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.
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.
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 recent years the world has been in the grips of the worst refugee crisis since the horrors of WWII. Between January and August 2015 over 44,000 people applied for asylum in Austria alone. While much attention has been focused on immigration and asylum policies, there is a lack of data on the actual people; what are their backgrounds, qualifications, and expectations?
The team—consisting of over 40 researchers, students, and volunteers—is aiming for around 500 interviews with people seeking asylum in Austria, and the survey is carried out in Arabic, Farsi, and English. Zakarya Al Zalak, IIASA researcher in the World Population Program, former director of the Damascus Statistical Technical Institute, and a Syrian himself, speaks to science writer Daisy Brickhill about directing the work.
Why are you carrying out this survey?
We know almost nothing about the refugees as individuals. Who are these people? How much education have they received? What are their qualifications? What are their hopes and values? This kind of information is vital, because it can assist policymakers to design strategies to help these people integrate into Austrian society.
Training for the survey. Photo credit: Judith Kohlenberger
What kind of questions do you ask?
There are six sections to our questionnaire. The first covers demography—things like age, sex, ethnicity, and religion. Even on these basic characteristics there is very little data. The second is about education. How long did they stay in school? What are their qualifications?
For the third section we focus on employment, asking whether they had a job before leaving their native country, and what their profession was. This will help assess the skills these people can bring to the Austria, and where they might be able to work. This is particularly important for integration, as it can help policymakers see where they might fit in to Austria’s workforce.
We use all kinds of questions and measures to get the most information possible. For example, when asking about health, we test the participants’ hand-grip strength. Previous IIASA research has shown that this is related to markers of aging, future disability, cognitive decline, and the ability to recover from hospital stays.
In the fifth section we ask about family. This is important because although many refugees are men travelling alone, they may be planning to bring their family once they have made a life for themselves.
You mentioned attitudes and values, how do you find out about these things with a simple questionnaire?
In the last section of the questionnaire we use several different approaches to explore attitudes. We ask whether they would mind if their children were taught about other religions at school, for instance. We also ask about their views on abortion and gender equality, among other things.
What are the next steps?
We finish sampling soon, so we are hoping to publish the preliminary results in January 2016. However, the most important part of the work is in the next stage. We have asked for participants’ contact details, and our plan is that we will reconnect with these people after some time, eight or nine months, say. At that point we can ask more about how they are finding life in Austria, and whether integration is going well. Have they taken a German language course, for example? Do they have work? Have they received training?
If we are unable to reach some people for follow-up there is a possibility of recruiting new participants. Although we will not have the data from the initial survey we can still ask them how long they have been here, and how their integration is going.
It must be difficult seeing your fellow Syrians in such dire straits.
Before coming to Austria, I worked with refugees in my own country. It seems strange to think of now, but at that time there were Iraqi people who had fled to Syria to seek asylum. Now, we are finding people who are “double refugees,” first fleeing to Syria from Iraq and then, as the situation in Syria worsened, from Syria to Austria. It must be an extremely hard journey. I very much hope this work helps policymakers to make things easier for them.
If you live in South Africa and did not complete high school then your chances of committing crime, being caught, and sent to jail are pretty high. This is what we can tell from comparing the education characteristics of the population of inmates in South Africa with that of the population who was not in jail. A recent study that I conducted with a team of African and European researchers in the framework of the Southern African Young Scientists Summer Program confirms some findings from previous research, such as this 2010 study that found that education has a statistically significant effect on crime.
South Africa spends about 8 billion dollars a year on public order and safety. Violence and related injuries are the second primary cause of death in South Africa, and in the last 10 years, the prison population rate has been in a range from 300 to 400 per 100,000 people, one of the highest rates in the world.
South Africa is still plagued with the after-effects of its apartheid history, which enforced sub-standard education for different racial groups, creating a polarized society. The disparity in education between white and other racial clusters actually widened after the fall of the apartheid government. At the same time—and not unrelatedly, as shown by our study—the apparently peaceful transition to a democratic regime was accompanied by a rise of crime and violence, a gauge of the dichotomized South African society and its high levels of social exclusion and marginalization.
Indeed, our analysis of the 2001 census shows that the effect of education on criminal engagement – meaning in this study actually serving time in prison for a crime – differs by race. This suggests that there is an interaction effect between race and education. The negative relationship between being highly educated and the likelihood of being incarcerated is linear for respondents of mixed ethnic origin (or “colored” according to the South African classification), Indians, and to a lesser extent also for Africans. For white respondents, however, the effect of education creates a bell-shaped graph, with the richest and poorest people less likely to be in prison, and the medium levels of education associated with the highest probability to be in prison.
Share of the general and inmate population by level of educational attainment, South Africa, 2001
We also looked at the empirical results from a sample drawn in the Free State province—a crime hot spot – which indicated that a person’s native language, a proxy for race and place of origin, has a statistically significant influence on the likelihood to commit a contact . We also found that the probability of committing contact crimes, including vandalism, threat, assault, and injury, decreased with years of education, while the likelihood of committing economic crimes, including tax fraud, increases with years of education
This research provides another good incentive to invest in education in South Africa, and particularly to insist on all children completing upper secondary education finishing with grade 12. Education statistically significantly decreases the probability of engaging in criminal activity. Hence, it should be included in the National Crime Prevention Strategy, particularly in some targeted provinces within South Africa.