March 2015 Faculty Spotlight

You teach a course on the demography of aging. How do you believe the challenges of aging have evolved over the years? How will these challenges evolve in the future?
The demographic transition (which refers to long term reductions in fertility and mortality) results in a population age structure shifting substantially toward older ages. World total fertility stands at 2.6 children per woman in 2005–2010, compared with 4.9 in 1950–1955. It is projected to drop further to 2.0 children per woman in 2045–2050. This is below the replacement level fertility which is about 2.1 children for a more developed country and somewhat greater for a country whose population is subject to higher mortality. In the meantime, global life expectancy has risen by nearly 21 years from 1950s. It is currently 67.6 years and is projected to rise another 8 years by 2045–2050. The “oldest old” population, those 80 years and older, are expected to grow rapidly in the developed world. In Japan, for instance, 1 out of 16 people is age 80 or over and in 40 years, 1 in every 6 people is expected to be part of the “oldest old.” On the other hand, in developing countries like India, Indonesia, Pakistan, and Nigeria, less than 1 in 100 are classified among the “oldest old” and they are not expected to exceed 1 in 25 by 2050. The demographic transition is occurring both in developing and developed countries, but at different pace and different levels.

Initially, declining fertility has been a net positive for countries like China. The dependency ratio, which is used to measure the burden of support for children and the aged to which the working-age population is subject to, declined fast. Rapid growth in the working-age population that is not accompanied by similar growth of the more youthful population could potentially have positive effects on economic growth, such as increases in income per capita and tax revenues. This is what demographers call “the demographic dividend.” Whereas the more developed regions and parts of East Asia have reaped this benefit, the process in most developing countries started later and has been less dramatic.

However, as life expectancy rises, share of older people in the population go up and the dependency ratio once again goes up with a larger share of old age dependents and a smaller share of younger children. This brings a new challenge to countries’ social safety net systems as old age pension costs go up as well as more people with long term sicknesses increase the burden on disability programs. An individual who claims pension benefits at the earliest eligible age and who dies at the age indicated by his or her country’s life expectancy at birth will enjoy such benefits for 23.0 years in China, 22.7 years in Japan, 19.0 years in Brazil, 17.2 years in the United States, 15.7 years in Indonesia, 13.5 years in India, and 11.3 years in Pakistan. In countries such as the United States, where the pension system is of the pay-as-you-go variety, population aging can present significant problems.

A shifting demographic landscape may require individuals to rethink social and financial decisions, such as labor force participation, saving and investment, marriage, education, childbearing, and living arrangements, in the context of smaller families and longer lifetimes. It will also require governments to rethink financing of social safety nets, shifting of government spending perhaps from younger to older population, as well as introducing policies to extend the working age years of the population via more inclusive labor market to encourage the older and disabled population to continue participating in the labor force.

Do you have any upcoming research projects? What do they involve and what do you hope to accomplish?
Yes, I do. I have been working on several different projects using anchoring vignettes to assess differences in self-reported health outcomes. Anchoring vignettes are brief descriptions of hypothetical situations that are utilized in surveys in order to correct otherwise interpersonally incomparable survey responses. In disability context, survey respondents are asked for self-assessments of their own health and work disability along with assessments of other hypothetical individuals described in anchoring vignettes. We use the variation in answers to vignettes in order to correct interpersonal variations in self-assessments that would be otherwise incomparable. I, along with my colleague from Baruch, use the vignettes to compare how health professionals and disability recipients’ rate health limitations such as pain, cardiovascular health, and depression as severity of disability compared to general public.

In another project, we investigate whether the disability differentials between European countries and the United States reflect differences in actual work limitations or differences in reporting styles across countries. In both scenarios, I believe that differences in reporting styles have important effects on assessments of the severity of work limitations. While the two projects apply similar methodology, the findings have different implications. In the first project, if we assume that health professionals (as well as disability recipients) have more knowledge when it comes to assessing health and disability, we can compare the general public and their ratings to them in order to understand where the biases of general public will be towards. Indeed, our findings show that general public is stricter in the assessment of health and disability. In other words, they are less likely to consider a given health problem a severe work limitation. In the second project, we consider differences in countries’ disability policies and how they affect assessments of work limitations. We hypothesize that stricter disability policy in a county will affect public perception of disability in the country as well inducing people to consider only dramatically declining work capacity as a work disability whereas more generous disability policy in a country will move the public perception towards a more inclusive conceptualization of work disability. In fact, our analysis suggests that such a relationship holds. The United States, for instance, has a very strict definition of work disability, in other words, the requirements are really high to be eligible for disability insurance benefits, compared to most European countries. As a consequence, people in the United States consider only very severe cases of worsened health as work disability.

How do you feel students at the School differ from other institutions you’ve worked at in the past?
We have a very diverse student body. Diversity both in terms of cultural backgrounds as well as life experiences provides a very rich learning environment in the classroom. Our students are very good at inferring concepts that I teach as “statistics” to their real life situations on their professional and personal lives as well as for understanding current policy discussions. As a result, I have very lively classes where we go beyond just explaining concepts and teaching formulas to actually understanding how these concepts are used in the real life. It is a great treat for me to observe that what I teach becomes a valuable tool for them in their future careers. I think the main difference between the students here and my past students in previous institutions is that I don’t really need to motivate the students here that “statistics” are a valuable tool for them; they already know that through their past experiences. I don’t need to motivate them to be interested in the concepts; they are already very self-motivated. All I have to do is guide that motivation and enthusiasm to structured and fruitful conversations on these concepts.