Less than 6% of the working age population has a post-secondary education in sub-Saharan Africa, according to the Wittgenstein Centre Data Explorer. However, there is a huge diversity of experiences in the region: those countries located in Southern and Western Africa have higher shares of highly educated people compared to those in Eastern and Middle Africa.
The potential for increasing education levels is tremendous as there is a huge demand for higher education, partly driven by rapid population growth. The population in the age of attending higher education—18–23 years—is forecasted to increase by 50% from its 2015 level (110 million) by 2035 (183 million), and will have doubled by 2050 to 235 million. The number of colleges and universities in the region has been burgeoning to fulfill the demand. Those are not always of very good quality, whether they are in the public sector or the private, as most are. While regulatory bodies exist to check whether all education providers meet national and international standards, they are not universal.
The expansion of higher education has led to substantial brain drain to Europe, North America, and Australia, because highly educated find better opportunities there for studying and jobs–and better salaries. Researchers have estimated that in some countries such as Eritrea, Ghana, Kenya, Sierra Leone, Somalia, and Uganda, more than a third of the national high-skilled labor force had migrated to OECD countries in 2000. While remittances that these people send home help compensate and reinforce the education in their countries of origin, they do not compensate for the departed skills and knowledge.
These facts about education in sub-Saharan Africa are well-known to education professionals and researchers in the field. But as we show in a new book Higher Education in Africa: Challenges for Development, Mobility and Cooperation, published in January 2017, there are a lot of other aspects of education in the region that are not so well-known and that could provide interesting avenues for further research.
For instance, you probably did not know that the African Union has a higher education harmonization strategy. The general idea is the same as the Bologna process in Europe: enhance the mobility of students by making higher education systems more compatible and by strengthening the quality assurance mechanisms. One chapter by Emnet Tadesse Woldegiorgis, which looks at the process of harmonization of higher education in Sub-Saharan Africa, shows that it follows in the footsteps of the Bologna process mostly because of the involvement of international donors and of the strong links between African universities and European ones.
Many chapters of the book look at the mobility of more highly educated people between Europe and sub-Saharan Africa. This is the case of a chapter by Julia Boger who interviewed graduates from Germany returning to their countries of origin: Ghana and Cameroon. The experiences of those graduates from the two West African countries are radically different: because mainly of their networks, the Ghanaian graduates face less difficulties in finding a job upon return to their country than the Cameroonians.
The last part of the book looks at some cooperation programs that are in place between the North and South (also between the South and the South). Lorenz Probst and colleagues, in their chapter, report about the challenges in implementing a transdisciplinary course in Africa within the context of the rather compartmentalized sectors of higher education in Africa.
The development of higher education could push forward change and innovation, just as much as capacity building in sub-Saharan Africa where it is direly needed.
Reference Goujon, Anne, Max Haller, and Bernadette Müller Kmet. 2017. Higher Education in Africa: Challenges for Development, Mobility and Cooperation. Newcastle upon Tyne, UK: Cambridge Scholars Publishing.
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
Samir KC is a researcher in the IIASA World Population Program. He worked on the population projections that form the “human core” of the Shared Socioeconomic Pathways (SSPs), a set of scenarios designed for climate change research, but increasingly being applied more broadly to research in sustainability and environmental change.
What are the SSPs? The Shared Socioeconomic Pathways are about the future, how the future could look like under different set of conditions. When we want to talk about the future or we need to think about the future, we always have to do some kind of a projection. Whatever the topic is, even in our personal life, we can use scenarios to map out how things might develop, creating different pathways, which can allow us to better understand how our choices could affect these pathways.
Socioeconomic means the major factors socially as well as economically that can affect future changes on our planet—demographic, socially, and economic. But within this broad umbrella, there are multiple disciplines who work on their own topics and have their own methods and data. If they want to work together they have to match with each other so that output of one work could be the input to another group. That’s why the word shared is there.
The SSPs were developed for the Intergovernmental Panel on Climate Change (IPCC). Why were they needed? For one thing, we just needed to update the data from the earlier generation of emissions scenarios, and define new scenarios. But secondly, the focus changed a bit between the IPCC’s last report and the most recent one, released in 2014. In the new scenarios, the focus is more on challenges to adaptation and mitigation of climate change. These dimensions are harder to incorporate because they depend on a lot of socioeconomic factors.
You worked specifically on the population projections for the SSPs, which were published in 2014. How did this process work? The first thing that we did was to define narratives for each of the SSPs, essentially a story about how the world would look like in the future. This first part is very important. These narratives were based on the current knowledge of science and how the variables are related and interact.
Then for each of the pathways, we had to start defining the variables like population, urbanization, technological change, and economy. Since population is one of the first variables you need in order to calculate other socioeconomic variables, it was the first thing we looked at when turning the narratives into a quantitative projection. Population is needed as a multiplier to calculate demand in the future, for example to calculate how much energy will be required in the future, how much water, and many other things. At the same time when there are adverse effects of climate change, the population determines how many people are impacted as well as who and where. For example the air pollution group who would need population to see how will air pollution affect the population. So population is an important variable.
It was an iterative process—there were lots of calls, involving sometimes 10 or 15 people from many different fields. Whenever we had something to share or something to decide, it was done in this big group. It was a lot of talking and listening to others. That was a very educational for me, because I learned a lot about how people are using population data. It was a very good dialogue—people had sometimes very simple questions but sometimes very interesting questions about population, fertility, mortality, and those kinds of things.
How did your population projections differ from previous demographic data used for climate research? In most climate research, until recently, population was used as a total number. Populations were assumed to be homogenous—everybody the same, the average will represent everyone. We argued that that is not the case, that you need to consider population heterogeneity, not only age and sex, but also education levels. There is a growing body of research showing that these details make a difference.
Still not everybody is using it, but for example, people working on GDP have used it, and hopefully more and more will use these factors in the future. We have shown in the past that knowing the education level of the population can help us make better projections. Having a more educated population has effects on many other socioeconomic measures. For example, more educated societies have higher level of productivity. Education level has also been used to calculate the speed of technological change. In societies where there are highly educated people the advancement in technological change comes faster than otherwise. And these factors are key to understanding humanity’s vulnerability to climate change, our ability to adapt, and our chances to solve the problem.
A lot of your work focuses on what might happen in the future. How do you explain to people the difference between scenarios or projections and predictions? When we make projections about the future, we don’t use the word “prediction.” The chances that such a projection will be wrong are 100%. We can never say exactly what will happen in the future.
It’s important to understand how the narratives were defined, how we defined the scenarios. We cannot guarantee the future, the results, but we can guarantee the quality of what can be done, what we can say now, today about the future. And then there is the idea of uncertainty – we have said something about the future but we haven’t reported any kind of uncertainty there other than reporting ranges of scenarios. This is a big area for future work. It’s difficult to do, and it would be difficult to interpret, but it’s important to consider.
References KC S, Lutz W (2014). The human core of the shared socioeconomic pathways: Population scenarios by age, sex and level of education for all countries to 2100. Global Environmental Change http://pure.iiasa.ac.at/10759/
Since the middle of the 19th century researchers have known that married men and women live longer than the unmarried: it is an inference as stable as a natural law. My colleague at IIASA, Sergey Scherbov and I supported its validity with a study in the 21st century, extending the pattern to encompass cohabiting. We also showed that people who have a partner are healthier than those without.
Across 16 European countries, partnered women aged 50 will outlive single women by 1.4 years on average before reaching age 80. For the men this difference is considerably larger: 4 years. Partnered people also have more years with healthy life (i.e., without disabilities) when compared to the singles: for women this gain is 5 years and for the men it is nearly 8 years. In general, partnership is more beneficial for the men.
What makes living with a partner so important for a longer life and better health? An important advantage of living with a partner is that the partner can provide emotional, economic, social, and physical support in everyday life and in case of illness. This advantage is known as the protective effect of marriage. Over a period of 160 years causes of death have changed and the conditions of life and health have changed, yet the protective effect of marriage remains. In contemporary living arrangements cohabitation frequently replaces marriage but it has the same protective effect.
We expected single people to lack the protective effect of marriage, in other words, singles are expected to have poorer health. In addition, each one of the single sub-groups (i.e., never married, widowed, and divorced/separated) is subject to different reasons for poorer health than partnered people. For example, the never-married might have a disability that prevents them from finding a partner; widowed people are likely to lead the lifestyle of their late partner (diet, exercise, smoking, economic conditions, etc.) and are therefore more likely to suffer from the same disease that ended their partner’s life; divorces can be due to increased disability in either one of the partners.
We carried out international comparisons among the 16 European countries and found substantial diversity between countries in Western and in Eastern Europe. Populations in Eastern Europe have shorter lives, shorter healthy lives, and a longer time spent with disabilities compared to those in Western Europe. These differences are greater for single people than for partnered people; for example single men in Slovakia live only 7.4 years free of disabilities in the interval from 50 to 80 years, while in Sweden they enjoy nearly 20 years of healthy life.
The Nordic countries are leading with respect to length of healthy life and small differences between partnered and single people. The protective effect of marriage or cohabitation seems to be small in these countries. We believe this is due to the strong social policies that prevail in these countries.
What can we expect for the future? Statistical data indicate that the proportion of single people above age 50 and especially of single men increases with time. Hence the proportion of those who experience disabilities and ill-health will rise unless policies are put in place to help relieve these adverse effects.
According to the Displaced Persons in Austria Survey (DIPAS) conducted by a team at the Vienna Institute of Demography and at IIASA, the large number of asylum seekers who came to Austria in the fall of 2015 appeared to possess levels of education that are higher than the average level in their country of origins. Moreover, the share of displaced persons from Syria and Iraq with a higher education is close to that of the Austrian population – around 30%.
This seemed surprising to many, judging from the number of critical and even aggressive comments that were posted online after the results of this study appeared in PLoS ONE in September and were covered by the press, mostly in Austria. Some of these comments even suggested that people were lying, and/or that the scientists were “do-gooders” covering up the truth.
However, there are several logical reasons for these findings, none of them having anything to do with deceit. The main reason why we know the study participants were not lying is that they had no incentive to lie. They were informed about the purpose of the survey and the fact that there was nothing at stake for them besides contributing to knowledge on the refugee population. Second, their levels of education matched very well with other information they gave, for instance their previous employment, so that if lying, they were uncannily consistent. Moreover, they were rarely alone when taking the questionnaire and it is difficult for a father or mother to lie for instance in front of their children. So we tend to believe the 514 displaced persons that answered the questionnaire. But these are not our only reasons:
Not everyone can afford the adventurous trip to Austria. We asked in the survey how much their journey to Austria–mostly through Turkey–cost, and 75% reported more than 2.000 US$ per person, and 30% more than $4.000. Such a sum is not easy to come by in countries where the average salary is low. The group of asylum seekers that fled to Austria was a selected group with a higher income, and consequently more likely to have had better access to education than those who could not afford to move further and were displaced within Syria or in the neighboring countries (Turkey, Lebanon, Jordan).
Furthermore, this is a young population. Most of them are below the age of 45 years, in fact, the mean age of the respondents was 31 years. Therefore they most likely benefited from the improvements in education that were prevalent in recent times before the war started.
What we cannot say is whether the level of education in their home countries is or was equivalent to the level of education in Austria. For example, we cannot say if an engineer in informatics from the Damascus University has the same knowledge and skills as an engineer trained at the Technical University in Vienna. However, studies implemented by the Public Employment Service in Austria show that refugees’ levels of competence and skills are largely in line with their levels of education and/or occupation. Furthermore, people who successfully pursued a higher education are more likely to be willing and interested to learn new things, such as learning a new language, developing additional skills, or retraining for other professions.
Therefore, the displaced persons that came to Austria at the end of 2015 have a high potential for contributing to the economy that should not be ignored.
Reference Buber-Ennser, I., Kohlenberger, J., Rengs, B., Al Zalak, Z., Goujon, A., Striessnig, E., Potančoková, M., Gisser, R., Testa, M.R., Lutz, W. (2016) Human Capital, Values, and Attitudes of Persons Seeking Refuge in Austria in 2015. PLoS ONE 11(9): e0163481. doi:10.1371/journal.pone.0163481
This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.
The world is on the move. Currently, more than 250 million people live outside their countries of birth. Of the moving masses, an estimated 6% are refugees fleeing across borders to more favorable environments. The ongoing European refugee crisis has increased the pressure to reap the benefits from migration while alleviating the burdens of societal movement.
Estimates of directional flows between 123 countries between 2005-2010. Only flows containing at least 50,000 migrants are shown. “The Global Flow of People” (www.global-migration.info) is by Nikola Sander, Guy Abel & Ramon Bauer, and published in Science as “Quantifying global international migration flows” in 2014 (vol. 343: 1520-152).
Concerns were recently raised as to whether granting asylum to refugees—who often make up the most productive parts of their original populations—prevents (re)development in their fractionated home countries? An important consideration absent in these debates are the monetary gifts migrants send to their family members back home.
The World Bank estimates that migrants currently return around 450 billion US Dollars per year to the developing countries they came from, and this number is expected to rise. These monetary remittances have multiple positive impacts, including economic growth. As refugees are primarily younger to middle-aged, their remittances likely pay for their wives and children’s access to medical care and education, or support their parents when pension systems are missing.
Intergenerational monetary transfers are therefore the focus of my recent publication Gifts Without Borders. Contrary to conventional institutionalized sustainable development, remittances grounded in intergenerational care benefit from communication within families. Long-lasting family ties allow direct feedback. People truly care about their loved ones back home and families share their day-to-day experiences honestly. Intergenerational remittances beyond borders are thus a purer and potentially longer-enduring pathway to sustainable development, as these stable funding streams’ impact is more accountable than standard international aid.
Based on World Bank and OECD data covering almost all countries of the world, my forthcoming publication in the book ‘Intergenerational Responsibility in the 21st Century’ highlights that the intergenerational glue of a migrating population helps countries lacking socially responsible and future-oriented public sectors. Rather than blaming asylum-granting countries for removing the labor force from fragile territories, hosting refugees is portrayed as making use of human capital in stable economies, while refugees—at the same time—develop their former homelands by direct monetary contributions in a natural, transparent, and accountable way. In the age of migration, analyzing intergenerational networks and their financial flows is an important, but unexplored, facet of sustainable development. My findings open prospective research avenues on how we can align the economic outcomes of human capital mobility with sustainable development.
Above all, attending the IIASA 2016 Alpbach-Laxenburg Group Retreat at the European Forum Alpbach helped to enhance my understanding of the relationship between migration and intergenerational responsibility. All these endeavors are targeted at contributing to sustainable development in a world on the move.
Taking action on climate change is one top priority of the Sustainable Development Goals (SDGs), especially since its adverse impacts can undermine sustainable development. At the same time, reducing gender inequalities and empowering women and girls is fundamental in making progress across all the goals.
These two issues are also closely linked: in certain circumstances, women are more vulnerable to the effects of climate change than men, for example, due to weaker physical ability, lower socioeconomic status, and greater social, economic and political barriers in coping capacity.
This is why, in recent work, we have been exploring the differential impacts of climate change on subgroups of population such as by gender, age, education, and income. The rising number of households headed by women across the world and, in particular, in southern Africa calls for special attention to their economic welfare. In general female-headed households are more likely to be in poverty. Under the context of the changing climate, it is likely that weather extremes, rainfall variability, and natural disasters associated with climate change will exacerbate economic disadvantages of female-headed households.
Female-headed households are more economically vulnerable to climate-related shocks for three big reasons, which researchers call a “triple burden”. First, persistent gender disparities in the labor market and other productive activities, including limited access to formal credit markets and land contribute to greater economic disadvantage for female-headed households. Second, these households often have a higher total dependency ratio–that is, women take care of a higher proportion of dependent children and the elderly. Third, women who are heads of households with no other adult help have a “double day burden” where they have to fulfil both domestic duties and make money outside the home. That means that female heads face greater time and mobility constraints and may have to work fewer hours or choose lower-paying jobs.
Female-headed households are more economically vulnerable to climate-related shocks for three big reasons, which researchers call a “triple burden”. Photo: Pablo Tosco/Oxfam
Add climatic shocks to an already disadvantaged family, and the livelihood disruption can be a catastrophe. However, there have been very few studies of how female-headed households actually fare in the context of climate change. In our new study published in World Development, we used household survey data from South Africa and local rainfall data over the period 2006-2012 to examine how female-headed households fare economically when facing variation in rainfall. The study provides new empirical evidence on economic welfare of households headed by women following climatic shocks.
The new and unique part of our study is that we are able to control for observed and unobserved characteristics of households using a statistical technique called fixed effects estimation, which enables us to control for the household-specific effects on income. It also lets us account for different income trajectories in households with different demographic compositions. Furthermore, we were able to evaluate the impacts of income shock on economic vulnerability of female-headed households using rainfall variability as an exogenous source of risk. Income loss due to other variables such as death of a household member or losing a job are likely to be endogenously determined by household characteristics, that is, female heads have lower level of education and hence are more likely to fall into unemployment. But because rainfall variation is not connected to household factors, we were able to measure the causal effect of climate variability on incomes, comparing different household types.
Our study shows that female-headed households in South Africa are indeed more vulnerable to climate variability than households headed by two adults, and not just because of the greater economic disadvantages that they start with. Even after controlling for household socioeconomic characteristics, female heads still fare worse when facing economic shocks. This might be due to limited access to family support and protective social networks who can step in to help in time of crisis.
Our analysis also reveals that not all types of female-headed households are vulnerable to rainfall variability. This finding is especially important for designing a policy to reduce vulnerability of female-headed households. Given different routes into female headship, we show that never-married female heads, women with a non-resident spouse (for example, where the husband has moved to work in another region), and widows have greater economic vulnerability to climate variability. The group of female-headed households where the female head has never been married is the largest of these groups. Households with adults of both genders where the female works but the male does not work and households of separated or divorced women are no more vulnerable than male-headed households.
We also found that vulnerability to climate impacts is related to the effect of rainfall on agriculture. We find that female-headed households face greater economic vulnerability only in the districts where rainfall has a large effect on loss in agricultural yields. Regardless of household engagement in agriculture, crop losses in a district can affect food and livelihood security through surges in food prices and shortfalls in local demand.
Although our study focuses on South Africa, the results showing that female-headed households are more vulnerable to climate variability call for particular interventions to their vulnerability in the context of climate change. The number of female-headed households is rising, with an exceptionally high proportion in southern African countries (36.3% in Lesotho (2006), 43.9% in Namibia (2013), 47.9% in Swaziland (2007). As climate variation and extremes also increase, policies to reduce vulnerability to climate change need to explicitly consider the plight of this subgroup of population.
Flatø, M., Muttarak, R., & Pelser, A. (2016). Women, weather, and woes: The triangular dynamics of female-headed households, economic vulnerability, and climate variability in South Africa. World Development. doi:10.1016/j.worlddev.2016.08.015
Muttarak, R., Lutz, W., & Jiang, L. (2015). What can demographers contribute to the study of vulnerability? Vienna Yearbook of Population Research, 13, 1–13. doi:10.1553/populationyearbook2015s001
Rosenhouse, S. (1989). Identifying the poor : is “headship” a useful concept? (No. LSM58) (pp. 1–62). Washington, DC: The World Bank. http://documents.worldbank.org/curated/en/1989/07/442370/identifying-poor-headship-useful-concept. Accessed 24 February 2015
Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.