This chapter explores the extent of and trends in care work in sub-Saharan Africa and makes a case for gender-responsive care policies. Care work, which encompasses both unpaid and paid care, is often undervalued and disproportionately falls on women and girls. Available time-use data show that caring responsibilities vary substantially with women’s personal and labor market characteristics, and employed women—if their paid and unpaid work activities are added together—have much longer workdays. The unequal distribution of care work hinders women’s empowerment, perpetuates gender stereotypes, and contributes to economic and social inequalities. Care work should be a critical component of the development agenda; there is a substantial need for better data, analysis, and research to inform gender-responsive care policies and measure progress. The authors outline the current state of care services and infrastructure in sub-Saharan Africa and present a framework for transformative care policies in the region. The chapter concludes by underscoring the significance of prioritizing care policies and infrastructure to achieve gender equality, inclusive development, and resilience in the face of crises.
Introduction
Care work—essential for sustainable economic development, social well-being, and the future of decent employment—involves the activities and social relations required to satisfy the productive and reproductive needs of all human beings. This includes direct care for children, the elderly, people living with disabilities, and people facing illnesses, as well as indirect care or domestic work, such as providing food and other necessities for a household. Care work encompasses two spheres of work—unpaid care work, including both direct and indirect, that is provided by individuals for the household or community, and paid care work that is usually direct care performed for pay or profit.
Care is a universal right and an essential public good. Despite its importance to society and the economy, care work is often not recognized as skilled work or a public issue. Households, governments, the private sector, and the community should share the responsibility for providing care work. Yet, most of the care work worldwide is undertaken by unpaid carers at a household level, and women and girls shoulder a disproportionate responsibility for it. Although unpaid care work can be rewarding, it is often drudgery, and its unequal distribution by gender forms a major barrier to women’s empowerment in economic, political, and social spheres, and it hampers the overall well-being of women and girls. Compared with their prevalence in the labor market, women are also overrepresented in paid care jobs, especially domestic work jobs. Complex socioeconomic norms precipitate the disproportionate distribution of unpaid care work by gender and the feminization of care work. Care work is viewed as an extension of women’s “natural” role as caregivers and thus perceived as a women’s issue.
Despite data limitations, a few trends in sub-Saharan Africa are clear. First, women and girls make up most of the unpaid care workforce. According to estimates from the International Labour Organization (ILO), Addati and others (2018), and Charmes (2019), women and girls spend as much as 3 to 3.4 times more on unpaid care work than do men and boys. Second, responsibilities of women to provide unpaid care work hinders their economic, social, learning, and leadership opportunities. Women in sub-Saharan Africa cite unpaid care work duties as the top reason for not participating in the labor force (Addati and others 2018). In addition, women in households with dependents (children or elderly people) work fewer hours in paid employment than do women in households with no dependents. Third, on average, women’s workdays—when both paid and unpaid work hours are added together—are much longer than men’s. Time poverty among employed women is significant and can lead to or exacerbate income poverty when women and households are unable to outsource care services (Zacharias, Antonopoulos, and Masterson 2012). Fourth, when women engage in paid work, their unpaid care responsibilities do not decrease proportionately. This affects their overall well-being, the quality of care enjoyed by caregivers and care recipients, and women’s overall productivity both in paid and unpaid work. Finally, paid care work is a very important source of employment for women, and most women in paid care jobs are domestic workers with informal working arrangements, low pay, and poor working conditions.
Why do we need better care policies and investment in care infrastructure in sub-Saharan Africa?
For better social, economic, and political growth of women and girls. Considerable research has identified unequal gender distribution of care work as a key barrier to women’s social, economic, and political empowerment. Socially prescribing women and girls as caregivers undermines their basic human rights and limits their opportunities and capabilities. Better care policies and infrastructure are key for alleviating gendered inequalities and increasing women’s quality of life.
For poverty reduction, which includes better health and education outcomes for all. Care work is systematically linked with economic inequality, poverty, and precarity. Care work is largely performed by women and girls within the home in an unpaid manner; thus, it affects marginalized households the most. Marginalized households lack essential infrastructure, such as clean water and fuel, so women spend more time on indirect care work. Moreover, low-income households are unable to afford quality childcare services or domestic care services. This constrains women from doing paid work or from working for more hours in paid jobs. Thus, evidence shows that better care systems, especially public childcare provisions, are fundamental to overcoming poverty and reducing inequalities (Halim, Perova, and Reynolds 2023). Further, better quality care services enhance quality of life as well as health care and education outcomes for care recipients, especially children (Staab 2015).
For supporting inclusive economic growth and development. Investment in care systems linked to labor market policies can create jobs, increase women’s productivity in both paid and unpaid work, facilitate women’s participation in the labor market, and remove inequalities in the labor force and at the household level. Women’s entry into the labor market and increased productivity lead to large economic dividends; this is linked to the fact that paid care work is an important source of employment for women, and it is poorly remunerated, undervalued, and frequently carried out in precarious conditions. Quality employment also generates more economic activity and higher tax revenues for the government. Overall, better care systems support inclusive economic growth and development.
For creating a resilient society and economy. The COVID-19 pandemic made even more evident the deficiency in how care systems are set up. Sub-Saharan Africa is vulnerable to crises, including but not limited to internal and external conflicts, environmental degradation, and climate change. Crises tend to increase care needs, make care work more arduous, and compound the injustices related to its unequal distribution. Such effects are felt most by those pursuing subsistence livelihoods. Robust care infrastructure and care systems help families, communities, and societies weather these crises.
In light of these factors, development practitioners and policymakers are increasingly recognising the need for better care policies and care infrastructure. This chapter discusses the state of care work and care policies in sub-Saharan Africa and highlights the need for more data and analysis to further the care agenda. The rest of this chapter is organized as follows: The second section uses available data in sub-Saharan Africa to measure trends and determinants of care work, both paid and unpaid, and discuss the importance of data and time-use surveys (TUSs); this section constitutes the core of the chapter. The third section, “Transformative Care Policies,” discusses what transformative care policies look like and presents an overview of the state of the care economy in the region. The fourth section, “From Better Data to Better Measures of Progress,” makes the case for better data, statistics, and research on care for informing gender-responsive care policies and measuring progress. The final section contains a summary and considers avenues forward.
Measuring Care Work in Sub-Saharan Africa: Paid and Unpaid
All over the world—and sub-Saharan Africa is no exception—the family or household provides most unpaid care work. Surveys on time use and the labor force are complementary sources of data for understanding the extent, trends, and determinants of unpaid care work. Although the paid care sector in sub-Saharan Africa is small, it is essential to the functioning of society. This section mainly draws on estimates from the ILO (Addati and others 2018), compiled using the latest TUSs and labor force surveys in all sub-Saharan African countries where data were available. First, the authors measure the magnitude and determinants of unpaid care work, composed of own-use production work of services1 and volunteer work in households producing services according to the 19th International Conference of Labour Statisticians Resolution I concerning work, employment, and labor underutilization. Second, the authors assess labor market characteristics of unpaid carers. Third, they examine care jobs and care workers. Fourth, they discuss data gaps and TUSs.
Extent of and Trends in Unpaid Care Work
The average woman in sub-Saharan Africa2 spends 249 minutes per day on unpaid care work; figure 17.1 presents average time spent by women on unpaid care work by country and category (Charmes 2019). In comparison, the average man spends 87 minutes per day on unpaid care work, which is about 40 percent of the time spent by women on the same activities. Figure 17.2 presents ILO estimates of time spent on unpaid care work by men, by country and category. Both men and women spend most of their time on domestic services for own final use within households (for example, indirect care work, housework), indicating such services’ importance for all adults. Caregiving services to household members (that is, direct care work) make up the next largest category of unpaid care work and community services. Help to other households (for example, volunteer work, a mixture of direct and indirect care work) makes up the smallest category of unpaid care work.
The average time spent on unpaid care work varies considerably across countries. Men in Mali spend the least time (21 minutes) and men in Cabo Verde spend the most time (246 minutes). It is worth noting that Cabo Verde is characterized by a difference in data collection methodology, so the authors urge caution about comparing Cabo Verde with other countries.3 Women’s unpaid care work ranges from 212 minutes in Cameroon to 291 minutes in Ethiopia. Mali has the largest gender divide, with women performing 92 percent of total unpaid care work. Even in Cabo Verde, which has the smallest gender divide in time allocation, women do 66.6 percent of the total unpaid care work.
Women’s Time Spent in Unpaid Care Work, by Country and Categories
(Minutes per day)
Source: Charmes 2019.Note: Refer to Annex 17.1 for survey year and characteristics.Men’s Time Spent in Unpaid Care Work, by Country and Categories
(Minutes per day)
Source: Charmes 2019.Note: Refer to Annex 17.1 for survey year and characteristics.The large gender gap in time spent on unpaid care work has two main and direct effects. One, women participate much less in paid work. In sub-Saharan Africa, women work only 0.66 hour for every 1 hour spent by men in paid work. Second, the total working hours spent by women per day is more than that spent by men. If the total time spent working, both paid and unpaid, is added together, women spend 432 minutes per day working, while men spend only 361 minutes, on average, which means that women have less time available for other activities such as education, participating in civic activities, or leisure. This outcome— referred to as time poverty4—can lead to or exacerbate income poverty for women and households. It can also lead to poor-quality care for recipients and affects the health and well-being of the unpaid carers. Research confirms that women’s labor force participation shrinks the gender gap in unpaid care work, but the decrease in time spent by women in unpaid care work does not lessen in proportion. Rost, Bates, and Dellepiane (2015) conducted a study in Ethiopia, Philippines, Uganda, and Zimbabwe; the researchers found that women spend 10 to 44 fewer minutes on primary unpaid care work per 60 minutes of paid work; however, women’s participation in paid work has no effect on secondary care work or supervision of dependents.
Gender gaps in time use are not uniform; they vary based on numerous socio-economic factors and individual characteristics, which highlights that intersec-tionality matters. Overall unpaid care work done by women and girls is higher in rural areas, for less educated women, for married women, and for women living in households with children. Men in rural residence and men living with children spend more time on unpaid care work, similar to women. However, the addition of a child to the household increases women’s care duties more than men’s care duties. Interestingly, more educated men spend more time on unpaid care work, indicating that education may influence social norms. In Ethiopia, Ghana, and Tanzania, young women spend as much or more time on unpaid care work as do adult women. Children are also significant providers of unpaid care work in Africa, and girls perform more work than do boys.
Unpaid Care Workers and the Labor Force
The authors now compare people living with care recipients at home (children under 15 years or elderly people), a proxy for people with high unpaid care work responsibilities, with people living without care recipients. This assessment continues to use ILO estimates (Addati and others 2018), based on data from national labor force surveys and household survey microdata, which covers 24 countries and approximately 70 percent of sub-Saharan Africa’s population. As shown in Figure 17.3, approximately 36.4 percent of women with direct care responsibilities are outside the labor force, compared with 19.8 percent of men living with care recipients. Conversely, 24.3 percent of men living without dependents are outside the labor force, which is much more than men with care responsibilities. In this way, men living with care recipients experience a labor force premium, which provides evidence for the “male as breadwinner” model.
Labor force and household surveys from 21 African countries covering 61 percent of the region’s population show that the most important reasons cited by women for being out of the labor force was unpaid care work (34.4 percent), followed by personal reasons—that is, being in education or being sick or disabled (33.8 percent). Sub-Saharan Africa’s share of people ages 15 to 24 is also substantial (20 percent), and a large proportion of these young people are not in employment, education, or training (NEET). Based on data from nine5 countries in east and southern Africa, Perry (2022) found that women are more likely to be NEET than men. Importantly, care work increases the probability of NEET status for women, especially for women 20 to 24 years old. Taken together, these findings suggest that women’s labor force participation is hurt by caring responsibilities.
Unpaid Carers and Persons Not Living with Dependents, by Gender and Labor Force Status
(Percentage)
Source: Addati and others 2018.Note: Refer to Annex 17.1 for survey year and characteristics.Income and residence also affect labor force participation decisions. Women living without care recipients are less likely than women living with care recipients to participate in the labor force. This is most likely explained by the fact that in resource-poor environments, women must search for paid work when there are dependents to look after. Further, households in sub-Saharan Africa often consist of extended family members—an arrangement that allows for care responsibilities to be shared. Unpaid carers are also less economically disadvantaged in rural areas, where 34.7 percent of women with care recipients at home are outside the labor force, compared with 41.6 percent of their urban counterparts.
In sub-Saharan Africa, whether a woman resides in a household with dependents alters the intensity and quality of her employment. In households with dependents, especially with young children who are less than six years old, women work fewer hours in paid employment; men see no such trend. Using data from 23 countries, which constitute 72 percent of the total employed population in sub-Saharan Africa, the authors find that the gender gap in working hours per week was 5.2 hours for employed men and women living in households with no children. This gap rises to 6.8 hours for employed men and women living in households with one child and increases further to 7.2 hours for employed men and women in households with two children. It is a well-documented fact that women’s wage employment is low in sub-Saharan Africa, but it dips even lower for employed women carers (13.8 percent). Most employed women living with dependents work in the informal sector (92.2 percent), mostly in own-account and contributing family work, which is slightly higher than employed women who live with no dependents (88.6 percent). Informal jobs come with significant downsides, but one reason women prefer them is for the flexibility they allow for juggling unpaid care work and paid work (Ceita 1999 cited in González and Grinspun 2001; Marcucci 2001; Verceles and Beltran 2004; Ramirez and Roses 2005).
Care Jobs and Care Workers
A serious deficit exists in care service provisions in the region. Sub-Saharan Africa has the lowest proportion of paid care jobs among all regions in the world, although there is considerable variation across countries. The care workforce generally includes (1) workers in education, health, social work, and domestic work; (2) care workers in other sectors (such as nurses in factories); and (3) non-care workers in care sectors (such as cooks and cleaners in a hospital or school). In sub-Saharan Africa, about 10.7 percent of employed women, compared with only 5.4 percent of employed men, are employed in care jobs. Duffy (2021) estimates that the care employment constitutes as much as 18 percent of total employment in South Africa and as little as 3.5 percent of total employment in Mozambique.
Such feminization of care work holds true across the world, and care work is often an entry point into the labor force for women in low-income countries. In sub-Saharan Africa, only about half of the care workers in care sectors are women, although this statistic hides significant vertical and horizontal segregation: the majority of the high-status care jobs are held by men. Agriculture is the largest sector in most sub-Saharan countries and women are overrepresented in agricultural jobs. For instance, about three out of every four people in Mozambique work in agriculture and 58 percent of agriculture workers are women (Duffy 2021).
On average, care work is underpaid, unprotected, and undervalued. These characteristics are related to its perception as an extension of women’s care roles, which lends it low status and low social recognition. However, not all care workers earn low wages. Hierarchies and differences exist among care workers in terms of remuneration, working conditions, and status. Some care professions are legally and socially regulated, which makes them high status and better paying. For example, medical doctors earn 55 percent more than nurses and 89 percent more than midwives in South Africa.
Domestic work is an important sector of care work in the region. About a third of sub-Saharan Africa’s care workforce, 2.3 million people, are domestic workers. This is a strongly feminized sector: 80 percent of all domestic workers are women. Informal working arrangements, low remuneration, and long working hours are common characteristics of domestic work in the region. Domestic work happens behind closed doors and comes with much higher risk of sexual harassment and physical violence. These workers are isolated and unable to organize, aspects that affect their bargaining position and contribute to their lower pay and long working hours. The pay penalty is particularly prevalent in this sector, for example, as found in South Africa (Budlender 2011). Given the relational nature of care work, it is also difficult to threaten to withdraw services or go on strike.
Data Gaps and TUSs
Unfortunately, much is left to be understood, especially about unpaid care work. For example, men’s and women’s contribution to unpaid care work has fallen slightly across the globe from 1997 to 2012; however, overall gendered distribution of unpaid care work remains largely the same. This global estimate is based on 23 countries with time series data, which include only 3 African countries (Benin, South Africa, and Tanzania). Thus, the authors cannot generalize this trend to sub-Saharan Africa. Similarly, income and time poverty move together and have an inverse-U relationship across the globe, but it’s unclear whether this holds true in sub-Saharan Africa. Also, links between time poverty and inequality, agricultural productivity, income poverty, and labor force participation are not yet understood.
Lack of nationally representative and comparable time-use data remains a big part of the challenge. The authors use data from 10 countries in sub-Saharan Africa, where comparable data from TUSs were available between 1998 and 2019. Since then, a few more countries in the region have conducted TUSs, some of which are still forthcoming. Yet most countries in the region have not conducted such surveys. To a great extent, this is because these surveys are costly and complex to conduct and require literate respondents. Time-use data are most reliably collected based on time diaries—that is, through an inventory of all activities conducted in the previous 24 hours. However, this effort requires literacy and numeracy. Asking stylized questions on a one-week reference period is still common practice in some TUSs. This approach avoids the problem of literacy and numeracy but often results in imprecise estimates. Further, there are problems with harmonizing definitions across countries and surveys and with adequately capturing activities that are simultaneously undertaken—for example, watching television while caring for a child.
Transformative Care Policies
This section discusses the ILO’s 5R framework, a policy approach to care work, applied to sub-Saharan Africa. The authors also introduce the African Care Economy Index (ACEI), which measures social recognition and state support for care work in African countries and reveals significant deficits in care policies across the region.
The 5R Framework
The care diamond expresses the social division of care in a society among four key institutional actors: families and household, markets, the state, and the community and other civil society organizations (Figure 17.4; Razavi 2007). Although most unpaid care work is concentrated at the household level, paid care work forms the other three points of the diamond. Governments are primary duty bearers for the provision of care services and care infrastructure. Care is both a right to which people should have access and a function that some people perform. From a rights-based perspective, care policies ensure that everyone has the right to receive and provide quality care.
The Care Diamond
Source: UN Women Training Center. https://portal.trainingcentre.unwomen.org/product/introduction-to-care-work-and-care-economy/.Note: Reproduced with permission from UN Women.The ILO’s 5R framework is a human rights–based and gender-responsive approach to public policy for care work. The framework recommends that policy should recognize, reduce, and redistribute unpaid care work; reward paid care work; and guarantee representation for care workers through social dialogue and collective bargaining. It aims to build a virtuous cycle to mitigate inequalities in care work, improve the socioeconomic lives of unpaid carers and paid care workers, and address barriers that keep women from entering the labor force. By extension, it works to improve quality of care for care recipients.
As a first step, more widespread recognition of the importance of care work at both the international and national level is required. Care work is necessary for all; requires time, energy, and skills; and comes with an opportunity cost in terms of time not spent on other activities. There was a landmark resolution in 2013 by the 19th International Conference of Labour Statisticians for inclusion of unpaid work and household production in System of National Accounts. However, national-level legislation and policy efforts across all countries in sub-Saharan Africa are far from including unpaid care work in national statistics. Foremost, there is a need for robust data at a national level, especially time-use data. Further research is required to measure all forms of care; understand links with GDP, poverty, and labor force participation and mitigating factors; and track progress in building care policies, care infrastructure, and care services.
Reducing unpaid care work requires public investment in both (1) social care services infrastructure and (2) physical rural infrastructure that is of high quality and affordable and accessible to all. Social care infrastructure—physical, human, and financial—supports universal social care services for children and people living with disabilities as well as universal health care. It transforms a substantial amount of unpaid domestic care work to paid social care work. In the absence of state involvement, such care services are expensive and quality services are available only to the high-income minority. This situation enhances gender, class, and intergenerational inequalities and leads to increased reliance on informal labor and migrant domestic workers. Building better physical rural infrastructure lessens unpaid care work by reducing the time required to deliver indirect care work. This includes but is not limited to building roads and providing access to clean water, sanitation facilities, electricity, digital technology, and the internet. Protection of natural resources such as land and water is equally important in ensuring adequate and inclusive care infrastructure for all. The formal private sector also has a role to play in protecting workers and providing decent working conditions so these employees are not overworked, undervalued, or underpaid.
Redistributing care work calls on two types of redistribution: between women and men and between all actors in the care diamond—households, the state, the private sector, and the community. Given the gender-based division of care labor, all relevant actors must aim to eliminate discriminatory social norms and gender stereotypes that assign care work to women by promoting positive masculinities to encourage men’s increased participation in care work. Such transformation of mindsets cannot happen in isolation and requires changes across society. Efforts must be culturally sensitive and emphasize strengthening the family unit and community bonds in sub-Saharan Africa. Furthermore, the state must actively take up responsibility for providing care as a universal right, in terms of both access to and quality of care services. Households usually bear the ultimate responsibility for filling care deficits and assume care responsibilities when public provisions are lacking. Important areas of intervention include labor market regulation and provisions of public care services. The state also has an active role to play in encouraging and incentivizing the private sector to offer gender-inclusive family-friendly employment policies to maintain work–life balance and maternity and paternity leave; they must support carers at the workplace. The last point of the care diamond, the community, can also support care work in various ways, from formalized entities to unofficial community-based networks.
Paid care work is systematically undervalued and underpaid. Policy efforts should seek to adequately reward paid care work, recognizing that it requires skills and resources. This includes regulating formal employment terms and conditions so that they reflect the principles of equal pay for equal work and decent working conditions. It is crucial to recognize that most of the labor force in sub-Saharan Africa, especially care workers, is concentrated in the informal sector. Thus, the state must focus its efforts on formalizing care systems and ensuring that social protection schemes include informal workers and migrant workers. Laws and policy measures must also ensure safe working conditions for paid care workers. Promoting representation of workers through collective bargaining and social dialogue is an equally important focus area. Decades of privatization and austerity have eroded collective bargaining power (Montague-Nelson 2022), but collective action remains an important forum in which paid care workers, especially women, can engage with employers and governments to discuss and negotiate working conditions and participate in decision-making processes.
Although not officially a part of the 5R framework, there is an emerging need to recognize the significance of resilience as an important characteristic of care systems. The COVID-19 pandemic shed light on the importance of care in the face of crisis. Sub-Saharan Africa is prone to various crises, including conflicts, climate change, and public health emergencies. Essential care services are needed more than ever in crisis situations, which often exacerbate the gendered distribution of care work. Thus, policy efforts need to promote resilient care systems in the face of spiraling care needs and demands on women and girls, and such efforts must address how crises affect food and energy shortages as well as forced migration.
The State of Care Services in Sub-Saharan Africa and the ACEI
There are large deficits in the coverage of care policies across sub-Saharan Africa, and all countries are far from realizing universal care provisions. Legislation for maternity leave, ranging from 8 to 17 weeks, exists in 23 African states.6 A few countries offer paid paternity leaves, but they are considerably shorter and range from 1 day to 10 days. There is a distinct lack of socialized childcare, elder care, and care for people living with disability; only a few countries regulate private provision of care in these areas. Socialized health care is also generally lacking and inadequate in size and accessibility. Notably, Kenya has recently set precedence by being the first country in the region to start work on a comprehensive care policy, though many countries do have legislation that addresses specific aspects of care. ACEI is a tool developed by the African Women’s Development and Communication Network (FEMNET) to measure social recognition and state support for care work in Africa. The index is composed of 10 basic metrics related to legislation, policy, and government expenditure. They are maternity and paternity leave, socialized childcare, socialized care for the elderly, socialized care for people living with disability, socialized health care, socialized food production, COVID care measures, domestic worker protection, care grants and subsidies, and family care leave. The index assigns a score out of 30, and a score of 18 and above is considered a passing grade. FEMNET analyzed and assigned a measure of the index in 54 African countries (Valiani 2022). All 54 countries scored less than 8, much below the passing grade. Burkina Faso (7.2), Ethiopia (6.3), Zimbabwe (6.0), South Africa (5.7), Kenya (5.7), and Ghana (5.5) were the top-scoring countries, with index values higher than 5. The Gambia (0.9), Nigeria (0.9), and Eritrea (0.3) were the lowest-scoring countries, with index values less than 5.
From Better Data to Better Measures of Progress
Care work should be understood contextually because it is deeply influenced by social norms, cultural practices, and historical factors specific to a given society or region. In this section, the authors emphasize the importance of a pan-African feminist framing of care and consider the role of TUSs and qualitative data. This section also discusses the exclusion of care work from GDP and income estimates and the need for reliable and sex-disaggregated data to inform gender-sensitive policies and programs in the region.
A Context-Specific Understanding of Care Work
Economists, feminists, and feminist economists have been discussing care since the 1960s, as highlighted in Ossome and Naidu (2021). Care work is central to human societies and essential for the functioning of families, societies, and economies. Care is defined by interdependence and interconnectedness, given the care needs of a person over a lifetime, from childhood to old age, and given the prevalence of sickness and disabilities. This interconnectedness is similar to the South African ethos of “Ubuntu,” or “togetherness.” Ubuntu highlights that “an authentic individual human being is part of a larger and more significant relational, communal, societal, environmental, and spiritual world” (Mugumbate and Chereni 2020).
Precisely due to this nature of care, it is heavily influenced by social norms that define what is good care, who is the caregiver, and who is the care recipient. Thus, a discussion and understanding of care must acknowledge how culture, religion, and history have contributed to the formation of these norms in the African context. Conceptual understandings of care, especially at a policy level, do not include a pan-African feminist framing, which is unsurprising given that care has not been a policy priority in the region. A growing body of thought and research on care work and the care economy in Africa is highlighting the need to define care for the region that considers more than just childcare, domestic work, and health care. The extended values of Ubuntu that embrace care for informal networks within the community, including extended families and friends and humanitarian work, should be considered. Furthermore, care work could extend to traditions of well-being, such as Indigenous healing practices, environmental protection, and spiritual care.
TUSs constitute a key source of quantitative data on unpaid care work. Although difficulties in implementing TUSs have been briefly discussed, their effectiveness in the African context must be further interrogated. For instance, what qualifies as a “household”? The answer is important because this unit is used to link the number of dependents and amount of care work needed. These contextual considerations must be balanced with concerns for international comparability. Much can be gained by conducting TUSs that are at least regionally harmonized— something that has not been achieved among the few such surveys that have been conducted so far. Furthermore, while TUSs give a quantitative estimate of time invested in unpaid care work, they are insufficient to understand the consequences and patterns that emerge from the observed time-use trends. Documenting real stories of people’s, especially women’s and girls’, lived experience is required to deeply understand the extent of care labor and its value to the household and community. Detailed community studies can also provide a better understanding of the local environments in which unpaid care work takes place (Folbre 2018).
Incorporating Data in National Statistics and Measures of Economic Progress
Unpaid care work generally compensates for a lack of public expenditure on care infrastructure and services. Despite its substantial magnitude and contribution to the economy, unpaid care work is excluded from the measurement of GDP, the main indicator of national income. Although GDP is often used as an indicator of development, it underestimates overall economic activity and undervalues social well-being. Figure 17.5 presents ILO estimates (Addati and others 2018) for the value of unpaid care work as a percentage of GDP for nine sub-Saharan African countries. These estimates are calculated by assigning a monetary value to time spent on unpaid care work by costing time based on minimum wages in the country, known as the opportunity cost approach. Women’s unpaid care work ranges from 8.6 percent in Madagascar to 3 percent in Mauritius, and men’s contribution ranges from 2.5 percent in South Africa to 0.6 percent in Mali. Although there are concerns that such estimates may be imprecise, they provide at least a lower bound to the economic value of unpaid care work. These concerns also overlook the reality that despite its considerable contribution, unpaid care work is currently valued at zero.
Value of Unpaid Care Work as a Percentage of GDP, US Dollar PPP 2011, by Gender and Country
(Percent of GDP)
Source: Addati and others 2018.Note: Refer to Annex 17.1 for survey year and characteristics. PPP = purchasing power parity.Another important consideration that has received less attention is valuation at the household level. Unpaid care work is not accounted for in household income or consumption estimates (Folbre 2015). Market-centric discussions about women’s labor supply and labor market participation fail to recognize that unpaid care work is an essential complement to market income. Thus, market-based income measures ignore the opportunity cost of reduced time for unpaid care. Investment in time-saving devices and basic infrastructure could significantly improve women’s productivity, increase their participation in paid work, and enhance household living standards. Such payoffs to public investments are understated when nonmarket work is not valued.
Lack of reliable and sex-disaggregated data on unpaid care work is a major barrier to gender-sensitive policy and programming. Efforts across the world and especially in sub-Saharan Africa still have a long way to go. Although there are some general trends in unpaid care work, there is considerable heterogeneity in the state of the care economy across nations. Thus, a more localized and contextual understanding of unpaid care work and care needs is needed. Such efforts are also important for tracking overall progress toward the care agenda at the national and regional levels and for sharing learnings across the region.
Conclusion
Women and girls play a significant role in providing care services across sub-Saharan Africa, in both an unpaid and a paid capacity. Care responsibilities have a negative impact on the ability of women to participate in the economy; form a barrier to their social, learning, and leadership opportunities; and affect their well-being and social status.
Most care services are provided by the family or household in an unpaid capacity, while paid care workers deliver a smaller, but important, proportion of care services. Women in sub-Saharan Africa spend more time on unpaid care work than do men, which leads to time poverty for employed women as well as gender gaps in labor force participation and time spent on paid work. Even as women enter the labor force, their unpaid care work responsibilities do not reduce proportionately. Thus, employed women work a “double shift”—one at work and one at home. Women from varied socioeconomic backgrounds have varying responsibilities for care work, and gender gaps in time use are not uniform. Hence, policymakers must employ an intersectional approach when devising care policies and care infrastructure. Unfortunately, any understanding of unpaid care work in sub-Saharan Africa is severely limited by data unavailability. TUSs are the most important source of data on unpaid care work, and few countries in the region have conducted a TUS in the past three decades.
Care jobs, especially paid domestic work, are a big source of employment for women. The paid care workforce is very small in sub-Saharan Africa and suggests deficiencies in care service provisions. Women’s care jobs, on average, are characterized by low pay, informal contracts, and difficult and unsafe working conditions. Most of these jobs are domestic work. The role of social norms in observed gender gaps cannot be overstated. Gender stereotypes of unpaid care work and the social association of women’s “natural” inclination toward caring explain to a great extent the high level of feminization prevalent in paid care employment.
Policymakers first need to recognize the care agenda as an important policy priority. Universal provision of quality and accessible care services is still far from reality on the continent. Public investment in social care and physical rural infrastructure is required to reduce time spent on unpaid care work. Redistributing care work between men and women and between social actors—households, markets, the state, and the community—is also an important part of the care agenda. Policies must focus on adequately rewarding paid care work and promoting representation of paid care workers through collective bargaining and social dialogue.
Care work must be understood in a context-specific manner—one that considers social norms and the extended values of Ubuntu. Because unpaid care work is excluded from the measurement of GDP, as such, GDP underestimates overall economic activity and undervalues social well-being. Efforts to collect reliable and sex-disaggregated data on care work, as well as including such data in national statistics, are necessary for tracking progress at the national and regional levels. TUSs are a key source of quantitative data on unpaid care work, but their implementation in sub-Saharan Africa must be carefully examined to balance contextual considerations with concerns for international comparability. A key priority for the care agenda is to strengthen the production and dissemination of data and statistics on care work and care-related policies.
Annex 17.1
Time-Use Survey Characteristics, by Country
Time-Use Survey Characteristics, by Country
| Country | Year | Period | Type of Survey | Sample Size | Survey Instrument | Mode of Data Collection |
|---|---|---|---|---|---|---|
| Benin | 2015 | 1 month | Module of household survey | 13,026 individuals | One diary | Interview |
| Cameroon | 2014 | 1 month | Module of household survey | 4,988 households | One diary | Interview |
| Cabo Verde | 2012 | 3 months | Module of household survey | 3,390 households | One diary | Interview |
| Ethiopia | 2013 | 1 month | Stand-alone | 52,262 individuals | One diary | Interview |
| Ghana | 2009 | 2 months | Stand-alone | 9,297 individuals | One diary | Interview |
| Madagascar | 2001 | 2 months | Stand-alone, sub sample of household survey | 7,749 individuals | One diary | Interview |
| Mali | 208 | 2 months | Stand-alone | 2,249 individuals | One diary | Interview |
| Mauritius | 2003 | 2 months | Module of household survey | 6,480 households | One diary | Interview |
| South Africa | 2010 | 3 months | Stand-alone | 30,897 individuals | One diary | Interview |
| Tanzania | 2014 | 4 quarters | Module of household survey | 10,553 individuals | One diary | Interview |
Time-Use Survey Characteristics, by Country
| Country | Year | Period | Type of Survey | Sample Size | Survey Instrument | Mode of Data Collection |
|---|---|---|---|---|---|---|
| Benin | 2015 | 1 month | Module of household survey | 13,026 individuals | One diary | Interview |
| Cameroon | 2014 | 1 month | Module of household survey | 4,988 households | One diary | Interview |
| Cabo Verde | 2012 | 3 months | Module of household survey | 3,390 households | One diary | Interview |
| Ethiopia | 2013 | 1 month | Stand-alone | 52,262 individuals | One diary | Interview |
| Ghana | 2009 | 2 months | Stand-alone | 9,297 individuals | One diary | Interview |
| Madagascar | 2001 | 2 months | Stand-alone, sub sample of household survey | 7,749 individuals | One diary | Interview |
| Mali | 208 | 2 months | Stand-alone | 2,249 individuals | One diary | Interview |
| Mauritius | 2003 | 2 months | Module of household survey | 6,480 households | One diary | Interview |
| South Africa | 2010 | 3 months | Stand-alone | 30,897 individuals | One diary | Interview |
| Tanzania | 2014 | 4 quarters | Module of household survey | 10,553 individuals | One diary | Interview |
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The ILO refers to own-use production work as “activities performed to produce goods or provide services intended for final use by the producer, their household and/or family” (ILO 2023).
In this subsection the authors calculate the regional averages for time use by using weights according to country population; however, readers should be careful with these estimates because the authors use data from only 10 countries in the region: Ethiopia, Mauritius, Mali, Tanzania, South Africa, Madagascar, Cabo Verde, Benin, Ghana, and Cameroon.
The survey in Cabo Verde was conducted by asking respondents stylized questions about their activities, not including paid work. Thus, one cannot reconstitute the complete schedule of an individual’s day.
Although several understandings and definitions of the term time poverty exist, the authors here conceptually use it to mean “the potential failure of individuals to fulfill their labor commitments while simultaneously meeting some minimum needs of personal maintenance” (Zacharias 2023).
Botswana, Ethiopia, Kenya, Malawi, Mozambique, Namibia, Rwanda, South Africa, and Uganda.
Algeria, Angola, Benin, Botswana, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Republic of Congo, Democratic Republic of the Congo, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, Gabon, The Gambia, and Ghana.
