Learn from the past, prepare for the future

By Roman Hoffmann, Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/ÖAW and WU), Vienna Institute of Demography, Austrian Academy of Sciences

Flooded street in Meycauayan, Bulacan, Philippines (credit: Kasagana-Ka Development Center Inc., 2016 )

Floods, droughts, and tropical storms have significantly increased, both in frequency and intensity in recent years. The burden of these events—both human and economic—falls in large part on low and middle-income countries with high exposure, such as coastal and island nations. In a recent study, with IIASA researcher Raya Muttarak, we found that education significantly contributes to increasing disaster resilience among poor households in the Philippines and Thailand, two countries which are frequently affected by natural calamities.

In these countries, public disaster risk reduction is important, yet public measures, such as investments in structural mitigation for large buildings or infrastructure, implementation of early warning systems, or planned evacuation routes and shelters, may not be enough to sufficiently protect communities from the devastating impacts of natural calamities. In addition, the undertaking of individual preparedness measures by households, such as stockpiling of food and water, strengthening of house structures, and having a family emergency plan, is crucial. Yet, even in areas which are heavily exposed to disasters, people often do not take any precautionary measures against environmental threats.

How people can be motivated to take precautionary action has been a fundamental question in the field of risk analysis. In the new study, which was based on face-to-face interviews in both Thailand and the Philippines, we found that prior disaster experience, which is influenced by geographical location of the home, is one of the key predictors of disaster preparedness. For those who were affected by a disaster in the recent past, education does not seem to play a significant role—they have already learned by experience.  However, among those who had not previously been affected, educational attainment becomes a key determinant. Even without having experienced a disaster, the educated are more likely to make preparations. In fact, educated people who haven’t experienced a disaster have preparedness levels that are as high as those of households who were only recently affected. Since education improves abstract reasoning and abstraction skills, highly educated individuals may not need to experience a disaster to understand that they can be devastating. This suggests that education, as a channel through which individuals can learn about disaster risks and preventive strategies, may effectively serve as a substitute for (often harmful) disaster experiences as a main trigger of preparedness actions.

In additional analyses, we investigated through which channels education promotes disaster preparedness by looking at the relationship between education and different mediating factors such as income, social capital and risk perception, which are likely to influence preparedness actions. We found that how education promotes disaster preparedness is highly context-specific. In Thailand, we found that the highly educated have higher perceptions of disaster risks that can occur in a community as well as higher social capital (measured by engagement in community activities) which in turn increase disaster resilience. In the Philippines, on the other hand, it appears that none of the studied mediating factors explain the effect of education on preparedness behavior.

Emergency shelter, San Mateo, Rizal, Philippines (credit: Kasagana-Ka Development Center Inc., 2013 )

Certainly, it remains important for national governments to invest in disaster risk reduction measures such as early warning systems or evacuation centers. However, our study suggests that public funding in universal education will also benefit precautionary behavior at the personal and household level. In line with recent efforts of the UN to promote education for sustainable development, our study provides solid empirical evidence confirming the important role of education in building disaster resilience in low and middle-income countries.

Reference
Hoffmann, R. & Muttarak, R (2017). Learn from the past, prepare for the future: Impacts of education and experience on disaster preparedness in the Philippines and Thailand. World Development  [doi:10.1016/j.worlddev.2017.02.016]

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.

Counting the Nepalese

By Samir KC, IIASA World Population Program

In 2011, the last decadal census of Nepal counted more than 26.5 million people, plus about 2 million “absentee” Nepalese working abroad. The census revealed a population that is on the move, a rapidly declining number of births, and a high degree of population heterogeneity between the different areas of Nepal. The increasing complexity in the demographic dynamics is making it difficult for Nepal’s government to plan future policies and allocate budgets. That’s why at IIASA in collaboration with Ministry of Health of Nepal, we recently projected the Nepalese population up to 2031 by age and sex for 75 districts as well as more than 4000 villages and municipalities.

Passengers on a bus in Nepal. The country is seeing large amounts of migration both within and outside of the country. ©AusAID

Our projections show that the population of Nepal will continue to increase, albeit at a slow rate from, 26.5 million today to 34.2 million in 2031, and the age structure will continue to grow older. We found that demographic behaviors differ largely by geographic area within Nepal, and highly correlates with the inequalities in terms of development and opportunities. For example, the fertility level in the Mid-Western Hills and Mountain region were very high compared to the rest of the country.

Since 1959, Nepal has had an aggressive but non-mandatory family planning policy with a message to limit family size to two children, but this policy will be soon ending as the overall fertility is approaching the benchmark in most parts of the country. Our study projects that the number of children born, which has been declining in the past 10-15 years, will stabilize with some fluctuation due to larger cohort of women entering the reproductive ages. In the past, the declining number of births  lowered the burden in universalizing health coverage. The study suggests that now the government should channel its resources where needed and the nationwide focus should be more on improving the quality of reproductive services rather than telling people how many children they should have.

A stream of migration
Our analysis shows that for Nepal, the future population dynamics are likely to be influenced in large part by migration, both within and outside of the country. We found that especially in the hill and mountain districts of Nepal, depopulation is occurring as people move away. Because of the Maoist conflict during 1996-2006 and its impact on all aspects of life, young Nepali males began leaving their homes to find safer areas and better employment opportunities, often in Arab and Southeast Asian countries. This in turn might have affected the fertility rates as well as increased internal migration of the dependents (of the migrants made possible by the flow of remittance) from less developed to more developed areas within Nepal.

In recent times, women have joined the migration stream, and are likely to be a major force in lowering the fertility rate in Nepal. If the trend continues, a large part of the mountains and hills is likely to depopulate and the political and socioeconomic consequences of such phenomenon should be studied.

Projected population change in Nepal in 2031 compared to 2011. ©Samir KC & Markus Speringer

Our projections show that the country should expect a huge number of this absentee population to return. The young men and women in their 20s and 30s who have left the country to work in Arab and Asian countries will have to return in their 40s and 50s due to strict rules regulating labor migration in these countries, the labor intensive jobs might not suit their age, and to finally reunite with the family back home. They could be forced to return even sooner if the economic situation in these countries is adversely affected by regional or global recession or conflict, price of oil etc. However, questions remain about how the return process will unfold, where people they return to, and what its impact on the society and the nation would be.

We think that the data and the population model, and the projection that we developed for Nepal could be very useful in many ways, for example in population, environment, economics, social transformation, sustainable development, and other areas. However, we need more data and projections and the possibility to run alternative scenarios, and to do this, demographers, population experts, and governmental institutions should collaborate. One such collaborative initiative is currently underway at the Shanghai University, where I have recently started to develop such a model in 11 countries in Asia, including Nepal. Once the base population model is ready, adding further layers representing the wellbeing of the population will be the next step.

Reference
KC S, Speringer M, Thapa A, & Khanal MN (2016). Projecting Nepal’s Demographic Future- How to deal with spatial and demographic heterogeneity. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-16-021 http://pure.iiasa.ac.at/14029/

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.

What you probably don’t know about higher education in sub-Saharan Africa

By Anne Goujon, IIASA World Population Program

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.

A 2015 graduation ceremony for the Open University of Sudan. ©Hamid Abdulsalam, UNAMID via Flickr

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.

Students in lecture room at St. Augustine University of Tanzania © Max Haller and Bernadette Mueller Kmet 2009

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.

Interview: Defining the future(s)

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.

Researchers use scenarios to map out a range of possible future developments in the socioeocomic factors that influence climate change. © Salvatore Vastano via Flickr

Researchers use scenarios to map out a range of possible future developments in the socioeocomic factors that influence climate change. © Salvatore Vastano via Flickr

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.

Schoolchildren in Indonesia: Population variables like education have big impacts on greenhouse gas emissions and vulnerability to climate change. © Asian Development Bank

Schoolchildren in Indonesia: Population variables like education have big impacts on greenhouse gas emissions and vulnerability to climate change. © Asian Development Bank

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.

More information

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/

Riahi K, van Vuuren DP, Kriegler E, et al. (2016). The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environmental Change. http://pure.iiasa.ac.at/13280/

This article gives the views of the interviewee, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Why are the refugees who came to Austria in 2015 more educated than expected?

By Anne Goujon, IIASA World Population Program

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%.

Students at school in Beirut, Lebanon. Two-thirds of the students at the school are Lebanese and one-third of the students are Syrian. Photo © Dominic Chavez/World Bank

Students at school in Beirut, Lebanon. Two-thirds of the students at the school are Lebanese and one-third of the students are Syrian. Photo © Dominic Chavez | World Bank

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.

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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.