SHAPING THE FUTURE HOW CHANGING DEMOGRAPHICS CAN POWER HUMAN DEVELOPMENT

living in the community, with some
level of independence, rather than in
residential care.
77. Yuen 2015.
78. Clapham 2015.
79. Yuen 2015.
80. UN DESA 2011; WHO 2007b.
81. Global City Indicators Facility 2013.
82. The Economist 2013.
83. Verena 2012.
84. World Bank 2016.
85. UNDP 2015a.
86. UN DESA 2011.
87. Bouman et al. 2015.
88. Marsh 2012.
89. United Nations 2013b.
90. Singapore has an early retirement age
of 55 for both men and women, but it
also has substantial post-retirement
reemployment.
91. Wang 2014.
92. East West Centre 2002.
93. In the United States, labour force
participation increased from 1990 to
2010. Only 12.1 percent of people aged
65 years and older were in the labour
force in 1990; 16.1 percent were in 2010
(Kromer and Howard 2013).
94. United Nations 2013a.
95. Ibid.
96. UNFPA and HelpAge International 2012a.
97. UN DESA 2011.
98. United Nations 2012a.
99. UNFPA and HelpAge International 2012a.
100. UNFPA 2011.
101. World Bank 2016.
102. IMF 2011.
103. Wang 2014.
104. Lu et al. 2013.
105. Langenbrunner and Somonathan 2011.
106. Ibid.
107. Tangcharoensathien et al. 2011.
108. Mason and Lee 2012.
109. Cai and Wang 2014.
110. The ratio is calculated by holding
age-specific public transfer inflows
and outflows constant, while allowing
population age structure to change in
accordance with historical estimates and
projections. The ratio is the projected
tax revenues relative to public transfers
(cash and in kind) as a percentage
of values in 2010. Revenues and
expenditures are projected assuming
that per capita taxes and public transfers/
expenditure by single year of age remain
constant at base-year values. Thus,
values are the result of changes in
population age structure only.
111. The role of the public sector is, in fact,
growing quite rapidly in most countries
of the region. In the Republic of Korea,
for example, social welfare benefits for
the elderly rose sharply over a very short
period.
112. ILO 2014a
113. Naoyuki et al. 2015.
114. East West Center 2000.
115. Stanton 2006.
116. UNDP 2015a.
117. East West Center 2002.
CHAPTER 5
1. UN DESA 2014.
2. United Nations 2012c.
3. Definitions of ‘urban’ areas differ,
including across countries. This
means that data are not always directly
comparable at the regional or global
levels. Government reclassification
of areas as ‘urban’ can also be based
on incentives that do not necessarily
reflect actual conditions. Differences
at the global level are illustrated by a
comparison of data definitions used by
UN DESA (2014) and the Brookings
Institute (2012). Brookings data for
Jakarta include large peri-urban areas,
resulting in a far larger population
than the UN DESA estimates. Many
datasets also fail to include temporary
migrants. This report tries to make
clear the definition of urban used
whenever statistics are presented. For
all population estimates, the report
relies on the UN DESA definition and its
corresponding statistics.
4. UN DESA 2014.
5. Ibid.
6. ADB 2012a.
7. UN DESA 2013a.
8. McKinsey Global Institute 2009.
9. UN-Habitat 2012a.
10. ‘Children’ are defined as people aged 0
to 14; ‘youth’ as between the ages of 15
and 24; ‘working-age’ as those aged 15
to 59; and ‘elderly’ as people aged 60
and above. The listed year indicates the
date of the household survey included
in UN DESA 2013b. All surveys are
from 2009 to 2013, except Lao People’s
Democratic Republic (2005). See UN
DESA 2013c.
11. It is also largely true globally. Rural
dependency ratios tend to be higher
than urban dependency ratios across
all regions, and they tend to be highest
in rural areas of the least developed
regions. See Anríquez and Bonomi 2008.
12. GDP data is in constant 2005 US dollars.
13. The year of the baseline data in
Cambodia was 1996.
14. Migration decisions are also not only
about whether or not to migrate, but
also where to go. Potential migrants
face complicated decisions with
many different options and uncertain
consequences. They are often making
these different decisions simultaneously.
15. Deshingkar 2006.
16. For example, a 2005 study found that
domestic remittances contributed
between 20 percent and 50 percent
of the total income of recipient rural
households in China (Cheng and Zhong
2005).
17. Dudwick et al. 2011.
18. Lall et al. 2009.
19. According to Kirsch et al. (2012), the
flood destroyed 55 percent of affected
homes and caused 87 percent of
households to move; lack of electricity
increased from 19 percent to 33
percent; and 88 percent of the affected
population reported a loss of income.
After six months, most people had not
recovered their prior standard of living.
Rural households were more commonly
impacted and slower to recover.
20. For examples, see de Haan and Rogaly
2002, Gardner and Osella 2003, and
Shah 2006.
21. Cities are not immune from
discrimination, including for newly arrived
migrants. But this does not discount the
lure of cities as an escape for many from
the constraints of rural areas.
22. For example, a survey in China found
the attractions of city life as among the
primary drivers of rural-urban migration
(Hu 2012).
23. UN-HABITAT 2012b.
24. According to UN-Habitat (2012b),
traditionally lower levels of female ruralurban
migration in South Asia have been
explained by factors such as sociocultural
restrictions on independent
female movement, marriage customs
where couples reside with the husband’s
parents, social norms that encourage
young men to move to the city, and the
lack of employment opportunities for
women in towns and cities. For more on
female migration in South-east Asia, see
Chant and McIlwaine 2009.
25. The World Bank (2013b) found a
large degree of overlap between a
country’s level of agglomeration and
its income classification. Most lowincome
countries are low-agglomeration
countries and most advanced economies
are high-agglomeration economies.
26. McKinsey Global Institute 2012.
27. Bangkok, for example, is home to less
than 20 percent of Thai citizens but
202