Populations all over the world are getting older. Not only will there be more elderly people alive in the future, but the elderly themselves will be changing. In general, they will be living longer, have better cognitive functioning, and be more educated. Nevertheless, conventional measures of population aging assume the characteristics of the elderly will not be changing. The combination of this static view of the elderly and the dynamics of age structure change produces a misleading picture of how population aging evolved in the past and how it is likely develop in the future.
For the formulation of appropriate public policies and for an informed public discussion of population aging, it is crucial that the most accurate measures are used.
Data accompanying Sanderson WC, S. Scherbov S (2015), Are we overly dependent on conventional dependency ratios? Population and Development Review, 41(4), 687–708.
The figures in Table Re-Aging 3 are all based on data produced by the United Nations for the 2015 volume of World Population Prospects. There figures differ slightly from those in the article because the latter were based on data from the 2012 volume of World Population Prospects. All the data are for both sexes combined.
Table Re-Aging 3 contains projections of (1) economic dependency ratios, 2) health care cost old-age dependency ratios, (3) pension cost dependency ratios, and (4) prospective old age dependency ratios. The figures are for OECD countries from 2013 to 2050.
All the figures in Table Re-Aging 1 and Table Re-Aging 2 are based on data produced by the United Nations for the 2012 volume of World Population Prospects.
Table Re-Aging 1 contains three measures. The first is the old age threshold. This is the age at which remaining life expectancy first falls below 15 years. The prospective proportion old is the proportion of the population at or above the old age threshold. The prospective old age dependency ratio has the number of people at or above the old age threshold in the numerator and the number of people from age 20 to the old age threshold in the denominator.
Table Re-Aging 2 contains the conventional median age and related prospective measures. The conventional median age could differ very slightly from the UN figure because of different interpolation procedures. In order to compute prospective median ages, we have to choose a life table to use as a standard. In the column labelled “Prospective Median Age” the standard is the life table for the region/country in 2010. In the column labelled “Prospective Median Age (Japan standard)” the standard life table is from Japan in 2010. Prospective median age is the age derived from the standard life table where remaining life expectancy is the same as it is at the median age in the indicated year. Because of the way it is constructed, the prospective median age using the country’s life table as a standard is the same in 2010 and the conventional median age.
More details about these measures can be found in these publications:
Sanderson WC & Scherbov S (2015). Are we overly dependent on conventional dependency ratios? Population and Development Review 41 (4): 687-708. DOI:10.1111/j.1728-4457.2015.00091.x.
Sanderson WC & Scherbov S (2015). Faster increases in human life expectancy could lead to slower population aging. PLoS ONE 10 (4): e0121922. DOI:10.1371/journal.pone.0121922.
Sanderson WC & Scherbov S (2014). Measuring the speed of aging across population subgroups. PLoS ONE 9 (5): e96289. DOI:10.1371/journal.pone.0096289.
Sanderson WC & Scherbov S (2013). The characteristics approach to the measurement of population aging. Population and Development Review 39 (4): 673-685. DOI:10.1111/j.1728-4457.2013.00633.x.
Lutz W, Sanderson WC, & Scherbov S (2008). The coming acceleration of global population ageing. Nature 451 (7179): 716-719. DOI:10.1038/nature06516.
Sanderson WC & Scherbov S (2005). Average remaining lifetimes can increase as human populations age. Nature 435 (7043): 811-813. DOI:10.1038/nature03593.
Last edited: 08 May 2017
European Research Council Grant no ERC2012-AdG 323947-Re-Ageing
Demographic Data Sheets
European and Russian Data Sheet
Arpino B, Bordone V, & Scherbov S (2017). Smoking, Education and the Ability to Predict Own Survival Probabilities: An Observational Study on US Data. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-17-012
International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313