Population Aging and the Three Demographic
Dividends in Asia
Naohiro Ogawa, Norma Mansor, Sang-Hyop Lee,
Michael R.M. Abrigo, and Tahir Aris∗

The present study first examines the trends in age structural shifts in selected
Asian economies over the period 1950–2050 and analyzes their impact on
economic growth in terms of the first and second demographic dividends
computed from the system of National Transfer Accounts. Then, using the
National Transfer Accounts, we analyze the effect of the age structural shifts
on the pattern of intergenerational transfers in Japan; the Republic of Korea;
and Taipei,China. A brief comparison of the results reveals that,
in the
next few decades, the latter two are likely to follow in Japan’s footsteps by
increasing public transfers and asset reallocations, and by reducing familial
transfers, particularly among older persons. Next, we consider a newly defined
demographic dividend, which is generated through the use of the untapped work
capacity of healthy older persons and to which we refer as “the silver” or “the
third” demographic dividend. By drawing upon microlevel datasets obtained
from Japan and Malaysia, we calculate the magnitude of the impact of that
dividend on macroeconomic growth in each of the two economies, concluding
that while in Japan the expected effect is substantial, in Malaysia it will take
several decades before the country can enjoy comparable benefits.

Keywords: demographic dividends,
Transfer Accounts, population aging
JEL codes: J11, J14

intergenerational

transfers, National

I. Introduction

In the 20th century, the world population growth rate peaked in the latter
half of the 1960s. Since then, the tempo of growth has been continuously slowing

∗Naohiro Ogawa (corresponding author): Asian Development Bank Institute, University of Tokyo, and
University of Malaya. E-mail: ogawa-naohiro@e.u-tokyo.ac.jp; Norma Mansor: University of Malaya.
E-mail: norma@um.edu.my; Sang-Hyop Lee: University of Hawaii at Manoa, and East-West Center. E-mail:
leesang@hawaii.edu; Michael R.M. Abrigo: Michael R.M. Abrigo: Philippine Institute for Development Studies.
E-mail: mabrigo@mail.pids.gov.ph; Tahir Aris: Institute of Public Health, Ministry of Health, Malaysia. E-mail:
tahir.a@moh.gov.my. This paper was presented at the ADB–IEA 2019 Roundtable, held 4–5 July 2019 in Tokyo.
Research for this paper was supported by JSPS Kakenhi Grant No. 15H05692. A considerable portion of the analysis
in this paper was developed in connection with the research project on Malaysia’s population aging undertaken by the
Social Wellbeing Research Centre of the Faculty of Economics and Administration, University of Malaya. We thank
the managing editor and the anonymous referees for helpful comments and suggestions. The Asian Development
Bank (ADB) recognizes “China” as the People’s Republic of China. The usual ADB disclaimer applies.

Asian Development Review, vol. 38, no. 1, pp. 32–67
https://doi.org/10.1162/adev_a_00157

© 2021 Asian Development Bank and
Asian Development Bank Institute.
Published under a Creative Commons
Attribution 3.0 International (CC BY 3.0) license.

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Population Aging and the Three Demographic Dividends in Asia 33

down, owing to substantial fertility declines in a host of developed economies and
a growing number of developing economies. As a result, in the past few decades,
population aging has been observed on a worldwide basis.

In various parts of the world, population aging has been accompanied by the
rapid growth of elderly populations. In 2015, elderly persons aged 65 and over in
Asia accounted for 55% of the elderly population of the world as a whole, and this
proportion is projected to increase to more than 60% by 2050 (United Nations [UN]
2017). Moreover, the number of those aged 65 and over grew dramatically at 2.4%
per annum in the second half of the 20th century. The corresponding number for
the first half of the 21st century is even projected to increase to 2.6%. Furthermore,
in Asia the proportion of the elderly in the total population rose from 4% to 5.8%
over the period 1950–2000, and is expected to grow at an astonishing tempo in the
years to come and reach 17.8% by the middle of the 21st century (UN 2017).

In marked contrast, the proportion of Asia’s young persons aged 0–14 is
projected to continuously decline from its peak value of 41% in 1965 to 18% in
2050. Although the actual number of young people more than doubled in the latter
half of the 20th century, it is now expected to decrease—from 1.13 billion in 2000
to 0.95 billion in 2050—at an annual rate of 0.4%.

As far as Asia’s working-age population (those aged 15–64) is concerned, it
is expected to expand more than 4 times from 1950 to 2050, while its proportion in
the total population is anticipated to fluctuate between 56% and 68% over the same
period. However, the age composition of the productive population is projected
to undergo a substantial transformation over the period in question. During the
period 1950–1990, for example, the proportion of those aged 15–24 in Asia’s total
population oscillated between 17% and 20%. After having recorded a peak of 20%
in 1990, the proportion has been and will continue to be on a downward trend,
diminishing to 13% by 2050.

More importantly, within Asia, there have been considerable intereconomy
differences in the level and speed of population aging (Fu and Hughes 2009; Park,
Lee, and Mason 2012). In a number of Asian economies, unprecedented changes
in age structure have occurred or are under way. In some of these economies, the
rise in old-age dependency has created myriad formidable policy challenges, the
response to which is likely to seriously influence their economic growth, poverty,
intergenerational equity, and social welfare for decades to come. In other economies
of Asia, the child dependency ratio has been falling rapidly, generating an important
demographic bonus, and facilitating faster economic growth.

To analyze the impact of age structural shifts on numerous socioeconomic
aspects, conventional demographic indicators such as the total dependency ratio
are commonly employed (Komine and Kabe 2009, Cheung et al. 2004, Golini
2004). These widely used indicators are exclusively based on chronological age
distributions in which each individual is equally counted as one regardless of age.

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34 Asian Development Review

From an economic point of view, however, the level of production and the amount of
consumption vary with age, so weights adjusted by age-specific per capita income
and consumption need to be assigned to each age group. Taking into account
this important point, the present study draws heavily upon a newly developed,
comprehensive, analytical framework called the National Transfer Accounts (NTA)
for estimating consumption, production, and resource reallocations by age on a per
capita basis.

In section II of this paper, we review patterns of age compositional shifts in
Asia since 1950. In section III, we examine the impact of age compositional shifts
on economic growth using two approaches: (i) conventional demographic indicators
and (ii) the NTA framework. In the first approach, the economic benefit of the youth
bulge induced by fertility declines is called “the demographic bonus,” while in the
second it is referred to as “the first demographic dividend.” In section IV, we use the
NTA model to analyze a key economic challenge for aging populations, which is
how to provide for old-age consumption in the face of substantially reduced income.
In some societies, this challenge is met by relying on intergenerational transfer
systems (either public programs or familial support systems). In others, the response
consists of increasing saving rates and accumulating greater physical wealth or
capital. It is in this latter response that prospects for more rapid economic growth
are enhanced, and this pro-growth mechanism is called “the second demographic
dividend.” Furthermore, we continuously employ the NTA framework to shed light
on how intergenerational transfer patterns change in the process of age structural
transformations. In section V, we turn our attention from the system of NTA to an
analysis of a newly defined demographic dividend, which is generated through the
use of the untapped work capacity of healthy older persons. In the present study,
this newly measured demographic dividend is labelled as “the silver demographic
dividend.” We might as well call it “the third demographic dividend” to distinguish
it from the two demographic dividends directly computed from the NTA system.

This paper contains the following: (i) a brief review of Asia’s changing
demographic landscape, with emphasis on age structural transformations among
selected Asian economies; (ii) a succinct description of the NTA model
to
facilitate the analysis that follows in the remainder of the paper; (iii) an
in-depth discussion of the demographic transition and its relationship to the first and
second demographic dividends, utilizing the cross-sectional results for 12 selected
Asian economies computed from the NTA system; (iv) a comparative analysis
of changing intergenerational transfer patterns in three rapidly aging East Asian
economies (Japan; the Republic of Korea; and Taipei,China); and (v) a quantitative
measurement of the potential work capacity among older workers (i.e., “the silver
demographic dividend” or “the third demographic dividend”) based on microlevel
data analyses for Japan and Malaysia. The final section of the paper summarizes the
major findings of the study.

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Population Aging and the Three Demographic Dividends in Asia 35

II. Rapidly Changing Age Compositional Shifts in Asia: 1950–2050

In 2015, Asia’s total population exceeded 4.4 billion people, which is
approximately 2.3 times larger than the population observed in 1965 (UN
2017). The annual growth rate of the population in Asia, however, has declined
continuously during the past 4 decades. After peaking at 2.45% from 1965 to 1970,
the region’s annual population growth rate during the 2010s is estimated at 0.98%.
With the emergence of slower population growth in the latter half of the 20th
century, Asia’s demographic outlook today is substantially different from that of
only a few decades ago.

Such substantially slower population growth in Asia has been caused chiefly
by a significant decline in fertility over the past few decades. From 1965 to 1970,
there was only one economy in Asia, Japan, with below-replacement fertility (i.e.,
a total fertility rate [TFR] of less than 2.1 children per woman). Japan’s postwar
fertility decline was the first of its kind to occur in the non-Western world, and it
was the greatest in magnitude among all industrialized economies (Ogawa, Jones,
and Williamson 1993; Hodge and Ogawa 1991). Following a short-lived baby boom
period (1947–1949), Japan’s fertility dropped dramatically (Ogawa and Retherford
1993; Retherford and Ogawa 2006; Ogawa, Retherford, and Matsukura 2009).
Between 1947 and 1957, Japan’s TFR declined by more than 50% from 4.54 to 2.04
children per woman. This reduction of fertility over a 10-year period was the first
such experience in the history of humankind. Subsequent to it, there had been only
minor fluctuations around the replacement level until the first oil crisis occurred in
1973. Thereafter, the TFR started to fall again and reached 1.26 in 2005, which was
an all-time low in postwar Japan. Since 2005, however, Japan’s TFR has been on
an upward trend, reaching 1.43 in 2017. If fertility were to remain constant at this
level, the population of each successive generation would decline approximately at
a rate of 31% per generation.1

Moreover, in terms of the population share, as shown in Figure 1, only
5.4% of Asia’s population lived in economies with below-replacement fertility in
1960–1965, compared with 43.9% in 1990–1995, when the People’s Republic of
China’s (PRC) fertility rate fell below the replacement level. In the second half of
the 2010s, slightly more than a half of Asia’s population resided in societies with
below-replacement fertility, and more than 80% of the Asian population will live
in economies with a fertility rate below the replacement level in the late 2020s,
when India is projected to reach a below-replacement level of fertility (UN 2017).
At present, among the economies of the three Asian subregions defined in the 2017
UN population projection (East Asia, Southeast Asia, and South Asia), there are
two economies with below-replacement fertility (Singapore and Taipei,China) that

1As of 2017, Japan’s replacement fertility level was 2.07. Thus, 1.43/2.07 = 0.69, which implies that if
Japan’s TFR remains unchanged in the years to come, the size of each successive generation will diminish by 31%.

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36 Asian Development Review

Figure 1. Proportion of the Asian Population Living in Economies with
Below-Replacement-Level Fertility, 1950–2050

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Source: Authors’ calculations based on data from United Nations. 2017. World Population Prospects: The 2017
Revision. New York.

are classified in the category of lowest-low fertility (i.e., those with a TFR below
1.3).2 In fact, East Asia’s fertility has been the lowest in the entire world since the
1990s (Gubhaju 2008; Ogawa et al. 2009; McDonald 2009; Gauthier 2015; Ogawa,
Matsukura, and Lee 2016).

Parallel to the rapid decline in fertility, marked mortality improvements have
occurred in Asia. The Japanese postwar experience is particularly a case in point.
When Japan joined the Organisation for Economic Co-operation and Development
in 1964, its life expectancy at birth was lower than that of any other member
country, but its life expectancy became the highest among all member states by
the early 1980s (Mason and Ogawa 2001). In 2017, Japan’s male life expectancy
at birth reached 81.1 years to become the third highest in the world, following
Switzerland and Hong Kong, China, while its female life expectancy reached 87.3
years, the second highest in the world, following only Hong Kong, China. Moreover,
18 economies and areas in the three abovementioned Asian subregions have life
expectancies higher than 70 years for both sexes combined. As indicated in Figure
2, the value of life expectancy at birth for both sexes combined for Asia as a whole
during 2015–2020 was 70.9 years, and it is generally considered that mortality

2According to the 2017 UN population projection, the Republic of Korea’s projected TFR for 2018 was 1.33,
but the country’s actual TFR for that year was just 0.98. Based on its actual TFR, the Republic of Korea should be
classified in the category of lowest-low fertility.

Population Aging and the Three Demographic Dividends in Asia 37

Figure 2. Life Expectancy at Birth for Asia as a Whole, 1950–2100

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Source: Authors’ calculations based on data from United Nations. 2017. World Population Prospects: The 2017
Revision. New York.

improvements begin to contribute to advancing the process of population aging once
the level of life expectancy at birth exceeds 70 years (Myers 1988).3

As a result of these rapid fertility and mortality transformations in the
latter half of the 20th century, we have witnessed phenomenal changes in Asia’s
demographic landscape in terms of population age compositions, with a relative
increase in the numbers of older persons and a relative decrease in the numbers
of the young. As illustrated in Figure 3, Asia’s total dependency ratio, which
is defined as [(0–14) + (65 and over)]/(15–64), reached its peak value (0.80)
in 1965, after which its long-term trend shows a U-shaped pattern, reaching its
trough value (0.47) in 2015. This implies that in Asia as a whole, the share of the
working-age population increased from 1965 to the middle of the 2010s. For Asia,
these 50 years during which the share of the working-age population continuously
rose corresponded to the period in which age structural shifts contributed to a
favorable impact on the per capita income growth, a phenomenon called “the
first demographic dividend,” which is exemplified by the “economic miracle” of
East Asian economies between 1960 and 1997 (Bloom and Williamson 1998,
Mason 2001). A detailed analysis of the first demographic dividend in Asia will
be presented in the ensuing section.

3At an early stage of mortality improvements, the extension of life is induced mainly by the reduction of
infant and child mortality, rather than by better survivorship at older ages. Hence, at the initial stage of mortality
transition, rising life expectancy leads to population rejuvenation rather than population aging (Ogawa 1986).

38 Asian Development Review

Figure 3. Changes in Dependency Ratios for Asia as a Whole, 1950–2050

Source: Authors’ calculations based on data from United Nations. 2017. World Population Prospects: The 2017
Revision. New York.

By and large, the demographic transition is a singular time period during
which fertility and mortality decline from high to low levels in a particular economy.
In the case of Asia, although the broad outlines of the demographic transition are
fairly similar in almost every economy in the region, the speed and timing of the
transition vary considerably across economies. The age composition of each of
the Asian economies under review has been changing swiftly since the middle of
the 20th century (Ogawa 2003). As shown in Table 1, from 1975 to 2000, the total
dependency ratio declined substantially in all three subregions and in 15 out of
the 17 economies listed (the Lao People’s Democratic Republic [Lao PDR] and
Nepal being the only exceptions). The extent to which the total dependency ratio
for each economy decreased over this period is closely related to the magnitude
with which its fertility declined, as reflected in the intertemporal change in the
youth dependency ratio, defined as [(0–14)/(15–64)]. Among the 17 economies
in Table 1, Thailand had the largest reduction in the total dependency ratio at
0.413 (from 0.852 to 0.439), followed by Mongolia (0.383), the Republic of Korea
(0.337), the PRC (0.321), Indonesia (0.304), Viet Nam (0.291), Malaysia (0.242),
Bangladesh (0.235), and the Islamic Republic of Iran (0.227). The fact that all
of these economies have shown substantial economic progress over the past few
decades seems to suggest that such steep declines in the total dependency ratio
facilitated their recent rapid economic growth.

The 2017 UN population projection, as shown in Table 1, indicates that the
economies with high total dependency ratios will face a considerable reduction

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Population Aging and the Three Demographic Dividends in Asia 39

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40 Asian Development Review

of the burden placed upon the working-age population in the first quarter of the
21st century and beyond. In these economies, the declining total dependency ratios
are likely to facilitate their developmental process. In contrast, the economies with
low total dependency ratios are expected to undergo a substantial increase in this
burden, mainly due to a rapid rise in the proportion of the elderly, as represented
by the aged dependency ratio expressed as [(65+)/(15-64)]. In economies where
the onset of fertility reduction was early, the changes in this aged dependency ratio
are most pronounced. Clearly, Japan had the largest gain (+0.136) from 0.113 in
1975 to 0.249 in 2000. Singapore showed the second largest gain (+0.042) from
0.065 to 0.103 over the same period, followed by the Republic of Korea (+0.034),
Thailand (+0.028), and the PRC (+0.028).

Among the 17 economies listed in Table 1, Japan is expected to have
the highest aged dependency ratio continuously up to 2050. However, a careful
comparison of the index of aging, which is defined as [(65 and over)/(0–14)] × 100,
yields a picture substantially different from the one based upon the aged dependency
ratios. By 2000, Japan’s index of aging had already exceeded 100. Over the period
2000–2025, Japan is expected to remain the most aged society not only in Asia
but also in the entire world. By 2050, however, the values of the index of aging
for Singapore and the Republic of Korea are projected to surpass that for Japan. In
addition, for Asia as a whole, the index of aging is projected to nearly reach 100
in 2050, which is considerably earlier than in 2074, which is the year projected for
the entire world, as depicted in Figure 4.4 Throughout human history, children were
substantially more numerous than the elderly, and the index of aging for the whole
world has never surpassed the 100 level. In the recent past, this newly emerging
demographic turning point has been called “the historic reversal of populations”
(Chamie 2016).

The data reported in Table 1 cover only four selected points in time: 1975,
2000, 2025, and 2050. It can be easily conceived that the age composition of each
economy undergoes a considerable transformation and transition. To shed light
upon such dynamic aspects of age structural shifts and their impacts on economic
growth, we turn our attention in the next section to the demographic dividends in a
number of selected Asian economies using the NTA framework.

III. The Impact of Age Structural Shifts on the First and Second

Demographic Dividends

A. Measuring the Impact of Demographic Changes on Economic Growth

In the 1990s, some population economists began to use the term
“demographic bonus.” However, since then a number of new terms referring to the

4The index of aging for the entire Asia is projected to exceed 100 in 2051.

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Population Aging and the Three Demographic Dividends in Asia 41

Figure 4. The Timing of the Historical Reversal of Populations: Japan, Asia,
and the World

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Source: Authors’ calculations based on data from United Nations. 2017. World Population Prospects: The 2017
Revision. New York.

same, or a highly comparable demographic–economic nexus, has appeared, ranging
broadly from such an expression as “demographic gift” to the term “window of
opportunity.” It is often the case that the total dependency ratio is defined differently
among researchers. Moreover, different criteria have been utilized to judge, on
the basis of computed total dependency ratios, whether or not an economy is
at the stage of a demographic bonus. For instance, Komine and Kabe (2009),
who use the conventional total dependency ratio, regard an economy as being at
the stage of a demographic bonus when the computed value falls continuously.5
In contrast, Cheung et al. (2004), although they employ the same conventional
total dependency ratio, apply a different criterion for assessing whether or not an
economy is experiencing a demographic bonus—for them, the demographic bonus
period corresponds to the stage where the computed value remains less than 0.5.6
In addition, Golini (2004) defines the total dependency ratio in a slightly different
manner—i.e., [(those aged 0–14) + (those aged 60+)]/(those aged 15–59)—and
classifies an economy as being at the demographic bonus stage when the calculated
value is below 0.66.

5According to Komine and Kabe (2009), the demographic bonus is generated if the value of [(those aged

0–14) + (those aged 65+)]/(those aged 15–64) continuously declines with the passage of time.

6Cheung et al. (2004) assert that the demographic bonus is generated when the value of [(those aged 0–14)

+ (those aged 65+)]/(those aged 15–64) is less than 0.5.

42 Asian Development Review

Figure 5. The Period of Demographic Bonus Based on Three Different Approaches

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Lao PDR = Lao People’s Democratic Republic, PRC = People’s Republic of China.
*See the detail in the text.
Source: Authors’ calculations based on data from United Nations. 2017. World Population Prospects: The 2017
Revision. New York.

A brief glance at Figure 5 reveals that

the period of a demographic
bonus differs considerably among the 12 selected Asian economies, depending
upon the definitions utilized. In six out of the 12 economies, the period of a
demographic bonus is not continuous if the computation is based upon the total
dependency ratio formula. For instance, in the case of Japan, there is a 7-year hiatus
(1970–1977) during the period 1950–1992. For the Lao PDR and Cambodia, the
number of hiatuses is considerably greater than Japan and other selected Asian

Population Aging and the Three Demographic Dividends in Asia 43

economies: in the case of the Lao PDR, there are five (1966–67, 1972–1982, 1986,
1991–1993, and 1996) from 1965 to 2045; while Cambodia has four (1966,
1982–1987, 1989–1995, and 2017–2019) from 1965 to 2045.7 Among the 12
economies, the Philippines would never enjoy a demographic bonus during the
entire period from 1950 to 2050 if computations were made on the basis of the
formula presented by Cheung et al. (2004). These calculated results imply that
the timing and duration of the demographic bonus vary among the 12 economies.
Moreover, the results for each economy also differ considerably, subject to the
formulas used.

As briefly mentioned in the previous section,

total
dependency ratio and its variants assume the same weight for every person
regardless of age, which is why they are very crude measures for quantifying
the impact of age structural transformations on economic growth performance.
To overcome this limitation of the total dependency ratio, we utilize the NTA
system and calculate the “first demographic dividend” instead of the “demographic
bonus.”

the conventional

B.

A Brief Outline of the National Transfer Accounts

Since the beginning of the 21st century, an international collaborative
research project has been carried out under the leadership of the following two
economists: Andrew Mason at the University of Hawaii at Manoa and Ronald D.
Lee at the Center for the Economics and Demography of Aging at the University of
California, Berkeley. A number of collaborating institutions in Asia, Latin America,
Europe, and Africa have been actively engaged in this international research project.
At present, almost 100 economies, both developed and developing, constitute the
full membership of the NTA global project.

One of the principal objectives of this project is to develop a system for
measuring economic flows across age groups. These flows arise because, in any
viable society, dependent members of the population—those who consume more
than they produce—are supported by members of the population who produce more
than they consume. Societies take different approaches to reallocating resources
from surplus to deficit ages, but two methods dominate. One method relies on
capital markets. Individuals accumulate capital during their working ages. When
they are no longer productive, the elderly can support their consumption by relying
on capital income (e.g., interest, dividends, rental income, and profits) and by
liquidating their assets. The second method relies on transfers from those at surplus
ages to those at deficit ages. Some transfers are mediated by the public sector.
Important examples of these kinds of transfers are public education, publicly

7Presumably, the age compositional shifts in the Lao PDR and Cambodia were the consequence of the

Indochina Wars (1946–1991), including the Viet Nam War (1955–1975).

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44 Asian Development Review

financed health care, and public pension programs. Many transfers are private;
among them, familial transfers are vital. The material needs of children are provided
for mostly by their parents. In Asian societies, familial transfers between adult
children and the elderly are also of huge significance. Some of these transfers are
between households, but intrahousehold transfers are much more important.

NTA provide a comprehensive framework for estimating consumption,
production, and resource reallocations by age. The accounts are constructed so
as to be consistent with and complementary to the National Income and Product
Accounts. Also, sectoral disaggregation allows the analysis of public and private
education and health-care spending. The NTA system will provide important new
information relevant to the following issues: (i) the first demographic dividend,
(ii) the second demographic dividend, and (iii) intergenerational transfers (public
and private [familial] transfers), (iv) aging policy, and (v) childbearing incentives.8

C.

Defining and Measuring the First Demographic Dividend

As discussed elsewhere (Mason 2001, 2007; Mason and Lee 2006; Lee and
Mason 2011), one of the important linkages between demographic transformations
and economic growth is the role of demographic dividends in the process of
economic development. As a country proceeds through the stages of demographic
transition, it undergoes considerable age structural shifts. When a country’s fertility
begins to fall, the first demographic dividend is generated because changes in its
population age structure have led to an increase in the population at working ages
relative to that at nonworking ages. In other words, the first demographic dividend
arises because of an increase in the share of the population at ages during which
production exceeds consumption. That is, the first demographic dividend is positive
when the economic support ratio, which is defined as the ratio of effective workers
to effective consumers, increases (Mason 2007).9

Using relatively simple mathematical notations, we can provide a short
description of the measure for the first demographic dividend: income per effective
consumer [Y (t )/N (t )], which is a measure of per capita income adjusted for age
variation in consumption, is the product of the economic support ratio [L(t )/N (t )]
and income per worker [Y (t )/L(t )]:10

Y (t )
N (t )

= L(t )
N (t )

× Y (t )
L(t )

(1)

8For further information on the NTA system, see the website of the Global NTA project at http://www.

ntaaccounts.org.

9Effective workers are calculated as a weighted sum of the population using the labor income age profile.

Effective consumers are calculated in a similar fashion, using the consumption age profile.

10For a more detailed mathematical description, see Mason (2007).

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Population Aging and the Three Demographic Dividends in Asia 45

Furthermore, N (t ), which represents the effective number of consumers, and L(t ),
which represents the effective number of workers, can be expressed as below:

N (t ) =

L(t ) =

(cid:2)

a
(cid:2)

a

α(a)P(a, t )

β(a)P(a, t )

(2)

where a and t denote age and year, respectively; α(a) and β(a) are the age profiles of
consumption and production respectively; and P(a, t ) is the population. Hence, the
estimates of the first demographic dividend are heavily dependent upon the average
age profiles of consumption (with both private and public sectors combined) and
production (for both paid employment and self-employment) of the economy under
study.

By the time of writing this paper, we managed to obtain the data required
for computing the first demographic dividend from the following 12 NTA member
economies in Asia: Cambodia in 2009; the PRC in 2009; Indonesia in 2012; India
in 2004; Japan in 2014; the Lao PDR in 2012; Malaysia in 2009; the Philippines
in 2015; the Republic of Korea in 2015; Thailand in 2013; Taipei,China in 2015;
and Viet Nam in 2012. By combining the age-specific per capita consumption and
production data for these 12 economies, weighted by the age-specific population
size for each economy, we have created the age-specific per capita consumption
and production profiles for “Asia as a whole” as an approximation (Figure 6). In
addition, the age-specific profiles of consumption and production on a per capita
basis for each of these 12 economies are displayed for comparative purposes in
Figure 7. These graphical expositions of the vertical values for both consumption
and labor income have been normalized on the basis of mean labor income for those
aged 30–49 years with a view to facilitating intereconomy comparative analyses.

It can be seen from Figures 6 and 7 that the two crossing ages at which the
status of economic independence changes differ substantially from graph to graph.
In the case of Asia as a whole, as shown in the top row of Table 2, the age at
which net consumers become net producers is 24, whereas the age at which net
producers become net consumers is 57. These two ages suggest that an average
Asian earns labor income greater than consumption for 33 years. Furthermore, a
quick glance at the ages of crossing from net consumers to net producers among the
12 Asian economies listed in Table 2 reveals that the PRC and Cambodia have the
lowest age (21 years), followed by Viet Nam (22 years), the Lao PDR (23 years),
and the Philippines (23 years old), while Japan and the Republic of Korea have the
highest age (28 years), followed by India (26 years) and Indonesia (26 years). For
the crossing ages from net producers to net consumers, Cambodia has the lowest
age (47 years), followed by Viet Nam (53 years). In contrast, the Lao PDR has the
highest age (62 years). Among the 12 economies, the difference between these two

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46 Asian Development Review

Figure 6. A Typical Asian Economic Life Cycle: NTA Estimates of Per Capita
Consumption and Labor Income for Asia as a Whole

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NTA = National Transfer Accounts.
Source: Authors’ calculations based on the National Transfer Account database.

ages is the largest in the case of the Lao PDR; an average Laotian produces more
than his or her consumption for 39 years. Interestingly, the Lao PDR’s neighbor,
Cambodia, has the shortest duration, i.e., 26 years. Obviously, this intereconomy
disparity in the crossing ages generates differences in the length and magnitude of
the first demographic dividend to a considerable extent.

To quantitatively demonstrate the timing and duration of

the first
demographic dividend for each economy, we need to discuss intertemporal changes
in the economic support ratio. Equation (1) can be expressed in growth terms as
follows:

(cid:3)

(cid:4)

(cid:3)

(cid:4)

(cid:3)

(cid:4)

g

Y (t )
N (t )

= g

L(t )
N (t )

× g

Y (t )
L(t )

(3)

The first demographic dividend is the rate of growth of the economic support
ratio, which rises or falls subject to the age compositional transformations in the
process of the demographic transition. During the demographic transition when
the economic support ratio is rising, income per effective consumer increases,
given that there is no change in productivity. As the economic support ratio
declines, however, income per effective consumer falls and the first demographic
dividend disappears. Thus, it should be stressed that the increase in income per
effective consumer is transitory. More importantly, the first demographic dividend

Population Aging and the Three Demographic Dividends in Asia 47

Figure 7. Comparison of Economic Life Cycle Patterns in the 12 Selected
Asian Economies

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Lao PDR = Lao People’s Democratic Republic, PRC = People’s Republic of China.
Source: Authors’ calculations based on the National Transfer Account database.

can be realized only if employment keeps pace with the growth of the working-age
population.

Now, we shall discuss the computed results pertaining to the first
demographic dividend for Asia as a whole and then for the 12 selected Asian
economies individually. With a view to quantifying the first demographic dividend
for Asia as a whole, which is approximated by combining the data compiled
from the 12 selected Asian economies, we have calculated the change in the
economic support ratio over the period 1950–2050, by applying the computed
age-specific per capita consumption and production results displayed in Figure 6
as statistical weights to the projected age-specific population of the entire Asia. At

48 Asian Development Review

Table 2. Crossing Age at Which the Status of Economic
Independence Changes for Asia as a Whole
and for 12 Selected Asian Economies

Economy

Asia as a whole
India
Philippines
Thailand
Indonesia
People’s Republic of China
Republic of Korea
Taipei,China
Cambodia
Malaysia
Viet Nam
Lao PDR
Japan

Crossing Age

From Net Consumers
to Net Producers

From Net Producers
to Net Consumers

24
26
23
25
26
21
28
25
21
25
22
23
28

57
59
57
56
56
58
57
55
47
56
53
62
59

Lao PDR = Lao People’s Democratic Republic.
Source: Authors’ calculations based on the National Transfer Account database.

this point, we have applied the same age-specific profiles of per capita consumption
and production, plotted in Figure 6, to the age-specific population of the whole
continent, assuming that these profiles remain unchanged throughout the entire
100-year period under review. This implies that the computational results only
reflect the effect of age structural change on the economic support ratio. In addition,
we have used the 2017 UN population projection as a source of demographic data
for computation.

The computed results of the first demographic dividend for Asia as a whole,
which is measured by the annual growth rate of its economic support ratio, are
shown in Figure 8. In case the annual growth rate of the economic support ratio
is positive, the first demographic dividend is generated. As can be observed in this
graphical exposition, the first demographic dividend for the entire Asia began in
1973, and is projected to come to an end in 2018, after which the Asian region as a
whole is expected to enter into the phase of population aging. Thus, the duration of
the first demographic dividend for Asia as a whole amounts to 45 years. As indicated
in Figure 8, the peak year of Asia’s first demographic dividend was 1990.

Furthermore, by heavily drawing upon the per capita age-specific labor
income and consumption data for each of the selected Asian economies, and on
the basis of the same computational assumptions and procedure applied to the
case of Asia as a whole, we have calculated a temporal change in the economic
support ratio for each of the 12 selected Asian economies for comparative purposes.
The calculated results are presented in Figure 9. There are marked intereconomy
differences among the 12 economies, both in terms of the timing and the duration

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Population Aging and the Three Demographic Dividends in Asia 49

Figure 8. Temporal Change in the Magnitude of the First Demographic Dividend for Asia
as a Whole, 1950–2050

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Source: Authors’ calculations based on the National Transfer Account database.

of the first demographic dividend. A few points of interest emerge from the results
shown in Figure 9. First, Japan entered the phase of the first demographic dividend
in 1950, which was the earliest among the 12 selected Asian economies in the
sample, and was followed by the Republic of Korea and Taipei,China in 1968.
Japan’s first demographic dividend period ended in 1982, while the corresponding
periods for the Republic of Korea and Taipei,China came to an end in 2013
and 2015, respectively. Second, among the 12 economies, Japan had the shortest
duration of the first demographic dividend, i.e., 32 years. Cambodia has the second
shortest duration of the first demographic dividend, i.e., 37 years from 1968 to
1981 and from 1997 to 2019. However, Cambodia is an exceptional case among
the 12 economies in that its first demographic dividend period is broken into two
subperiods. As mentioned earlier, this hiatus between 1981 and 1997 was affected
substantially by the unusual age compositional shift caused by a series of wars
in which Cambodia was involved in the second half of the 20th century. Third,
among the 12 selected Asian economies, the Philippines is projected to have the
longest period of the first demographic dividend at 79 years from 1971 to 2050. The
Philippines is followed by Indonesia, the Lao PDR, and India, which are projected
to have first demographic dividends lasting 63, 64, and 66 years, respectively.

More importantly, a quick glance at Figure 9 reveals that the annual growth
rate of the economic support ratio differs considerably across economies and with
the passage of time, thus indicating that the magnitude of the first demographic
dividend varies substantially among the 12 economies and over time. To shed light
upon the magnitude of the first demographic dividend for each economy, we have

50 Asian Development Review

Figure 9. Comparison of the Temporal Change in the Magnitude of the First
Demographic Dividend in 12 Selected Asian Economies

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Lao PDR = Lao People’s Democratic Republic, PRC = People’s Republic of China.
Source: Authors’ calculations based on the National Transfer Account database.

computed the average annual growth rate of the economic support ratio observed
for each of the selected Asian economies between the beginning year and the
end year of the first demographic dividend stage. As presented in Table 3, the
largest magnitude was recorded by the Republic of Korea (1.13%), followed by
Thailand (1.03%); Taipei,China (0.99%); and the PRC (0.90%).11 In the case of the
Philippines, the magnitude is expected to amount to a low value of 0.34%. India is
projected to have an even lower value of 0.31%.

11As previously mentioned, due to the unusual temporal change of its first demographic dividend, Cambodia

has been excluded from this computation.

Population Aging and the Three Demographic Dividends in Asia 51

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52 Asian Development Review

Figure 10. Estimated Relationship between the Magnitude of the First Demographic
Dividend and Amount of Reduction in the Total Fertility Rate per Year
in Selected Asian Economies

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Note: X refers to the average reduction in the total fertility rate per year.
Source: Authors’ calculations based on data from United Nations. 2017. World Population Prospects: The 2017
Revision. New York.

Besides the average annual growth rate of the economic support ratio for
the selected Asian economies, we have also gathered data, as indicated in Table
3, pertaining to the average annual amount of the decline of the TFR from the
beginning year to the final year of the first demographic dividend. To gain further
insights into the relationship between the magnitude of the decline of the TFR
and the average annual growth rate of the economic support ratio during the first
demographic dividend stage, we have conducted a relatively simple regression
analysis, covering all 11 economies listed in Table 3. In the regression equation,
the former variable has been employed as the explanatory variable and the latter
as the dependent variable. As shown in Figure 10, the estimated coefficient for
the explanatory variable is statistically significant (t-value of –2.86), suggesting
that the greater the average amount of fertility reduction per year, the greater the
potential impact of the first demographic dividend on macroeconomic growth. This
statistical result is in agreement with an axiomatic view held among population
economists that one of the key factors conducive to Asia’s miraculous economic
growth in the past several decades has been its extremely rapid decline in the
TFR (Bloom, Canning, and Malaney 2000; Lee and Mason 2011; Mason and Lee
2012).

Population Aging and the Three Demographic Dividends in Asia 53

D.

Computing the Second Demographic Dividend

The second demographic dividend corresponds to the growth rate of
productivity or output per effective worker, which is induced by the accumulation of
wealth as well as physical and human capital deepening. The second demographic
dividend arises when individuals at all age groups increase their demand for wealth
in some form to support their old-age consumption. One possibility is that old-age
economic security might heavily rely on transfers from public pension and welfare
programs, or from adult children and other family members. The other possibility is
that individuals accumulate capital during their working years, which in turn serves
as the source of support in retirement. Both of these forms of wealth can be utilized
to support consumption in old age.

It is extremely important to pay attention to the following key point: only
capital accumulation will lead to an increase in productivity. Unlike the first
demographic dividend, the second demographic dividend is not transitory, and it
may lead to a permanent increase in capital deepening and income per effective
consumer. The second demographic dividend does not occur automatically, but
rather can be realized if consumers and policy makers are forward looking and
respond effectively to coming demographic changes by encouraging an old-age
support system that substitutes capital for the transfer of wealth. There are two
ways that demographic factors cause an increase in the demand for life cycle wealth
and the second demographic dividend. First, there is a compositional effect, caused
by an increase in the share of individuals who have nearly or fully completed their
productive years. Second, there is a behavioral effect, caused by an increase in life
expectancy and the accompanying increase in the duration of retirement leading to
an increase in demand for wealth.

Demand for life cycle wealth is mainly concentrated among older working
adults who are approaching their peak earnings and have completed their
childrearing responsibilities. Mason (2007) uses the wealth held by those aged 50
years and older to measure the effect of demography on life cycle wealth and the
second demographic dividend. Demand for life cycle wealth is computed as the
difference between the present value of lifetime consumption and the present value
of lifetime production for adults.12

By closely following the computational procedure described in Mason
(2007), we have calculated the second demographic dividend for all 12 economies
listed in Figure 7. All the values reported in Table 4 represent the average annual

12Computational assumptions employed in Mason (2007) were as follows: (i) holding the transfer policy
constant so that the growth rates of the capital and life cycle wealth are equal; (ii) setting the elasticity of labor
income with respect to capital at 0.5 (i.e., the second demographic dividend is calculated as half of the growth rate
of wealth ratio to income); and (iii) the growth of consumption and labor income are 1.5% per year, and the interest
rate is 3%.

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54 Asian Development Review

Table 4. Second Demographic Dividend in 12 Selected Asian Economies
Expressed in Terms of the Annual Growth Rate (%)

Economy

Profile

2010–2020

2020–2030

2030–2040

2040–2050

Japan
Republic of Korea
Malaysia
Philippines
Thailand
Viet Nam
Lao PDR
Taipei,China
PRC
Cambodia
India
Indonesia

2014
2015
2009
2015
2013
2012
2012
2015
2009
2009
2004
2012

0.29
2.01
1.91
1.27
1.77
1.75
6.25
1.79
1.79
1.48
1.43
1.97

0.32
1.09
1.29
1.22
1.23
1.07
2.89
0.86
0.99
0.73
1.17
1.63

0.18
0.37
1.29
0.97
0.50
0.98
2.24
0.34
0.64
1.65
1.08
1.18

0.01
0.13
1.10
0.80
0.20
0.62
1.88
0.13
0.42
1.17
0.90
0.78

Lao PDR = Lao People’s Democratic Republic, PRC = People’s Republic of China.
Source: Authors’ calculations based on the National Transfer Account database.

Figure 11. Comparison of the First and Second Demographic Dividends in Malaysia

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Sources: Authors’ calculations based on the National Transfer Account database.

growth rate of capital stock for each successive decade over the period 2010–2050.
As can be clearly seen from this table, most of the developing Asian economies
are likely to have a sizable second demographic dividend in the years to come.
Particularly, the magnitude of the second demographic dividend is substantially
larger than that of the first demographic dividend over the period 2010–2050
in all economies. To illustrate this point more concretely, we have plotted in
Figure 11 the pattern of changes in the first and second demographic dividends

Population Aging and the Three Demographic Dividends in Asia 55

for Malaysia. It is also worth observing that although Japan’s first demographic
dividend has already been negative for more than 3 decades, as shown in Figure 8,
its second demographic dividend, which is projected to occur substantially after the
2020–2030 period, is expected to remain positive up to 2050.

Before closing our discussion pertaining to the first and second demographic
dividends, we should bear in mind that the projected results summarized in Tables
3 and 4 reflect only the age compositional effect. The relationship between the
demographic dividends and income growth is very policy dependent. The first
demographic dividend arises in part because the working-age population is growing
rapidly. The economic gains can be realized only if employment opportunities
expand as rapidly as the numbers seeking new jobs. The second demographic
dividend arises in part because prime-age adults save more to provide for their
retirement. Their ability or willingness to save, however, may be undermined by
poorly developed financial markets or overly generous publicly funded pension
programs. Demographic transformations simply define possibilities, and the
outcome is heavily dependent on a large number of nondemographic factors.

IV. Population Aging and Its Impact on Intergenerational Transfers in Three

East Asian Economies

In this section, we use the NTA system to analyze the changing patterns of
intergenerational transfers in Japan; the Republic of Korea; and Taipei,China. These
three East Asian economies have already entered an advanced stage of population
aging, where the patterns of intergenerational transfers, both public and private
(familial), have been shifting to a marked extent. For the sake of convenience, we
first examine the NTA computational results for Japan, the forerunner of Asia’s
population aging. Subsequently, we compare the case of Japan with those of the
Republic of Korea and Taipei,China.

The NTA, which measures intergenerational flows for a certain period of

time, is governed by the following relationship:
= C + IK + IM + τ −

yl + r(K + M ) + τ +
g

+ τ +
f

g

+ τ −
f

(4)

= transfer inflows from the public sector; τ +
f

where yl = labor income; rK = returns to capital; rM = returns to land and credit;
τ +
= transfer inflows from the private
g
sector; C = consumption; IK = investment in capital; IM = investment in credit and
land; τ −
= transfer outflows to the
g
private sector.

= transfer outflows to the government; and τ −
f

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3

In addition,

consumption and production,
reallocations through assets and net transfers as expressed below:

the life cycle deficit, which is the difference between
is matched by age reallocations consisting of

56 Asian Development Review

Figure 12. Changing Pattern of the Per Capita Life Cycle Deficit in Japan

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Source: Authors’ calculations based on the National Transfer Account database.

C − yl
(cid:5) (cid:6)(cid:7) (cid:8)
Lifecycle deficit

= yA − S
(cid:5) (cid:6)(cid:7) (cid:8)
Asset reallocations

− τ −
+ τ +
g
g
(cid:5) (cid:6)(cid:7) (cid:8)
Net public transfers
(cid:5)

+ τ +
f

− τ −
f
(cid:5) (cid:6)(cid:7) (cid:8)
Net private transfers
(cid:8)

(cid:6)(cid:7)
Net transfers

(cid:8)

(cid:5)

(cid:6)(cid:7)
Age reallocations

(5)

where yA = asset income, and S = saving.

Before proceeding to a discussion of the computational results, however,
caution should be exercised with regard to the following two points. First, the
terms “familial transfers” and “private transfers” are used interchangeably in this
paper—both refer to transfers coming from other family members of the same
or a different household. Second, although net private transfers comprise bequests
and inter vivos transfers, the computation of the bequest component had not been
completed at the time of writing this paper. For this reason, bequests are excluded
from the computational results reported in this paper. Also, the estimated values for
the totals have been adjusted on the basis of National Income and Product Account
values to ensure consistency.

Figure 12 compares the changing patterns of the three components of
reallocation of the life cycle deficit for the entire population in Japan from 1989
to 2009. The three components include net reallocations through assets, net public

Population Aging and the Three Demographic Dividends in Asia 57

transfers, and net private (familial) transfers. Panels A, B, and C illustrate the annual
reallocations of the per capita life cycle deficit for the whole population of Japan
observed in 1989, 1999, and 2009, respectively.

A brief comparison of the three panels in Figure 12 reveals the following
transfers to the elderly
the composition of net
two points of interest. First,
population changed dramatically over the 20-year period from 1989 to 2009. To
facilitate the intereconomy comparison among the three East Asian economies,
we have standardized all the monetary values in the three panels by dividing
them by the mean labor income of those aged 30–49 years. As can be easily
observed by comparing the three panels, the amount of per capita net public
transfers to the elderly population increased significantly from 1989 to 2009.
Similarly, the amount of net asset-based reallocations grew remarkably over the
same period. In contrast, the relative importance of net private (familial) transfers
from the young to the elderly declined to an appreciable extent. These results
seem to indicate that the Japanese elderly have been increasingly dependent upon
public transfers (predominantly old-age pensions and medical care services) and
asset-based reallocations in supporting their retirement life.

Second, and more important, as marked by the two ovals in Figure 12
(one in Panel B and the other in Panel C), the amount of net private (familial)
transfers to the relatively young elderly persons (roughly in their 60s and early
70s) was negative in both 1999 and 2009, implying that the amount of financial
assistance the relatively young elderly persons provided to their adult children
and/or grandchildren exceeded the monetary assistance from the latter to the former.
From Panels A and B, we see that the amount of such negative net familial transfers
from the relatively young elderly to other age groups rose during the period of
Japan’s “lost decade” (Yoshikawa 2001). These results suggest that despite the fact
that multigenerational coresidence has weakened over the past few decades (Ogawa,
Retherford, and Matsukura 2006), the Japanese elderly still play a vital role in
providing financial support to their offspring when the latter encounter economic
difficulties.13

Next, by utilizing calculated results for Japan presented in Panel C of Figure
12, we compare Japan’s intergenerational transfer pattern with that of the Republic
of Korea in 2015 (Figure 13) and Taipei,China in 2015 (Figure 14). A close
examination of these three graphical expositions reveals that in the case of Japan,
public transfers play a more dominant role in financing the life cycle deficit among
the elderly population than in the cases of the Republic of Korea and Taipei,China.
This intereconomy difference is largely attributable to the fact that, because the
social security system in Japan was established approximately 3 decades earlier

13Although older persons in Japan are often considered an overall liability for the country, they are actually
playing a key role as society’s safety net. For this reason, they should be viewed as latent assets in contemporary
Japanese society (Ogawa 2008; Ogawa, Matsukura, and Chawla 2011).

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58 Asian Development Review

Figure 13. Pattern of the Per Capita Life Cycle Deficit in the Republic of Korea, 2015

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m

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.

Source: Authors’ calculations based on the National Transfer Account database.

Figure 14. Pattern of the Per Capita Life Cycle Deficit in Taipei,China, 2015

/

e
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a
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–
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b
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r
2
0
2
3

Source: Authors’ calculations based on the National Transfer Account database.

Population Aging and the Three Demographic Dividends in Asia 59

than in the Republic of Korea and Taipei,China, Japanese elderly persons have
been able to enjoy higher pension benefits at a more mature stage, as well as more
comprehensive medical care services than their counterparts in the Republic of
Korea and Taipei,China. Moreover, in the Japanese case, the net asset reallocations
play a more substantial role in financing the life cycle deficit among the elderly
population than in the case of either the Republic of Korea or Taipei,China. This
difference reflects the fact that the three economies underwent rapid economic
growth at considerably different points in time.

In view of future aging trends in both the Republic of Korea and
Taipei,China, it is highly conceivable that the two economies will follow in Japan’s
recent footsteps in transforming their patterns of intergenerational transfers by
shifting to public transfers and asset reallocations, and attaching less importance to
private (familial) transfers, particularly among the elderly population. Furthermore,
although the current demographic setting of these three East Asian economies is
considerably more advanced than that of most developing economies in South and
Southeast Asia, many of the economies in the three Asian subregions share to a
great extent similar traditional values relating to familial responsibilities. In view
of these similarities, we may safely presume that the recent experiences of the
changes in intergenerational transfers in the abovementioned East Asian economies
can serve as a useful regional reference point to many developing economies in
Asia for formulating effective and efficient policies for coping with rapid population
aging.

It is also worth observing that the private (familial) transfers directed to the
young population in the three East Asian economies are noticeably larger than
those in NTA economies outside Asia, although relevant graphs for interregional
comparison are omitted. As discussed elsewhere (Ogawa et al. 2015), the amount
of financial resources that parents spend on their children’s education is extremely
large in these three East Asian economies, and this has been one of the major
reasons why East Asia currently has the lowest TFR in the world.

V. The Potential Work Capacity of the Elderly and the “Silver

Demographic Dividend”

In this section, we turn our attention from the NTA-based analysis to a new
analytical topic—a newly defined demographic dividend generated through the use
of the untapped work capacity of healthy older persons. In this study, we label it
“the silver demographic dividend.” For the sake of convenience, we may also refer
to it as “the third demographic dividend” to distinguish it from the two demographic
dividends directly computed from the NTA system.

Our main motive to shed light on measuring this newly defined demographic
dividend is related to the recent shortage of human resources in some of Asia’s aging

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60 Asian Development Review

economies. Japan is a typical case; its labor force size and its age composition have
changed significantly in the postwar period. According to Japanese census data, the
size of the total labor force grew continuously from 1970 to 1995. After reaching
its peak in 1995, however, it commenced shrinking. According to the population
projection released in 2019 by the National Institute of Population Problems
and Social Security Research, the working-age population (15–64 years old) is
expected to dwindle from 77.3 million in 2015 to 45.3 million in 2065. Taking into
consideration such gloomy demographic and labor force prospects, the Government
of Japan recently announced an eye-catching plan. According to it, the government
will require all employers to keep their employees on the payroll until they reach
the age of 70 if the latter wish to stay on. To achieve this goal, the government is
asking businesses to choose from among seven measures designed to allow older
people to continue working. The measures include abolishing the retirement age,
extending the retirement age to 70, and introducing elderly employees to jobs at
other firms. Furthermore, the legislation is expected to come in two stages. First,
the government plans to submit a bill, urging businesses to keep their employees
until they reach the age of 70. After that, the government will eventually make the
above measures mandatory.

In view of this recent government initiative, we have attempted to measure
the potential work capacity of old workers to alleviate the adverse effects of aging
and population decline on Japan’s economic growth. To facilitate this numerical
exercise by following up on our earlier study (Matsukura et al. 2018), we have
attempted to quantify the potential work capacity in Japan in terms of health status
among those aged 50 and over, by pooling all the observations from the first to
the fifth waves (i.e., 2007, 2009, 2011, 2013, and 2015) of the survey called the
Japanese Study of Aging and Retirement (JSTAR).14 In our earlier work (Matsukura
et al. 2018), we covered only the first three waves of JSTAR. In the present study, we
first estimate the relationship between health and employment for men and women
aged 50–59 and use the estimated result, along with the actual characteristics of
old people (aged 60–79), to simulate the latter’s capacity to work based on their
health. We then attempt to link the estimated statistical results derived from JSTAR
to the system of NTA to quantify to what extent the economic support ratio would
be enhanced through utilization of the untapped work capacity among old workers
(aged 60–79).

14JSTAR is a longitudinal, interdisciplinary survey that collects internationally comparable data on the
middle aged and old. The JSTAR project commenced in 2007, and the survey has been implemented in 2-year
intervals. JSTAR is a sister survey compatible with the Health and Retirement Study; English Longitudinal Study
of Aging; Survey of Health, Aging, and Retirement in Europe; China Health and Retirement Longitudinal Study;
and Longitudinal Aging Study in India. JSTAR’s design and sample methodology are described elsewhere (Ichimura,
Hashimoto, and Shimizutani 2009). The baseline sample consists of male and female respondents aged 50–75 from
10 municipalities. The respondents were randomly chosen from household registries kept by the local governments.
The sample size and the average response rate at the baseline were approximately 8,000 and 60%, respectively.
JSTAR collects a wide range of variables, including the economic, social, family, and health conditions of the sampled
respondents.

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Population Aging and the Three Demographic Dividends in Asia 61

In our analysis, we have not included a number of factors affecting the
decision of labor supply (e.g., wages), but focused on the health disability to
examine to what extent the labor supply of the elderly is limited. We have employed
a linear probability model to regress the binary variable of employment, which is
equal to 1 if the individual is in the labor force (both employed and unemployed)
and 0 if the individual is out of the labor force, on the following health-related
explanatory variables: (i) dummy variables for self-reported health status (five-point
scale); (ii) the incidence of limitations on instrumental activities of daily living; (iii)
the Center for Epidemiologic Studies Depression Scale;15 (iv) the Nagi physical
ability index;16 (v) limitations in sensory organs (eyesight, hearing, and chewing);17
and (vi) individual attributes such as sex, educational attainment, and marital status.
In addition, dummy variables for each municipality and for survey years have been
included.

The estimated regression results are summarized in Table 5. By utilizing
these results, we have simulated the untapped work capacity for Japanese older
adults aged 60–79. We have used the estimated coefficient to compute predicted
in JSTAR and averaged them by each age. The
values for each individual
“untapped work capacity” is defined as a slack between the actual and the
predicted employment probability. Figure 15 shows that the estimated untapped
work capacity, marked in gray, increases with age. The untapped work capacity
in Japan is estimated to amount to 4.12 million for persons aged 60–79.

To calculate the potential impact of these additional workers on Japan’s
gross domestic product (GDP), we have set up the following three cases. Case I
assumes that if the potential elderly workers are employed, they earn labor income
in accordance with the NTA age-specific labor income profile observed in 2009;
Case II assumes that the potential elderly workers at each age can earn the same
amount of labor income as their counterparts who were employed in 2014; and
Case III assumes that if the potential elderly workers are employed, they earn only
the minimum wage set by Japanese law. The computed results are as follows: in
Case I, the real GDP for 2015 is 4.5% higher; in Case II, it is 6% higher; and in
Case III, it is 3.2% higher. These additional GDP gains might be regarded as the
“silver demographic dividend” or “third demographic dividend.”

15Scores on the Center for Epidemiologic Studies Depression Scale range from 0 to 60, where higher scores
suggest a greater presence of depression symptoms. A score of 16 or higher is interpreted as indicating a risk for
depression.

16The Nagi index in JSTAR consists of 10 items and is designed to capture difficulties in physical activities
that are relevant to work capacity: (i) walking 100 meters, (ii) sitting continuously for 2 hours, (iii) standing up from a
chair after sitting for a long time, (iv) climbing several steps without using the handrail, (v) climbing one step without
using the handrail, (vi) squatting or kneeling, (vii) raising hands above the shoulders, (viii) pushing and pulling large
objects such as chairs and sofas in a living room, (ix) lifting and carrying an object weighing more than 5 kilograms,
and (x) grasping a small object such as a 1 yen coin with fingers.

17For each of the sensory organs, we have assigned the following three numerical values: 2 denotes conditions

ranging from “very good” to “not bad,” 1 stands for “bad,” while 0 stands for “impossible.”

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62 Asian Development Review

Table 5. Estimated Regression Results (Dependent variable: 1 = in the labor force,
0 otherwise)

Explanatory
Variables

Sensory organs
Eyesight
Hearing
Chewing ability

Municipalities
Takikawa
Sendai
Adachi
Chofu
Kanazawa
Shirakawa
Tondabayashi
Hiroshima†
Tosu
Naha

Year of survey

2007†
2009
2011
2013
2015
Constant

Coefficient

T-value

−0.005
−0.059
0.136

0.016
−0.043
0.044
0.031
0.025
0.065
0.019
—
0.016
0.017

—
−0.025
−0.028
−0.036
−0.023
0.577

−0.16
−1.48

3.53***

0.56
−1.83*
1.84*
1.15
1.13
2.84***
0.76
—
0.67
0.75

—
−1.68*
−1.68*
−1.87*
−0.91

4.44***

Explanatory
Variables

Sex

Man
Woman†
Education

Junior high†
Senior high
Junior college
University or higher

Marital status

Currently married
Currently not married†

Self-rated health status

Excellent
Very good
Good
Fair†
Poor
CESD
(cid:2)16
<16† IADL (cid:2)1 0† Nagi index Walking 100 meters Sitting for two hours Standing up for a long time Climbing several steps without the handrail Climbing one step without the handrail Squatting or kneeling Raising hands above the shoulders Pushing and pulling a large object Lifting and carrying more than 5 kilograms Picking up a small object with fingers Coefficient T-value 0.234 — — 0.037 0.040 0.072 −0.079 — 0.104 0.060 0.005 — −0.247 0.019 — 0.005 — 21.7*** — — 2.17** 2.09** 3.72*** −5.91*** — 5.24*** 3.06** 3.45** — −5.52*** 1.55 — 0.45 — −0.095 −0.079 0.010 −1.51 −1.75* 0.25 −0.060 −1.35 −0.016 −0.29 −0.038 −0.013 −1.12 −0.24 −0.074 −1.42 −0.144 −2.75** 0.150 2.06** CESD = Center for Epidemiologic Studies Depression Scale, IADL = instrumental activities of daily living. Notes: Adjusted R-squared = 0.165; number of observations = 4,666; and *, **, and *** represent statistical significance at the 10%, 5%, and 1% levels, respectively. † Denotes the reference group. Source: Authors’ calculations. l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 8 1 3 2 1 8 9 7 7 3 7 a d e v _ a _ 0 0 1 5 7 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Population Aging and the Three Demographic Dividends in Asia 63 Figure 15. Age-Specific Observed Labor Force Participation Rate and Potential Labor Force Participation Rate in Japan l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / Source: Authors’ calculations. In addition to Japan, we have applied a comparable analytical approach to Malaysia. In the case of Malaysia, we have drawn upon the data gathered from the 2011 National Health and Morbidity Survey conducted by the Institute of Public Health. The specification of regression is comparable to the Japanese case, although the number of explanatory variables introduced into the regression has been considerably smaller due to the limited compatibility of the information gathered by JSTAR and the National Health and Morbidity Survey. Table 6 presents each estimated regression coefficient together with the t-value. The simulated results are interesting. If Malaysia’s older adults aged 60 and over behaved in accordance with what the regression results suggest, the number of workers older than 60 in the country would be 2.14 times higher than what it is now. If such an increase in the number of older workers had been achieved, the country’s GDP in 2011 would have increased between 0.55% (based upon Malaysia’s NTA’s age-specific labor income profile) and 0.95% (based upon minimum wages). These gains would also increase dramatically if we applied Japan’s 2009 population structure to the Malaysian result; Malaysia’s GDP would have increased by between 2.5% and 4.2%, which is fairly comparable to the results we obtained from the Japanese simulation. The computational results for Japan and Malaysia suggest that the untapped labor capacity has enormous potential to boost the GDP of these two economies. However, we have not examined the issue of whether the use of untapped work / / / / 3 8 1 3 2 1 8 9 7 7 3 7 a d e v _ a _ 0 0 1 5 7 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 64 Asian Development Review Table 6. Estimated Regression Results for Malaysia, 2011 Explanatory Variables Coefficient T-value Constant Sex Ethnicity Education Marital status Male Femalea Malaya Chinese Indian Other Bumiputeras Others No formal educationa Primary education Secondary education Tertiary education Marrieda Single Widow, widower, divorcee Self-rated health status Good Moderatea Bad Depression scale Difficulty in work and daily activities Eyesight 0.278 0.404 — — 0.046 −0.013 0.006 0.126 — 0.040 0.097 0.228 — 0.049 0.034 0.041 — −0.119 0.007 −0.023 0.007 8.18*** 23.87*** — — 2.30** −0.45 0.19 2.68*** — 1.33 3.12*** 5.84*** — 1.17 1.26 2.05** — −1.95* 1.40 −0.91 0.33 Notes: Adjusted R-squared = 0.193; number of observations = 3,114; and *, **, and *** represent statistical significance at the 10%, 5%, and 1% levels, respectively. “Bumiputeras” is a broad term that denotes Malays, the indigenous peoples of Malaysia known as Orang Asli, and the natives of Sabah and Sarawak in East Malaysia. “Other Bumiputeras” in the table above means Bumiputeras other than Malays. aDenotes the reference group. Source: Authors’ calculations. capacity of old persons could affect the well-being of workers belonging to other age groups. VI. Concluding Remarks In this paper, we have reviewed the trends in age structural shifts in a number of selected economies in Asia over the period 1950–2050 and analyzed their impact on the first and second demographic dividends, using the computed results generated under the global NTA project. The computed results indicate that although there has been and will be large variability in the level and tempo of population aging among Asian economies, the magnitude of the impact of the first and second demographic dividends on macroeconomic growth has been and will be substantial in most of them. More importantly, because the first demographic dividend is basically transitory in nature, each economy should be aware of its timing so as to seize its potential for strengthening the socioeconomic foundations the impact of the second for developing social security systems. Moreover, l D o w n o a d e d f r o m h t t p : / / d i r e c t . m i t . / e d u a d e v / a r t i c e - p d l f / / / / / 3 8 1 3 2 1 8 9 7 7 3 7 a d e v _ a _ 0 0 1 5 7 p d . f b y g u e s t t o n 0 8 S e p e m b e r 2 0 2 3 Population Aging and the Three Demographic Dividends in Asia 65 demographic dividend on macroeconomic growth is subject to the effectiveness of a wide range of policies to be adopted by the government. In addition, we have demonstrated, using the NTA framework, the impact of age structural shifts on the pattern of intergenerational transfers in Japan over the period 1989–2009 and subsequently compared the case of Japan in 2009 with the cases of the Republic of Korea and Taipei,China in 2015. The brief comparison suggests that, in view of the projected demographic trends, the Republic of Korea and Taipei,China will follow Japan in the shifting pattern of intergenerational transfers over the next few decades. Although our discussion has been confined primarily to these three economies, the empirical findings concerning them are highly applicable to other Asian economies for the following two reasons. First, many developing Asian economies have been following these East Asian economies in terms of their pattern of demographic development, and such a trend is likely to persist for many years to come, as seen in the 2017 UN population projection. Second, Japan, the Republic of Korea, and Taipei,China share traditional cultural values to a considerable degree and have a similar family organization. Moreover, there are many developing economies in Southeast and South Asia that have similar sociocultural and demographic traits to East Asia. In view of this, we may expect that the East Asian experiences of population aging and changing intergenerational flows will lend themselves to analyzing crucial policy issues likely to crop up in the future as part of the population aging process in developing economies in Southeast and South Asia. Toward the end of this paper, we dealt with a new important research topic in the realm of population aging, “the silver demographic dividend” or “the third demographic dividend,” which is generated through the use of the untapped work capacity of healthy older adults. It is of great importance to note that this topic is closely related with changes in the health of the elderly. 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