SHAPING THE FUTURE HOW CHANGING DEMOGRAPHICS CAN POWER HUMAN DEVELOPMENT

End Notes
CHAPTER 1
1. UNFPA 2014b.
2. The term ‘demographic dividend’ usually
refers to the potential economic growth
resulting from a change in population
age structure. In this report, the term
refers not only to potential economic
growth, but also to potential human
development progress.
3. UNDP 2015a.
4. Annex Table 2.
5. Human Development Index values have
not been calculated for nine Asia-Pacific
countries and territories, namely the
Cook Islands; the Democratic People’s
Republic of Korea; Macao, China (SAR);
Marshal Islands; Nauru; Niue; Taiwan
Province of China; Tokelau and Tuvalu.
6. Annex Table 1.
7. Ibid.
8. Ibid.
9. Ibid.
10. Ibid.
11. Annex Table 3.
12. Ibid.
13. Annex Table 4.
14. UNDP 2014.
15. Annex Table 5.
16. The demographic data in this report are
per the World Population Prospects
projections, 2015 revisions (UN DESA
2015a). Asia-Pacific in the report refers
only to East Asia, South-east Asia, South
Asia and Oceania. It does not include
Central Asia, North Asia and West Asia.
Please see the Readers Guide for a
complete list of countries, and the Annex
Tables for country data.
17. World Bank 2015a.
18. The population projections used in this
report are based on the medium-variant
of United Nations population projections.
19. Annex Table 7.
20. The window of demographic opportunity
is the time when the proportion of the
population aged 0 to 14 is below 30
percent, and the proportion aged 65-
plus is below 15 percent (United Nations
2004).
21. In 2100, four out of five people in the
region will be 15 years of age or older
and 28 percent will be 60 years of age or
older.
22. Annex Table 9.
23. Ibid.
24. UN DESA 2015a.
25. Annex Table 9.
26. The common indicator of fertility is the
total fertility rate, which expresses the
number of births that can be expected
to occur for a typical woman in a given
society during her childbearing years.
The total fertility rate and crude birth rate
are especially influential in determining
the number of children in a country.
27. IMF 2015 and World Bank 2015 use a
similar typology for grouping countries
on the basis of demographic variables.
28. Annex Table 8.
29. Government of India 2012; Hunter 2012.
30. Andhra Pradesh, Tamil Nadu, Kerala,
Karnataka, Goa, Punjab, Himachal
Pradesh, Jammu and Kashmir,
Maharashtra, West Bengal, Sikkim,
Tripura and the union territories.
31. Annex Table 8.
32. Bloom and Williamson 1998.
33. UN DESA 2012.
34. Ibid.
35. Afghanistan, Bhutan, Democratic
People’s Republic of Korea, Fiji, Kiribati,
Lao People’s Democratic Republic,
Micronesia, Myanmar, Nepal, India,
Mongolia, Pakistan, Papua New Guinea,
Philippines, Solomon Islands and Timor-
Leste.
36. Annex Table 8.
37. Feeney and Mason 1997; Bloom and
Williamson 1998.
38. UN DESA 2015a.
39. Migration stock data refer to the number
of people living in a country other than
the one in which they were born at a
given point in time.
40. Sijapati 2015.
41. IOM 2013.
42. Castles et al. 2012.
43. IOM 2013.
44. Castles et al. 2012.
45. OECD 2012a.
46. The demographic dividend occurs from
‘accounting’ and ‘behavioural’ effects.
One accounting effect is the swelling
of the working-age population after a
baby boom. Another is the fact that the
‘working age’ coincides with the prime
years for savings. Behavioural effects
include the rise in women’s workforce
activity as fertility declines; faster
urbanization as people move from rural
to urban areas for improved education
and employment opportunities; the
boost to savings and productivity as
people work harder and save more due
to the possibility of a longer retired
life; and the use of human and physical
capital, infrastructure and technological
innovation.
47. Bloom and Williamson 1998; Bloom et
al. 2007; Lee et al. 2000; Lee and Mason
2006.
48. Becker and Barro 1988; Lee and Mason
2010; Prettner and Prskawetz 2010.
49. See Coale and Hoover 1958. The study
stressed three demographic factors
affecting economic development. First,
there is the age dependency effect
as rapid population growth creates
a worsening dependency ratio that
leads to a dip in the savings rate for
people in their early 30s due to the high
consumption needs of people with young
families. Second, there is a resource
diversion effect as high population
growth leads to a large amount of
money spent by the government on
social sectors rather than on productive
growth-oriented sectors. Third, a
‘capital-shallowing’ effect occurs as rapid
population growth leads to a fall in the
ratio of capital to labour. See also Bloom
and Freeman 1988; Bloom et al. 2003.
50. Bloom and Williamson 1998.
51. Wang 2011.
52. IMF 2011.
53. Drummond et al. 2014.
54. UNDP 2015a.
55. For a detailed description of the model,
see Mason 2005.
56. Economic growth is measured here by
GDP per equivalent consumer (GDP/N)
rather than the more traditional GDP
per person. Growth of GDP/N is a
better measure of gains in the standard
of living because high-consuming age
groups grew more rapidly than lowconsuming
age groups between 1970
and 2010. Accounting for age structure
changes leads to a downward revision
of economic growth of between 0.1 and
0.2 percentage points, except in Africa,
where the downward revision is only 0.04
percentage points.
57. The effective number of workers uses
age variation in labour force participation,
unemployment, hours worked and
productivity to measure the size of
the work force. The effective number
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