dividend to increase), in which case economic growth is very likely to follow. So, a dependency ratio of 1:1 means that every worker has to support one dependant. In a country such as South Korea, which had a dependency ratio of 0.39 in 2018, each person of working age only had to support one-third of a dependant. Japan bottomed out at a dependency ratio of 0.43 in 1992. China and the Asian Tigers bottomed out at 0.36 in 2010 and 2013, respectively. All these countries experienced their periods of most rapid economic growth in the years during which their dependency ratios were declining.

  11. In the least developed countries, one in four children (aged 5–17) is estimated to be involved in child labour. International Labour Organization, 2015; International Labour Organization, 2018, Women and Men in the Informal Economy: A Statistical Picture, Geneva: International Labour Office; World Report on Child Labour 2015: Paving the Way to Decent Work for Young People, Geneva: International Labour Office.

  12. A rate of 2.1 children per woman is generally accepted as the replacement fertility rate. Without inward migration, populations start to decline below this rate.

  13. See: P Eloundou‐Enyegue, S Giroux and M Tenikue, 2017, African Transitions and Fertility Inequality: A Demographic Kuznets Hypothesis. Population and Development Review, 43(S1), pp. 59–83.

  14. C Roxburgh et al., 2010, Lions on the Move: The Progress and Potential of African Economies, Brussels: McKinsey Global Institute, p 19.

  15. M Ravallion, S Chen and P Sangraula, 2007, New Evidence on the Urbanization of Global Poverty. World Bank Research Digest, 1(4), pp. 26–28.

  16. A Leke, M Chironga and G Desvaux, 2018, Africa’s overlooked business revolution

  17. AfDB/OECD/UNDP, 2016, African Economic Outlook 2016: Sustainable Cities and Structural Transformation, Paris: OECD Publishing

  18. P Collier, 2016, African Urbanisation: An Analytic Policy Guide, London: International Growth Centre.

  19. P Auerswald and J Yun, 2018, As population growth slows, populism surges, The New York Times

  20. P Auerswald and J Yun, 2018, As population growth slows, populism surges, The New York Times

  21. The averages are for the top and bottom quintiles. Institute for Health Metrics and Evaluation, 2019, Global health data exchange

  22. D Canning, R Sangeeta and YS Abdo (eds), 2015, Africa’s Demographic Transition: Dividend or Disaster? Washington DC: World Bank, p. 18.

  23. M Roser, 2017, Fertility rate

  24. M Roser, 2017, Fertility rate

  25. D Canning, R Sangeeta and YS Abdo (eds), 2015, Africa’s Demographic Transition: Dividend or Disaster? Washington DC: World Bank, p. 19.

  26. United Nations Department of Economic and Social Affairs, 2018, Estimates and projections of family planning indicators 2018

  27. United Nations Department of Economic and Social Affairs, 2020, World fertility and family planning 2020

  28. Maternal mortality rate is a measure of the number of women who die while pregnant or within 42 days of the termination of pregnancy.

  29. IFs still uses the Gender Empowerment Measure (GEM) for its history and forecasts, although GEM has now been discontinued and replaced by the Gender Inequality Index (GII) as used by the UN Development Programme.

  30. Forecasts over extended time horizons are very uncertain. Forecasting to 2043 is already stretching our understanding of how human and natural systems interact, and things will certainly be very different by 2063 and even more so by 2100.

  31. South African Department of Social Development, 2020, Demography and COVID-19 in Africa: Evidence and policy responses to safeguard the demographic dividend; B Onyango, 2020, The impact of COVID-19 on the demographic dividend pillars in Africa, presentation as part of the webinar ‘The impact of COVID-19 on the African continent’s prospects of harnessing a demographic dividend’, 11 November 2020

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Cite this research

Jakkie Cilliers (2022) Demographics. Published online at futures.issafrica.org. Retrieved from https://futures.issafrica.org/thematic/03-demographic-dividend/ [Online Resource] Updated 24 August 2022.