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
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
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.
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.
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
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.
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.
By Sergei Scherbov, IIASA World Population Program (This post was originally published on The Conversation)
The populations of most countries of the world are aging, prompting a deluge of news stories about slower economic growth, reduced labor force participation, looming pension crises, exploding health care costs and the reduced productivity and cognitive functioning of the elderly.
These stories are dire, in part because the most widely used measure of aging – the old-age dependency ratio, which measures the number of older dependents relative to working-age people – was developed a century ago and implies the consequences of aging will be much worse than they are likely to be. On top of that, this ratio is used in political and economic discussions of topics such as health care costs and the pension burden – things it was not designed to address.
Turning 65 in 2016 doesn’t mean the same thing as hitting 65 in 1916. So instead of relying on the old-age dependency ratio to figure out the impact of aging, we propose using a series of new measures that take changes in life expectancy, labor participation and health spending into account. When you take these new realities into account, the picture looks a lot brighter.
How facts from the census questionnaire were tabulated into statistics in 1950. © The U.S. National Archives/Flickr
Our tools to measure aging have aged
The most commonly used measure of population aging is the “old-age dependency ratio,” which is the ratio of the number of people 65 years or older to those 20 to 64.
But, since the old-age dependency ratio was introduced in the early 1900s, most countries have experienced a century of rising life expectancy, and further increases are anticipated.
For instance, in 1914, life expectancy at birth in Sweden was 58.2 years (average for both sexes). By 2014, it had risen to 82.2 years. In 1935, when the U.S Social Security Act was signed into law, 65-year-olds were expected to live 12.7 more years, on average. In 2013, 65 year-olds may expect to live 19.5 years more.
But these changes aren’t reflected in the conventional statistics on aging. Nor is the fact that many people don’t just stop working when they turn 65, and that people are staying healthier for longer.
To get a better sense of what population aging really means today, we decided to develop a new set of measures that take these new realities into account to replace the old-age dependency ratio. And instead of one ratio, we created several ratios to evaluate health care costs, labor force participation and pensions.
Who retires at 65 anymore?
One of these new realities is that the number of people working into their late 60’s and beyond is going up. In 1994, 26.8% of American men aged 65-69 participated in the labor force. That figure climbed to 36.1% in 2014 and is forecast to reach 40% by 2024. And the trend is similar for even older men, with 17% of those aged 75-79 expected to still be working in a decade, up from just 10% in 1994.
Clearly, these older people did not get the message that they were supposed to become old-age dependents when they turned 65.
This isn’t unique to the U.S. Rates like these in many countries have been rising. In the U.K., for instance, the labor force participation rate of 65- to 69-year-old men was 24.2% in 2014, and in Israel it was 50.2%, up from 14.8% and 27.4%, respectively, in 2000. In part this is because older people now often have better cognitive functioning than their counterparts who were born a decade earlier.
So, instead of assuming that people work only from ages 20 to 64 and become old-age dependents when they hit 65, we have computed “economic dependency ratios” that take into account observations and forecasts of labor force participation rates. This tells us how many adults not in the labor force there are for every adult in the labor force, giving us a more accurate picture than using 65 as a cutoff point. We used forecasts produced by the International Labor Organization to figure this out.
The old-age dependency ratio in the U.S. is forecast to increase by 61% from 2013 to 2030. But using our economic dependency ratio, the ratio of adults in the labor force to adults not in the labor force increases by just 3% over that period.
Clearly, doom and gloom stories about U.S. workers having to support so many more non-workers in the future may need to be reconsidered.
Is the health care burden going to be so high?
Another reality is that while health care costs will go up with an older population, they won’t rise as much as traditional forecasts estimate.
Instead of assuming that health care costs rise dramatically on people’s 65th birthdays, as the old-age dependency ratio implicitly does, we have produced an indicator that takes into account the fact that most of the health care costs of the elderly are incurred in their last few years of life. Increasing life expectancy means those final few years happen at ever later ages.
In Japan, for example, when the burden of the health care costs of people aged 65 and up on those 20-64 years old is assessed using only the conventional old-age dependency ratio, that burden is forecast to increase 32% from 2013 to 2030. When we compute health care costs based on whether people are in the last few years of their lives, the burden increases only 14%.
Pension ages are going up
The last reality we considered concerns pensions.
In most OECD countries, the age at which someone can begin collecting a full public pension is rising. In a number of countries, such as Sweden, Norway and Italy, pension payouts are now explicitly linked to life expectancy.
In Germany, the full pension age will rise from 65 to 67 in 2029. In the U.S., it used to be 65, is now 66 and will soon rise to 67.
Instead of assuming that everyone receives a full public pension at age 65, which is what the old-age dependency ratio implicitly does, we have computed a more realistic ratio, called the pension cost dependency ratio, that incorporates a general relationship between increases in life expectancy and the pension age. The pension cost dependency ratio shows how fast the burden of paying public pensions is likely to grow.
For instance, in Germany, the old-age dependency ratio is forecast to rise by 49% from 2013 to 2030, but 65-year-old Germans will not be eligible for a full pension in 2030. Our pension cost dependency ratio increases by 26% over the same period. Instead of indicating that younger Germans will have to pay 49% more to support pensioners in 2030 compared to what they paid in 2013, taking planned increases in the full pension age into account, we see that the increase is 26%.
Pranom Chartyothin, a 72-year-old bus conductor, sells and collects bus tickets in downtown Bangkok, Thailand. Photo Credit: Jorge Silva/Reuters, CC BY
Sixty-five just isn’t that old anymore
In addition to this suite of measures focused on particular aspects of population aging, it is also useful to have a general measure of population aging. We call our general measure of population aging the prospective old-age dependency ratio.
People do not suddenly become old-age dependents on their 65th birthdays. From a population perspective, it makes more sense to classify people as being old when they are getting near the end of their lives. Failing to adjust who is categorized as old based on the changing characteristics of people and their longevity can make aging seem faster than it will be.
In our prospective old-age dependency ratio, we define people as old when they are in age groups where the remaining life expectancy is 15 years or less. As life expectancy increases, this threshold of old age increases.
In the U.K., for instance, the conventional old-age dependency ratio is forecast to increase by 33% by 2030. But when we allow the old-age threshold to change with increasing life expectancy, the resulting ratio increases by just 13 percent.
Populations are aging in many countries, but the conventional old-age dependency ratio makes the impact seem worse than it will be. Fortunately, better measures that do not exaggerate the effects of aging are now just a click away.
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.
By Luis Castro, researcher in the Sustainability NEXUS Research Cluster of the IIASA World Population Program.
The refugee crisis going on across Europe has brought the importance of migration analysis into sharp focus. Policymakers need to know the answers to many questions that require realistic and timely answers, such as:
- What are the demographic impacts of massive immigration in the short, medium, and long term?
- What are the impacts on a population’s age distribution if the immigrants are migrating as family units, especially if they have a cultural tradition of large numbers of children?
- What are the impacts if the immigrants are mainly males of labor-force age?
- Is there a relationship between education level and the propensity to migrate?
For almost 40 years, IIASA has developed analytical tools and system analysis methods to help answer these questions and others. These methods and tools have been used for UN population projections, as well as by many individual countries around the world, but there is still much research to be done on to help us understand the complex dynamics of migration.
Until the end of the last century, migration modeling was given scant attention. A simple explanation for such lack of interest is perhaps the fact that most social, economic, and demographic research was targeted at the national level. Under such circumstances it was generally assumed that populations were “closed” and international migration was not considered. In addition, demographic studies of sub-national areas used the measure of “net migration”—the number of immigrants minus the number of emigrants—even though this simplifies the situation to the point where key information is lost.
In 1977, just after IIASA had completed its first five years of research activity, the institute announced that a key research theme for the future would be human settlements and services. This focused on developing methods for multiregional demography and included analysis and modeling of age specific migration flows was using data from 17 IIASA national member countries as well as Mexico, which was not yet a member. I dedicated five years at IIASA to developing and testing different migration models investigating patterns of age distributions among groups of migrants, see the graph.
This graph shows how the numbers of migrants of different ages vary. Families migrating, for example, cause a peak in numbers at pre-labor force ages.
Demographic studies often view migration as a collection of independent individual movements. Yet it is widely recognized that many migrations undertaken by individuals whose movements are linked to others. For example, children migrating with their parents, wives with their husbands, or grandparents with their grandchildren.
The aim of my early research at IIASA was to identify some of the effects of family dependency on the migration of men and women, and those of different ages. We developed a model that split migration into independent and dependent flows. This work can explain variations in patterns of migration in societies at different stages of development.
The world has drastically changed since the past 25 years or so, and most nations have become more open and dependent on other countries, more regional alliances have appeared. However, international migration will continue to have the utmost priority for policymakers, not only because of the impacts on the receiving countries but also because of the consequences for the countries of origin.
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.
In the 21st century the major global divide runs between knowledge societies and those where access to education is hampered or denied, say population experts Reiner Klingholz and Wolfgang Lutz in a new book. In an interview with campus.de they explain what this means.
Education empowers us to look beyond our own horizon and to consciously choose our lifestyle. Better qualified people are more involved in political decision making processes and foster democratization – this is what your book says. Does this mean in reverse that societies with limited education opportunities are, as a rule, less democratic?
Rainer Klingholz: From antiquity to medieval times, the uneducated masses were dominated by despotic elites. Wherever the first seeds of democracy were observed, for example in ancient Greece or Florence during the Renaissance, at least a certain part of the male population could write and read. They were in a better position to see what was going on and they strived for more influence in decision making. The more educated the population became, the more chance there was for democracy. In the modern world, we see a clear statistical association between the education of broad segments of society and a well-functioning democracy, although education is a precondition and not always a guarantee.
There are direct and indirect reasons why education is good for democracy. Education directly fosters the ability to obtain information, express one’s own opinions, engage oneself in discussions and look for compromise, all prerequisites for a lively democracy. Education works indirectly through economic development as it fosters prosperity, and such societies are in a better position to afford the ‘luxury’ of democracy. Even autocratically governed countries, such as Singapore and China, which have invested massively in education and achieved rapid economic growth, can also be seen as moving in the direction of democracy in a long term.
Singapore (home of the aquarium pictured here) and other Asian countries have invested heavily in education, with impressive results. © Goinyk Volodymyr | Dreamstime.com
You say that in a context of global competition countries with low educational standards have lower chances to succeed. Could these countries get out of misery by their own strength or does this problem require a global solution?
Wolfgang Lutz: Looking back in history, we see that many countries have made it without outside assistance. In our book we describe the example of Finland, which was one of the poorest regions of Europe before 1900 and later due to massive educational efforts became not only a winner of PISA test but also one of the most innovative industrial countries. Or, let’s look at Mauritius, which as recently as the 1960s presented a textbook example of a country trapped in the vicious cycle of poverty, population growth, and destruction of the environment. Today, thanks to an early boost in education that was followed by fertility decline and economic growth, it is the most successful country in Africa. Similarly, the rise of the “Asian Tigers” has been induced by massive investment of their own modest means into basic education of the broad layers of population.
In many other countries, mostly in Africa and in South and West Asia, this did not happen. As a consequence, there is still widespread poverty and birth rates have remained high, causing continued rapid population growth and difficulties in finding solutions for existing problems. Under these circumstances, it is not surprising that dissatisfaction results in conflicts which in turn trigger streams of refugees. There are of cause many other reasons for this but lack of education is a root cause.
The most important factor behind decreasing fertility rates is female education. If women complete at least secondary school, they have substantially fewer children, they and their offspring are much healthier, and they become more independent from their husbands, as they are better informed and can obtain their own income. Education is the best and most effective development aid. In order to make this happen, the least developed countries need urgent help from outside. The world cannot wait decades for these countries to later possibly make it on their own. By that time, their population may have multiplied by a factor of 3-5, resulting in higher poverty and possible conflicts. There is good reason why there has been compulsory education and a right to education for all children until the age of 16 for a long time in all developed countries. This must apply equally to all children of the world.
Just a small portion of total development aid expenditures goes into education. Have we still not recognized the problem?
Reiner Klingholz: We have, on paper. The new Sustainable Development Goals (SDGs) of the United Nations postulate exactly this. The problem is that these ambitious education goals are not being implemented. Only 2 to 4 percent of global development aid goes into basic education; this makes it impossible for all children to complete primary school and even less secondary school. Most of the development money goes into big infrastructure projects that satisfy local potentates and promote corruption and exports from the donor countries. Building of a rural school, or education of teachers, in Mali or Pakistan are not attractive in that sense. Since educational efforts only become noticeable in 10-20 years, it is much more attractive for a current president to build a new highway. Despite or perhaps because of this, we point out that investment in basic education is the most important investment for enhancing the ability of people and countries to help themselves and it therefore should become an absolute priority in international development.
In some Arab or African countries there is a youth bulge without adequate occupation or place in the society. What are the long-term consequences of this?
Wolfgang Lutz: The main problem of these countries is that the population grows faster than opportunities are being created, especially job opportunities. Many young people do not see prospects for their lives and at the same time they see through TV or internet that elsewhere people are much better off. Under such conditions, young men in particular have a tendency to become radicalized, or fall victim to religious zealots, who tell that people of different religions are the enemies. This mixture leads to a clash between education cultures that we describe in the book.
Students outside a school in Rwanda © Alangignoux | Dreamstime.com
Who or what impedes education in countries like Pakistan, Egypt, or in Western Africa?
Rainer Klingholz: Until the middle of 20th century, most of those countries were pawns in the hands of colonial powers that did not invest in broad education. They were afraid of a population empowered through mass education. In the majority of these countries with independence, authoritarian governments came to power who pursued the same goal: they wanted to stay in power surrounded by small educated elites and had no intention of empowering their citizens through education. Fortunately, in many of the countries the situation has improved in recent years and younger generations are now better educated than the older ones. But there is a real threat from fundamentalist religious or terroristic groups, such as IS or Boko Haram, that actively fight against modern education. They want to stop the teaching of natural sciences and instead have boys memorize the holy scriptures and exclude the girls from education altogether
What does Martin Luther have to do with your book?
Wolfgang Lutz: Martin Luther was the first person in history who actively and successfully fought for the basic education of all, including girls and the poorest farmers. He wanted every individual to find his/her own way to salvation through being able to read the Bible. To achieve this, Luther had to translate the Bible into a language that people understood. But most of all, he had to do something to enable all people to read themselves. This focus on universal literacy was new in world history and went further than e.g. the rather elitist humanists had gone.
Interestingly, we see today that the protestant countries that first implemented those educational reforms in the course of the next decades and centuries became more economically successful as a consequence. The rise of the Netherlands and Great Britain, the industrial revolution, and the later success of the United States, the improvement of living conditions and declining death rates—all this had as a necessary precondition the education of broad segments of the population that ultimately goes back to the Reformation. Luther himself did not have long-term social and economic consequences in mind. Coming from a medieval culture he personally would have been probably unsettled by the following developments towards modernity.
In your book “Who survives?” you describe different scenarios of the future of humanity to the end of the 21st century depending on investments in education in the near future. Can we only survive current and future crises if we indeed prioritize education?
Rainer Klingholz: At the beginning of the 21st century, humanity faces the biggest challenges in its history. It has to abolish poverty, stop population growth, combat climate change, and sustain peace in a world which at the moment may seem to be falling apart. These problems require the best possible brain power and the empowerment through education of everybody. The alternatives to education are high population growth in the poor countries where uneducated women have much higher birth rates together with many other development problems, which likely result in chaos and possibly conflict.
Wolfgang Lutz: The problem is that education needs time to show its positive effects. We have to wait until children come out of school and become active adults. Education is hence not a quick solution to any of the urgent problems that fill today’s newspapers. But in a long run, there are no alternatives to universal education.
Note: 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.