Population Aging and the Three Demographic Dividends in Asia

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 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. 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.

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

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 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

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 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.

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

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 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, the conventional 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.”

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 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

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

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.

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 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.

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 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%.

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

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.

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.

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.

A brief comparison of the three panels in Figure 12 reveals the following two points of interest. First, the composition of net transfers to the elderly 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

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.

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 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).

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.

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.”

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 capacity of old persons could affect the well-being of workers belonging to other age groups.

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 for developing social security systems. Moreover, the impact of the second 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. Since it is certain that the health of Asia's elderly will continue improving over time, this new research topic is likely to be addressed by more population economists in Asia and elsewhere in the future.