00074918.2014.896236
Bulletin of Indonesian Economic Studies
ISSN: 0007-4918 (Print) 1472-7234 (Online) Journal homepage: http://www.tandfonline.com/loi/cbie20
The Demography of Indonesia in Comparative
Perspective
Peter McDonald
To cite this article: Peter McDonald (2014) The Demography of Indonesia in
Comparative Perspective, Bulletin of Indonesian Economic Studies, 50:1, 29-52, DOI:
10.1080/00074918.2014.896236
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Date: 17 January 2016, At: 23:24
Bulletin of Indonesian Economic Studies, Vol. 50, No. 1, 2014: 29–52
THE DEMOGRAPHY OF INDONESIA IN
COMPARATIVE PERSPECTIVE
Peter McDonald
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The Australian National University
Having reduced its fertility rate over the past 40 years, Indonesia has reached a
new demographic crossroad. Its fertility rate is now around 2.5 births per woman,
which, if sustained, would add substantial numbers to Indonesia’s population in
the future. There are concerns within Indonesia that the present level of population
growth is an obstacle to continued economic development and, accordingly, that
fertility should be reduced to the replacement level of 2.1 births per woman as soon
as possible. Yet a comparative perspective indicates that countries such as Singapore, Japan, and Thailand are concerned about the effects that their very low rates
of fertility are having on their labour forces and their rates of population ageing.
This article suggests that with the right policy settings Indonesia can avoid this outcome yet continue to reduce its fertility. It discusses the implications of Indonesia’s
population growth and distribution for its economy, as well as the poor quality of
demographic data.
Keywords: population growth, age structure, urbanisation, fertility, mortality, population
and development
JEL classiication: J11, J21, J61, O15
INTRODUCTION
Reducing the rate of population growth by reducing the fertility rate has been a
central component of Indonesia’s development planning agenda since the late
1960s. This has also been the position of most comparator countries in Southeast
Asia and East Asia. In effect, the aim has been to reduce the fertility rate to around
two births per woman. Today that aim is close to being achieved in Indonesia,
and in some provinces the fertility rate has fallen below this level. Indonesia’s
population will continue to grow, however, because of ‘population momentum’,
in which future population growth is driven by increasingly higher numbers of
women in the reproductive ages and, hence, by more births than deaths.
One of the main justiications for the introduction in the 1960s and 1970s of
policies to reduce fertility in developing countries was that in the 20 to 40 years
following the fall in fertility, the age distribution of the population would concentrate in the working ages. Without the economic burden of large numbers of
children and large family sizes, nations and families alike could apply capital to
productive investment rather than to consumption, resulting in higher GDP per
capita. In the interim, the smaller numbers of children would mean that a greater
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http://dx.doi.org/10.1080/00074918.2014.896236
© 2014 Indonesia Project ANU
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30
Peter McDonald
level of expenditure could be applied to the education of each child (Jones 1971).
Over time, the country would experience a leap forward in human capital as the
next, smaller generation was educated to higher levels. Universal primary education was an associated feature of these policies. Today this approach is referred
to as the ‘demographic dividend’ or ‘demographic bonus’. It has been argued
that the demographic dividend was a central component of the economic successes in countries such as Japan, South Korea, Taiwan, and Singapore (Bloom
and Williamson 1998; Kinugasa 2013). Its logic was also part of the rationale for
China’s adoption of the one-child policy. Deng Xiaoping was a major sponsor of
the one-child policy, based on his expressed view that China would not be able
to develop its economy or raise the living standards of its people unless the birth
rate fell rapidly (Potts 2006). There is also a reasonable argument that the contrasting economic development pathways of Thailand, Indonesia, and the Philippines
over the past 40 years have been associated with the relative timing and extent of
the decline in fertility in these countries.
The use of fertility reduction as a policy approach to development arose out
of the Cold War. In the years immediately after the Second World War, American demographers such as Frank Notestein and Ansley Coale were able to convince the US government that declining fertility was a necessary prerequisite for
economic development. This was something of a reversal of the previous theoretical position, demographic transition theory, by which fertility fell only as a
consequence of development (Szreter 1993). Demographic transition theory had
strong theoretical underpinnings. In contrast, the view that fertility could fall
prior to economic development was based not so much on a theory of how this
might occur as on the consequences if it did occur. More than any other source,
the evidence for this consequential argument was provided by the book Population Growth and Economic Development in Low-Income Countries (Coale and Hoover
1958). In the context of the Cold War battle for the hearts and minds of people
in developing countries, lowering fertility was presented as a means to rapidly
increase living standards, so that they would be won over to the capitalist way.
By 1967, 30 heads of government, including the newly appointed General Soeharto, acting president of Indonesia, had signed a strikingly worded Declaration
on Population:
As Heads of Governments actively concerned with the population problem, we
share these convictions: We believe that the population problem must be recognised as a principal element in long-range national planning if governments are
to achieve their economic goals and fulill the aspirations of their people. We believe that the great majority of parents desire to have the knowledge and the means
to plan their families; that the opportunity to decide the number and spacing of
children is a basic human right. We believe that lasting and meaningful peace will
depend to a considerable measure upon how the challenge of population growth
is met. We believe the objective of family planning is the enrichment of human life,
not its restriction; that family planning, by assuring greater opportunity to each person, frees man to attain his individual dignity and reach his full potential. (Turbay
Ayala and Caradon 1968, 3)
This statement has been the mainstay of population policy in Indonesia since
1967. A vigorous national family-planning program began in Indonesia in the
1970s, and, as I describe later in this article, Indonesia’s fertility rate has more
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The Demography of Indonesia in Comparative Perspective
31
than halved since that time. The centre point of Indonesian population policy has
been, and still is, to reduce the rate of population growth as rapidly as possible by
controlling fertility.
The family-planning approach to development aims to reduce the national
fertility rate to around two births per woman, on average. This level of fertility produces zero population growth in the longer term. In several countries in
Southeast and East Asia, however, fertility has fallen well below two births per
woman, giving rise to concerns about rapid ageing of their populations and the
adequacy of future labour supplies. Japan, Taiwan, the Republic of Korea, and
Singapore have all taken pronatalist stances in a desire to increase their fertility rates (Westley, Choe, and Retherford 2010). Thailand has also moved in this
direction, in its 11th National Economic and Social Development Plan 2012–2016
(NESDB 2012). While the efforts to reduce fertility from high levels to around
two births per woman have been remarkably successful in most cases, attempts
to raise the birth rate from very low levels, both in Europe and in East Asia, have
been largely unsuccessful. In recognition of this, Singapore has recently published
a white paper advocating relatively large-scale immigration in order to slow the
ageing of its population and to meet current and future labour demand (NPTD
2013). As described below, migration to Singapore has run at a very high level in
the past ive to eight years. In demographic terms, immigration can be effective in
offsetting very low fertility in a country with a small population, like Singapore,
but the levels of immigration required to offset very low fertility in large populations, such as those of Japan or Thailand, or possibly in Indonesia in the future,
are not credible. There are also cultural obstacles to large-scale migration—as evidenced, to this point, by Japan. In the context of its very low fertility rate, there is
considerable debate about the appropriateness of China continuing its one-child
policy (Feng, Cai, and Gu 2012).
The spectre of very low fertility is very much on the policy agenda in countries
where fertility has fallen to or is approaching two births per woman. Given the
experience of other Asian countries with longer histories of fertility decline, what
approach should Indonesia be taking to its future level of fertility? Will internal
migration from higher-growth provinces be able to compensate for labour shortages that may arise in low-fertility regions? How rapid is the ageing of Indonesia’s
population and how big an issue is this for policy? Migration to the metropolises
of East Asia has led to the populations of the cities being relatively young while
the rural areas are ageing rapidly. What are the implications of demographic differences in the core and the periphery? Will Indonesia supply labour to countries in the region (and further aield) experiencing labour shortages? This article
addresses these questions in comparative perspective, but irst it gives attention
to uncertainties about the demography of Indonesia—it is dificult to plan for the
future if there is uncertainty about the present.
CONTEMPORARY DEMOGRAPHIC UNCERTAINTY
In contrast with the relatively high level of certainty about Indonesian demographic trends that underpinned development planning in the 1970s and 1980s,
today there is a great deal of uncertainty. This uncertainty, which is hampering
the formulation of new policy initiatives, has arisen for several reasons. Most
important, dificulties associated with the conduct of the 2000 Population Census
32
Peter McDonald
TABLE 1 Intercensal Population Growth in Indonesia, 1971–2010
(%)
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1971–1980
1980–1990
1990–2000
2000–2010
Raw census counts
UN 2010 Revision
UN 2012 Revision
2.30
1.95
1.42
1.41
2.42
2.01
1.46
1.17
2.43
2.05
1.57
1.41
Source: Author’s calculations based on data from BPS (Badan Pusat Statistik) and the United Nations
(UN) Population Division’s World Population Prospects.
of Indonesia affected the results in ways that have not yet been adequately
assessed. The 2000 census was conducted relatively soon after the country moved
to a democratic political system and decentralised management of core-service
delivery (Hull 2001). While the need for data to be available at the district (kabupaten) level of government was expected, the 2000 census was carried out soon
after the 1997–98 Asian inancial crisis. As a result, the ambitious aims of the census extended well beyond the budget capacity to achieve them. Terry Hull has
reported on the deiciencies of the 2000 census:
The resulting data set was seriously lawed in at least two ways. First, shortcomings
in the training and management of interviewers meant that large numbers of people and households were not properly canvassed. It is known that some interviewers simply failed to cover their territories adequately, while others apparently illed
in ictitious material, or copied information from local government family registration data rather than seeking out and interviewing the householders. (Hull 2009)
In addition, enumeration was dificult in certain regions of the country, for reasons of political insecurity. The technology used to scan the paper questionnaires
was also not of suficiently high quality, and the scanning machines often confused digits such as 8, 3, and 5. The relatively low quality of the 2000 census discouraged analysis of its results and thus contributed to a vacuum of demographic
information that extends back at least to the 1990 census. This vacuum has led
to considerable contemporary uncertainty about Indonesia’s demography. Some
assert that Indonesia is now experiencing a new ‘population explosion’ (see discussion below). This assertion is based on intercensal population growth rates
derived from the raw counts of population in the successive censuses, as shown
in the second column of table 1. By these numbers, population growth stopped
falling in Indonesia as far back as 1990 and there has been a slight rise in the
past decade. The implication of this result is that the Indonesian fertility rate has
hardly fallen at all or has risen in the past two decades.
Uncertainty about the trend in the growth rate of the Indonesian population is
evidenced by the substantial changes that were made to the estimated intercensal
growth rates between the 2010 and the 2012 Revisions of World Population Prospects, prepared by the United Nations (UN) Population Division (table 1). Between
June 2011 and June 2013, the UN Population Division switched its viewpoint on
Indonesia’s population growth from a strong and steady downward trend to one
The Demography of Indonesia in Comparative Perspective
33
TABLE 2 Excess of United Nations Population Estimates over Raw Census Counts
(%)
UN 2010 Revision
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1971
1980
1990
2000
2010
1.5
2.6
3.2
3.6
1.1
UN 2012 Revision
–2.2
–1.0
0.0
1.5
1.5
Source: Author’s calculations based on data from BPS (Badan Pusat Statistik) and the United Nations
(UN) Population Division’s World Population Prospects.
that mirrors the trend based on the raw counts. Table 2 compares the raw census counts of population with the UN estimates in the 2010 and 2012 Revisions,
respectively. The UN in its 2012 Revision is implying that the 1971 and 1980 raw
counts overestimated the actual population, while the 1990 raw count was the
same as the UN estimates in the 2012 Revision. The extent of the undercount is
then considered to be the same in the carefully taken 2010 census (Hull 2010) as it
was in the poorly taken 2000 census. The logic of the changes in the UN estimates
is somewhat mystifying, which underlines the need for an intensive investigation of Indonesia’s demography from 1970 to 2010.1 Varying estimates continue to
appear with the new oficial population projections showing the estimated population of Indonesia in 2000 to be 205.1 million, lower than the census count and
almost four million lower than the latest UN estimate for 2000 (BPS 2014).
To add to the argument of uncertainty, as described in appendix 1, the recorded
population growth rates based on raw counts for many of the provinces of Indonesia over the past three decades (1980–90, 1990–2000, and 2000–2010) display
trajectories that challenge plausibility. For example, several provinces show a pattern in which the growth rates in 1990–2000 were considerably lower than those
in 1980–90 and 2000–2010.2
Uncertainty applies not only to the population total but also to some of its characteristics. From the results of the 2010 post-enumeration survey (PES), 20% of
the population had inconsistent ages reported between the census and the PES
and 35% had inconsistent levels of education. Marital status was inconsistently
reported for 10% of the population (BPS 2011a).
As discussed below, uncertainty about population growth in Indonesia is
founded on poor measurement of the components of its population change:
1. Such an intensive investigation will be undertaken through an Australian Research
Council Linkage Project grant awarded to researchers at The Australian National University and The University of Adelaide, in association with the Australian Government Department of Foreign Affairs and Trade, the United Nations Population Fund in Indonesia, BPS,
and Indonesia’s National Family Planning Coordination Agency (Badan Kependudukan
dan Keluarga Berencana Nasional).
2. West Sumatra, Jambi, Lampung, DKI Jakarta, DI Yogyakarta, South Kalimantan, East
Kalimantan, Southeast Sulawesi, Maluku, and West Papua.
34
Peter McDonald
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fertility and mortality rates and net international migration. Indonesia has failed
to develop reliable ways of measuring these components of change. Along with
the current age structure, these components of change are the determinants of
past and future population growth.
INDONESIA’S DEMOGRAPHY IN COMPARATIVE PERSPECTIVE
To place Indonesia in comparative perspective, I use demographic data provided
by the UN Population Division in its 2012 Revision.3 I compare Indonesia with
12 other countries in the Asia-Paciic region: Iran, India, Bangladesh, Myanmar
(Burma), Singapore, Malaysia, Thailand, Vietnam, China, Japan, the Philippines,
and Australia. This group includes all the major countries of Southeast Asia, as
well as China, India, and Iran as countries with large populations in Asia. It also
includes Japan, Singapore, and Australia as regional developed-country comparators. As shall be seen, the conventional wisdom that developing countries have
high rates of population growth and developed countries have low rates is not
borne out by this regional comparison.
Population Size
The irst and most obvious point to make is that Indonesia’s population is very
large, by now the fourth largest in the world. While population size tells us little about economic or social development, McNicoll (1999) and others (Jackson
and Howe 2008) argue that population size matters more and more as the economic disparities between countries become less divergent. Conventional military power also depends on how many soldiers a country has in its army, given
the increasing capacity to arm those soldiers relatively cheaply. Writing in 1999,
McNicoll said that Indonesia ‘is likely to retain an effectively heavyweight if not
hegemonic role in Southeast Asia’, very largely because of its population size
(McNicoll 1999, 423).
Conversely, any positive rate of growth applied to a very large population generates a very large number of additional people. This consideration has inluenced
the minds of policymakers in Indonesia for decades. Today, in Indonesia, there is
considerable concern in many circles that current population growth constitutes
a ‘population explosion’ (ledakan penduduk) that has negative implications for
almost every aspect of life.4 The concern has been expressed most signiicantly by
Sonny Harmadi, director of the Demographic Institute of the University of Indonesia (for one example, see Harmadi, ‘Pesan Kependudukan 2011’ (Kompas, 11
Jan 2011). Harmadi was expressing concern about a population explosion before
the release of the 2010 census count and, using raw rates similar to those shown
in the second column of table 1, he conirmed his fear after the census results
became available. His concerns have been mirrored by other luminaries such as
3. This is not to say that I endorse the estimates made by this organisation for Indonesia.
Indeed, prior to more intensive analysis, I ind the UN estimates over time to be very confusing. However, the 2012 Revision revised the UN’s prior estimates substantially for other
countries besides Indonesia. Thus, in the interests of maintaining cross-national consistency, I have used the estimates from the 2012 Revision.
4. This concern is immediately evident from an online search of ‘ledakan penduduk’.
The Demography of Indonesia in Comparative Perspective
35
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the then head of the Coordinating Board for National Family Planning (Badan
Koordinasi Keluarga Berencana Nasional [BKKBN]) Sugiri Syarief (Antara News,
25 Nov 2011) and presidential candidate Prabowo Subianto (Tribunnews.com, 30
May 2013).
Rates of Population Growth
In policy terms, the important issue is not so much the current level of Indonesia’s population growth as its trend. If the aim is to reduce population growth to
zero, the UN 2010 Revision data for Indonesia are evidence providing support
for more of the same policy approach; the raw data and the UN 2012 Revision
data are evidence calling for a radical change in policy. My own sense, subject to
revision after more intensive investigation, is that the Indonesian fertility decline
may have been exaggerated in the decades prior to 2000. The population growth
rate has probably been falling consistently, but with levels of growth higher than
those shown in table 1.
Figures 1 and 2 show Indonesia’s rate of population growth (based on UN 2012
Revision data) in comparison with those of 12 other countries of the region for
two periods of time. In 1970–75, the nine developing countries conirmed their
expected pattern of high rates of growth (above 2% per annum) while the three
more developed countries (Japan, Australia, and Singapore) had the lowest rates.
At 2.5%, Indonesia had the ifth highest rate. By 2005–10, Indonesia had the sixth
highest rate, 1.4%, but only because two of the developed countries, Singapore
and Australia, had jumped from the low end to the high end. Both these countries
were by then supporting higher population growth through large-scale migration
programs (igure 4). Both were also producing their own form of ‘demographic
dividend’ by importing workers directly into the younger working-age groups.
Indonesia’s 2005–10 growth rate was a little higher than that of Iran, a country in which recent policy debate has focused on whether the birth rate should
be stimulated (Abbasi-Shavazi, pers. comm.). Iran fears that its fertility is falling
below replacement levels and that it will experience the anguish about very low
fertility now expressed in countries such as Japan, South Korea, Singapore, and
Thailand. There is no such concern in Indonesia, despite the apparent similarity
of current population growth rates.5
Figure 4 shows the breakdown of recent population growth in the selected countries into net migration and natural increase. Most noticeable is Singapore’s very
high net migration rate of 1.9% per annum. Australia also has a high net migration rate of more than 1% per annum. The UN estimates that net international
migration for all the other countries is very small in relative terms. For Indonesia,
a net outmigration of 148,000 persons per annum is estimated for 2005–10, but
this may well be an underestimate. Hugo (2009), citing Ananta and Ariin (2008),
5. The UN projects Indonesia’s and Iran’s rates of population growth to be similarly positive in 2030–35 (igure 3). Indonesia’s rate of 0.66% per annum implies an increase of population at that time of almost two million people per annum. The 2030–35 projected population growth rates show that large countries like India, Bangladesh, and the Philippines
would still have quite high rates of growth. At the other extreme, Thailand, Japan, and
China will have relatively large negative rates of growth, which is highly concerning now
at least to Japan and Thailand and, predictably, to China at some future point.
FIGURE 1 Annual Rate of Population Growth, Selected Countries, 1970–75
(%)
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Philippines
Thailand
Iran
Bangladesh
Indonesia
Malaysia
Myanmar (Burma)
China
India
Vietnam
Singapore
Australia
Japan
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
FIGURE 2 Annual Rate of Population Growth, Selected Countries, 2005–10
(%)
Singapore
Australia
Malaysia
Philippines
India
Indonesia
Iran
Bangladesh
Vietnam
Myanmar (Burma)
China
Thailand
Japan
0.0
0.5
1.0
1.5
2.0
2.5
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
3.0
FIGURE 3 Annual Rate of Population Growth, Selected Countries, 2030–35
(%)
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Philippines
Australia
Malaysia
Indonesia
India
Bangladesh
Iran
Singapore
Vietnam
Myanmar (Burma)
China
Thailand
Japan
–0.5
0.0
0.5
1.0
1.5
2.0
2.5
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
FIGURE 4 Annual Rates of Net Migration and Natural Increase,
Selected Countries, 2005–10
(%)
Malaysia
Philippines
India
Indonesia
Iran
Bangladesh
Vietnam
Myanmar (Burma)
Australia
China
Singapore
Thailand
Japan
–0.5
Net migration
0.0
0.5
1.0
1.5
Natural increase
2.0
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
2.5
38
Peter McDonald
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states that there were 2.7 million documented migrants from Indonesia in other
countries, in addition to large numbers of undocumented migrants. In contrast,
if most of these migrants are temporary contract workers who will eventually
return to Indonesia, which seems to be the case, this would be consistent with low
net migration.
Age Distributions
Associations between economic development and demography are based most
often on the nature of the age distribution of the population—in particular, on
the balance between those of working age and those in the younger and older
dependent ages. Countries with high birth rates have relatively large numbers of
young dependents; countries with low birth rates, in time, have relatively large
numbers of old dependents. This section discusses Indonesia’s age distribution
in comparative perspective. Comparison is made with Thailand, in particular,
because it has recently moved to implement pronatalist policies, whereas debate
in Indonesia is concerned with policies to address a perceived births-led population explosion; yet both countries had similar age distributions around 1970, and
both have experienced substantial fertility declines.
In 1970, 43% of Indonesia’s population was aged 15 and under, compared with
44% of Thailand’s (igures 5 and 6). Thailand’s rate of population growth at the
time was a little higher (igure 1), because its fertility rate was higher. But, since
then, Thailand’s rate of growth (and its fertility) has fallen faster than that of Indonesia. The varying speeds of decline have had differing effects on the age structures of the two countries (igures 5 and 6) and important implications for policy.
The Thai age pyramid in 2010 is undercut at the younger ages; the largest iveyear age group is those aged 35–39. As the large cohort aged 30–49 in 2010 has
passed through the working ages, it has, in theory, generated the demographic
dividend in a classic form, because the numbers have been smaller at the younger
and older ages. As this age group moves into the older ages, also in classic fashion, the population will age considerably and population ageing will emerge as
a central issue of population policy. The UN projects that the percentage of the
population aged 65 and over in Thailand will increase from 9% in 2010 to 23% in
2050, a higher level than is projected for Australia in 2050 (igure 7). In Australia,
migrants and their subsequent births, along with a relatively high birth rate, are
projected to keep the population at the young end of the spectrum of developed
countries (McDonald and Temple 2010). In 2012, the Thai government shifted its
policy agenda to one that is similar in form to those of many countries in Europe
and East Asia, where fertility rates are very low (NESDB 2012). The policy proposals include pronatalist inancial measures (such as lower taxes for those with
more children) and family-friendly workplace policies, including lexible working hours, paid parental leave, and childcare.
The new Thai agenda also promotes policies for older people, including incentives to continue working rather than to retire, tax incentives for self-support
through personal savings, the development of a national income support scheme
for the aged, systems and incentives for the support of older people by their families, and better health and welfare infrastructure. The Thai government’s policy
document also focuses on improving the productivity of the economy through
higher human capital and higher multifactor productivity. The simple argument
is that a richer country, one with high GDP per capita, will be in a better position
FIGURE 5 Age Distributions of Indonesia, 1970, 2010, and 2050
(population in millions)
1970
Males
Females
85+
80–84
75–79
2010 and 2050
55–59
50–54
45–49
40–44
35–39
30–34
25–29
20–24
15–19
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
14
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
14
10–14
5–9
0–4
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
Note: The projected age distribution for 2050 is represented by the dashed lines.
FIGURE 6 Age Distributions of Thailand, 1970 and 2010
(population in millions)
1970
Males
Females
85+
80–84
75–79
2010
70–74
65–69
60–64
55–59
50–54
45–49
40–44
35–39
30–34
25–29
20–24
15–19
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
4
3
2
1
0
-1
-2
-3
-4
4
3
2
1
0
-1
-2
-3
10–14
5–9
0–4
-4
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70–74
65–69
60–64
40
Peter McDonald
FIGURE 7 Share of Population Aged 65 and Over, Selected Countries, 2010 and 2050
(%)
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Japan
Singapore
China
Thailand
Australia
Vietnam
Iran
Indonesia
Myanmar (Burma)
Malaysia
Bangladesh
India
Philippines
0
2010
2050
5
10
15
20
25
30
35
40
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
to support its aged population (see Lutz and K. C. [2013] for an exposition of this
argument).
Population ageing will occur much more slowly in Indonesia. Owing to a
slower decline in fertility between 1970 and 2010 than was the case in Thailand,
Indonesia’s age pyramid in 2010 is not as undercut: the largest age group is the
youngest (those aged 0–4), and the size of this group may well be understated. By
2010, 30% of Indonesia’s population was aged 15 and under, compared with 19%
of Thailand’s. According to the UN projections, the percentage aged 15 and under
in Indonesia in 2050 will be 20%, still higher than the Thai percentage in 2010.
Having more time to adjust to an ageing population could be an advantage
for Indonesia. Figure 7 provides one view of the country’s demographic future.
It shows a projection of Indonesia’s present population and age structure to 2050,
based on the assumption that the fertility rate will fall to 2.1 births per woman by
2015. The result shows substantial population ageing by 2050; but the age structure remains relatively lat-sided, and the population growth rate at that time
would be approximately zero. By this projection, the total population of Indonesia in 2050 would be 323 million. The policy question for Indonesia is whether a
slow movement to zero population growth would provide better outcomes than
the pathway that Thailand is on, despite the ultimately large population size of
Indonesia. Should a country trade a larger population size for a more sustainable
longer-term age structure? The policy approaches being taken by countries facing
population decline and very rapid ageing suggest that they would prefer to trade
a somewhat higher population size for an age structure that was more amenable
to economic and social policy.
The projection in igure 5 is only one potential pathway for Indonesia. Some
would argue that Indonesia could attain low fertility and then face problems
similar to those of Thailand. Others would argue that Indonesia’s future may look
more like India’s, in which only 14% of the population would be aged 65 and over
in 2050 (igure 7). My own sense is that ageing in Indonesia will occur slowly, and
The Demography of Indonesia in Comparative Perspective
41
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that Indonesia’s fertility is very unlikely to be below 1.5 births per woman in the
foreseeable future, if ever. Nevertheless, the demographic future of Indonesia is
inherently uncertain and, because of poor data measurement and a lack of accuracy about the prevailing levels of fertility and mortality, more uncertain than for
other comparator countries. Demographic futures are important in areas of planning with long lead times, such as large-scale infrastructure and education and
health services.
Fertility
Fertility in Indonesia is estimated directly and indirectly. Direct estimates are
obtained from the results of the infrequent Indonesian Demographic and Health
Survey (IDHS). Indirect estimates are obtained every 10 years from the census
results, by using the own-children method, which links children in a household
to their mothers and produces a table showing the ages of children by the ages of
their mothers (see Abbasi-Shavazi [1997] for an evaluation of the method).
The census-based own-children method is not robust to under-enumeration in
the census of the number of children (for example, those aged 0–4) relative to the
number of women of childbearing age, and this may be a considerable problem in
Indonesia.6 In countries with relatively good vital registration data, such as India
and Iran, the own-children estimates of fertility are lower than those based on
birth registration data.
In the IDHS, a sample of women is asked to report the details of all their pregnancies, which makes it possible to calculate fertility directly from the number
of births reported by the women surveyed. The accuracy of the result depends
on whether the sample truly represents the population. In the last two IDHS collections, in 2007 and 2012, the age-speciic proportions of married women were
much higher than those recorded in other data collections, such as Susenas and
the 2000 and 2010 censuses. In other words, there is strong evidence that the IDHS
tends to miss women who are not married. Single women have few children, so
the fertility rates from the IDHS tend to be too high (assuming that the number of
births is accurately reported).7
In summary, the census-based own-children estimates of fertility are likely to
underestimate fertility in Indonesia, whereas the IDHS is likely to overestimate it.
IDHS estimates suggest that Indonesian fertility rates have hardly changed since
the mid-1980s, and that the decline has stalled at around 2.6 births per woman
(Hull and Hartanto 2009; Hull pers. comm.). By the own-children estimates from
the censuses, fertility fell to around 2.3 births in the late 1990s, but rose slightly to
about 2.4 births in the latter years of the 2000s (BPS 2011b).
6. For example, if we estimate the population aged 0–4 at the time of the 2000 census by
reverse surviving the population aged 10–14 at the 2010 census, this estimate is approximately 12% higher than that recorded in 2000. The own-children estimate of the total fertility rate from the 2000 census was 2.27 births per woman, but with a 12% correction it
would have been 2.54. This is a large variation to consider when trying to measure the
trend in fertility.
7. The 2007 IDHS estimated the total fertility rate to be 2.57 in 2002–3, and the 2012 IDHS
estimated it to be 2.60 in 2007–8. If the IDHS proportions married by age are adjusted to
those obtained in the 2000 and 2010 censuses, the IDHS estimates of fertility for these years
fall respectively to 2.35 and 2.20 (Hull and Hartanto 2009; Hull pers. comm.).
42
Peter McDonald
FIGURE 8 Total Fertility Rates, Selected Asian Countries, 1970, 1985, 1995, and 2010
(births per woman)
Philippines
Indonesia
India
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Malaysia
Bangladesh
Vietnam
Myanmar (Burma)
Australia
Iran
China
Thailand
1970
1985
1995
2010
Japan
Singapore
0
1
2
3
4
5
6
7
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
The argument has been made that Indonesia’s family-planning program has
been disrupted by decentralisation (Habsjah 2009; Hull and Hartanto 2009), and
that this is why fertility has remained constant for a long period (as shown by
the IDHS estimates). This argument has also been used to justify a rise in fertility, using own-children estimates, between the 2000 and 2010 censuses. It has
also been suggested that democracy has stimulated a shift to a more conservative
(Islamic) society, and that this shift has stimulated the birth rate. On the other side,
fertility has fallen sharply in almost all other Islamic countries, and sharp rises in
education and urbanisation are very likely to have pushed the Indonesian fertility
rate downwards. The age pattern of fertility also shifts to older ages between the
own-children estimates of 2000 and 2010 (BPS 2011b). This kind of shift in the age
pattern of fertility is usually associated with a fall in the fertility rate.
For comparative purposes, igure 8 uses the estimates provided by the UN Population Division (2012 Revision). The estimates show Indonesia’s fertility level
drifting up in rank from the ninth highest among the 13 countries around 1970 to
the second highest around 2010. The UN estimates are more in keeping with the
IDHS estimates than with the census-based estimates, despite the criticisms that
have been made of the IDHS estimates. As a consequence, Indonesia’s fertility
around 2010 is estimated to be above that of India, Malaysia, and Bangladesh.
Iran has the largest downward movement, from 7.0 births per woman in 1985 to
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The Demography of Indonesia in Comparative Perspective
43
1.85 in 2010 (see Abbasi-Shavazi, McDonald, and Hosseini-Chavoshi 2009). The
UN estimates that the fertility rates of China and Thailand have now fallen into
the ‘very low’ range, under 1.5 births per woman. The Philippines, not unexpectedly, has the highest fertility rate, and there are those who argue, in keeping with
the demographic-dividend theory, that high fertility has been an obstacle to economic growth in that country.
The latest UN estimates of fertility for Indonesia question the conventional
wisdom of rapidly declining fertility. They indicate that the Indonesian government may need to take stronger action in addressing the country’s stalling decline
in fertility. Yet if the UN estimates are too high, as some would argue they are,
an overly vigorous approach to fertility reduction may push Indonesian fertility
rates in the direction of ‘very low’ fertility—which is also not desirable. The ideal
outcome for Indonesia is to have fertility fall to around two births per woman
and then be sustained at that level. The countries that have achieved this (without
fertility falling to very low levels) have accepted that couples may have more than
two children, and have also provided support for families with children.
Mortality
While there is uncertainty about the level of fertility in Indonesia, there is no reliable information about mortality for people over the age of ive. Planners need
accurate information on adult mortality, both to project the numbers at older
ages and to plan aged-related services. This section shows that a change in the
method of measurement could transform Indonesia from one of the best performers among the comparator countries in reducing mortality to one of the worst.
The conventional way of measuring adult mortality in Indonesia is to associate a model life table—most commonly that of Coale and Demeny’s (1966) West
model—with the estimate of child mortality (mortality below age ive) to obtain
estimates of mortality at all other ages and life expectancy at birth. The West
model life tables are based very largely on the mortality experience in Europe,
Australia, and New Zealand in the 19th century, and questions remain about their
appropriateness to countries like Indonesia in the 21st century because the regime
of causes of death and the state of medical knowledge are very different in today’s
developing countries compared with 19th-century Western experience.
Child mortality in Indonesia is most commonly estimated by using data on the
number of live births that women have had and the number of those live births
that are still alive at the time of the census or the survey, according to the women’s
ages at the time of the survey. The methodology dates back to the 1960s and was
designed to measure child mortality in situations where mortality is very high—
say, around 200 deaths under the age of ive from 1,000 live births—and where
childbearing begins at a young age. When child mortality falls to a much lower
level and childbearing begins at older ages, as is the case in Indonesia today, this
method is not robust enough to measure the much smaller movements in child
mortality.8 Applying this method to 2010 census data, Statistics Indonesia (Badan
Pusat Statistik [BPS]) estimated the rate of child mortality to have been 30 deaths
per 1,000 births in 2006 (BPS 2011c). Another method of estimation, used in the
8. If the age distribution of mothers at the time of birth were to be older than the distribution assumed in the model, the level of child mortality would tend to be underestimated.
44
Peter McDonald
FIGURE 9 Life Expectancy at Birth, Selected Countries, 1970–75 and 2005–10
(years)
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Japan
Australia
Singapore
Vietnam
China
Malaysia
Thailand
Iran
Indonesia
Bangladesh
Philippines
India
Myanmar (Burma)
0
1970–75
2005–10
10
20
30
40
50
60
70
80
90
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
IDHS, involves asking women about the dates of birth and death (if applicable)
of each of their children. Such data can be used to make direct estimates of child
mortality. This method, however, tends to underestimate child mortality because
the birth and death of children who died shortly after birth are often not reported.
The most recent survey shows a child mortality rate, based on this method, of
32 deaths per 1,000 live births during 2008–12 (BPS et al. 2012). This estimate is
largely consistent with that of the 2010 census, but both may be consistently low.9
In its 2012 Revision, the UN Population Division estimated life expectancy in
Indonesia in 2005–10 to be 69.6 years (igure 9). This is consistent with the estimate
for 2006 (70.7 years) published by BPS (2011c). However, Muhidin and Nasrun’s
(2012) estimate of 60.8 years from the 2010 census, which also refers to about 2006,
is a very different result.10 These contrasting estimates show that the level of mortality in Indonesia is highly speculative, and much more so than the fertility rate.
Figure 9 shows that Indonesia’s life expectancy, at 60.8 years, would easily be the
lowest among the comparator countries, the lowest of which is currently Myanmar (Burma), at 64.2 years. Much consideration needs to be given to improving
the estimation of mortality in Indonesia.
Population Distribution and Internal Migration
The movement of population from densely settled Java to other islands is a policy
approach that originated in the Dutch colonial period, and the idea of population
9. There is little consistency at the provincial level between the census-based estimates and
the IDHS estimates—the former appears to be particularly low in the eastern provinces.
10. Muhidin and Nasrun (2012) also use West model life tables, but they include an analysis of the change in age cohort sizes between the 2000 and 2010 censuses (the intercensal
survival method).
The Demography of Indonesia in Comparative Perspective
45
TABLE 3 Growth of the Regions of Indonesia, 1971–2010
(ratio of population, 2010 to 1971)
Java
Kalimantan
Sulawesi
1.80
2.68
2.04
Sumatra
Remainder
Indonesia
2.43
2.23
1.99
Source: Author’s calculations based on data from BPS.
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TABLE 4 Net Migration, Provinces of Java, 2005–10
Banten
Central Java
DI Yogyakarta
DKI Jakarta
272,000
–678,000
124,000
–239,000
East Java
West Java
Java
–285,000
453,000
–354,000
Source: BPS (2011d).
redistribution is embedded in the minds of most Indonesians at primary school.
In addition, fertility fell earlier and further in the provinces of Java than in those
outside Java. For these reasons, we would expect a redistribution of population
away from Java. Yet urban economic development has been concentrated in Java’s
largest cities, which have grown substantially. The once-wide boundaries of DKI
Jakarta long ago became inadequate to contain the city’s growth, and Jakarta now
abuts on the neighbouring cities of Depok, Bekasi, and Tangerang. This section
considers the extent to which the redistribution of population from Java to the
outer islands is taking place today.
The net effect of these demographic trends is that Java has grown a lot more
slowly than all the other regions of Indonesia. The fastest growing region has
been Kalimantan; East Kalimantan’s population increased almost ive times
during 1971–2010 (table 3). Growth within Java is quite diverse, with West Java
(including Banten) increasing 2.5 times but Central and East Java each increasing
only 1.5 times. The high growth rate of West Java relects Jakarta’s spreading into
that province.
The slower growth of Java, at least in recent years, owes little to outmigration from Java. Table 4 shows that net migration from Java during 2005–2010
amounted to only 354,000, or just 71,000 per annum, a number that is trivial compared with the total population of the island (BPS 2011d). The table also shows
that DKI Jakarta, which has experienced net outmigration since the late 1980s,
recorded negative net migration of 239,000 in this period, as people moved out of
the province to housing estates in the areas of West Java and Banten contiguous
with DKI Jakarta. The even larger in-migration to West Java and Banten shown
in table 4 can also be attributed to the growth of the megacity of Jakarta. Central
Java is the largest source of out-migrants, with a net loss of 136,000 per annum in
the ive years before the 2010 census.
The dificulty of deining city boundaries hinders cross-country comparisons
of cities and their growth. For example, the UN Population Division recorded the
population of the urban agglomeration of Jakarta in 2010 to be 9.6 million, which
46
Peter McDonald
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FIGURE 10 Share of Population Living in Urban Areas, Selected Countries,
1970, 2010, and 2030
(%)
Singapore
Australia
Malaysia
Iran
Japan
China
Philippines
Indonesia
Myanmar (Burma)
Thailand
Vietnam
Bangladesh
India
0
1970
2010
2030
10
20
30
40
50
60
70
80
90
100
Source: United Nations Population Division, World Urbanization Prospects: The 2011 Revision.
is precisely the population recorded for the province at the 2010 census. Yet it is
accepted that the city has now sprawled into West Java and Bantan, and that its
real urban agglomeration is considerably larger.11
Deinitions of rural and urban areas are also notoriously inconsistent across
countries. Glossing over this problem, igure 10 shows that urbanisation has been
a very powerful force in Indonesia since 1970. Yet in 2010, the urban population
remained below 50% of the total population (a higher proportion than in ive
of the comparator countries: Myanmar [Burma], Thailand, Vietnam, Bangladesh,
and India). The World Bank has recently argued that urban agglomerations provide major advantages for development, and that Indonesia’s relatively high
level of urbanisation may present it with considerable opportunities to increase
productivity (World Bank 2013). However, the UN’s projections of urbanisation
suggest that the growth of the urban segment will be slow in all the developing
countries shown in igure 10. In Indonesia, for example, the urban proportion is
projected to increase from 44% to just 54% in the next 20 years. This slow rate of
urbanisation does not seem to be in keeping with the increases in education that
will take place in this period. The UN projections also do not take into account the
results of the 2010 Indonesian census, whic
ISSN: 0007-4918 (Print) 1472-7234 (Online) Journal homepage: http://www.tandfonline.com/loi/cbie20
The Demography of Indonesia in Comparative
Perspective
Peter McDonald
To cite this article: Peter McDonald (2014) The Demography of Indonesia in
Comparative Perspective, Bulletin of Indonesian Economic Studies, 50:1, 29-52, DOI:
10.1080/00074918.2014.896236
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Date: 17 January 2016, At: 23:24
Bulletin of Indonesian Economic Studies, Vol. 50, No. 1, 2014: 29–52
THE DEMOGRAPHY OF INDONESIA IN
COMPARATIVE PERSPECTIVE
Peter McDonald
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The Australian National University
Having reduced its fertility rate over the past 40 years, Indonesia has reached a
new demographic crossroad. Its fertility rate is now around 2.5 births per woman,
which, if sustained, would add substantial numbers to Indonesia’s population in
the future. There are concerns within Indonesia that the present level of population
growth is an obstacle to continued economic development and, accordingly, that
fertility should be reduced to the replacement level of 2.1 births per woman as soon
as possible. Yet a comparative perspective indicates that countries such as Singapore, Japan, and Thailand are concerned about the effects that their very low rates
of fertility are having on their labour forces and their rates of population ageing.
This article suggests that with the right policy settings Indonesia can avoid this outcome yet continue to reduce its fertility. It discusses the implications of Indonesia’s
population growth and distribution for its economy, as well as the poor quality of
demographic data.
Keywords: population growth, age structure, urbanisation, fertility, mortality, population
and development
JEL classiication: J11, J21, J61, O15
INTRODUCTION
Reducing the rate of population growth by reducing the fertility rate has been a
central component of Indonesia’s development planning agenda since the late
1960s. This has also been the position of most comparator countries in Southeast
Asia and East Asia. In effect, the aim has been to reduce the fertility rate to around
two births per woman. Today that aim is close to being achieved in Indonesia,
and in some provinces the fertility rate has fallen below this level. Indonesia’s
population will continue to grow, however, because of ‘population momentum’,
in which future population growth is driven by increasingly higher numbers of
women in the reproductive ages and, hence, by more births than deaths.
One of the main justiications for the introduction in the 1960s and 1970s of
policies to reduce fertility in developing countries was that in the 20 to 40 years
following the fall in fertility, the age distribution of the population would concentrate in the working ages. Without the economic burden of large numbers of
children and large family sizes, nations and families alike could apply capital to
productive investment rather than to consumption, resulting in higher GDP per
capita. In the interim, the smaller numbers of children would mean that a greater
ISSN 0007-4918 print/ISSN 1472-7234 online/14/00029-24
http://dx.doi.org/10.1080/00074918.2014.896236
© 2014 Indonesia Project ANU
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30
Peter McDonald
level of expenditure could be applied to the education of each child (Jones 1971).
Over time, the country would experience a leap forward in human capital as the
next, smaller generation was educated to higher levels. Universal primary education was an associated feature of these policies. Today this approach is referred
to as the ‘demographic dividend’ or ‘demographic bonus’. It has been argued
that the demographic dividend was a central component of the economic successes in countries such as Japan, South Korea, Taiwan, and Singapore (Bloom
and Williamson 1998; Kinugasa 2013). Its logic was also part of the rationale for
China’s adoption of the one-child policy. Deng Xiaoping was a major sponsor of
the one-child policy, based on his expressed view that China would not be able
to develop its economy or raise the living standards of its people unless the birth
rate fell rapidly (Potts 2006). There is also a reasonable argument that the contrasting economic development pathways of Thailand, Indonesia, and the Philippines
over the past 40 years have been associated with the relative timing and extent of
the decline in fertility in these countries.
The use of fertility reduction as a policy approach to development arose out
of the Cold War. In the years immediately after the Second World War, American demographers such as Frank Notestein and Ansley Coale were able to convince the US government that declining fertility was a necessary prerequisite for
economic development. This was something of a reversal of the previous theoretical position, demographic transition theory, by which fertility fell only as a
consequence of development (Szreter 1993). Demographic transition theory had
strong theoretical underpinnings. In contrast, the view that fertility could fall
prior to economic development was based not so much on a theory of how this
might occur as on the consequences if it did occur. More than any other source,
the evidence for this consequential argument was provided by the book Population Growth and Economic Development in Low-Income Countries (Coale and Hoover
1958). In the context of the Cold War battle for the hearts and minds of people
in developing countries, lowering fertility was presented as a means to rapidly
increase living standards, so that they would be won over to the capitalist way.
By 1967, 30 heads of government, including the newly appointed General Soeharto, acting president of Indonesia, had signed a strikingly worded Declaration
on Population:
As Heads of Governments actively concerned with the population problem, we
share these convictions: We believe that the population problem must be recognised as a principal element in long-range national planning if governments are
to achieve their economic goals and fulill the aspirations of their people. We believe that the great majority of parents desire to have the knowledge and the means
to plan their families; that the opportunity to decide the number and spacing of
children is a basic human right. We believe that lasting and meaningful peace will
depend to a considerable measure upon how the challenge of population growth
is met. We believe the objective of family planning is the enrichment of human life,
not its restriction; that family planning, by assuring greater opportunity to each person, frees man to attain his individual dignity and reach his full potential. (Turbay
Ayala and Caradon 1968, 3)
This statement has been the mainstay of population policy in Indonesia since
1967. A vigorous national family-planning program began in Indonesia in the
1970s, and, as I describe later in this article, Indonesia’s fertility rate has more
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The Demography of Indonesia in Comparative Perspective
31
than halved since that time. The centre point of Indonesian population policy has
been, and still is, to reduce the rate of population growth as rapidly as possible by
controlling fertility.
The family-planning approach to development aims to reduce the national
fertility rate to around two births per woman, on average. This level of fertility produces zero population growth in the longer term. In several countries in
Southeast and East Asia, however, fertility has fallen well below two births per
woman, giving rise to concerns about rapid ageing of their populations and the
adequacy of future labour supplies. Japan, Taiwan, the Republic of Korea, and
Singapore have all taken pronatalist stances in a desire to increase their fertility rates (Westley, Choe, and Retherford 2010). Thailand has also moved in this
direction, in its 11th National Economic and Social Development Plan 2012–2016
(NESDB 2012). While the efforts to reduce fertility from high levels to around
two births per woman have been remarkably successful in most cases, attempts
to raise the birth rate from very low levels, both in Europe and in East Asia, have
been largely unsuccessful. In recognition of this, Singapore has recently published
a white paper advocating relatively large-scale immigration in order to slow the
ageing of its population and to meet current and future labour demand (NPTD
2013). As described below, migration to Singapore has run at a very high level in
the past ive to eight years. In demographic terms, immigration can be effective in
offsetting very low fertility in a country with a small population, like Singapore,
but the levels of immigration required to offset very low fertility in large populations, such as those of Japan or Thailand, or possibly in Indonesia in the future,
are not credible. There are also cultural obstacles to large-scale migration—as evidenced, to this point, by Japan. In the context of its very low fertility rate, there is
considerable debate about the appropriateness of China continuing its one-child
policy (Feng, Cai, and Gu 2012).
The spectre of very low fertility is very much on the policy agenda in countries
where fertility has fallen to or is approaching two births per woman. Given the
experience of other Asian countries with longer histories of fertility decline, what
approach should Indonesia be taking to its future level of fertility? Will internal
migration from higher-growth provinces be able to compensate for labour shortages that may arise in low-fertility regions? How rapid is the ageing of Indonesia’s
population and how big an issue is this for policy? Migration to the metropolises
of East Asia has led to the populations of the cities being relatively young while
the rural areas are ageing rapidly. What are the implications of demographic differences in the core and the periphery? Will Indonesia supply labour to countries in the region (and further aield) experiencing labour shortages? This article
addresses these questions in comparative perspective, but irst it gives attention
to uncertainties about the demography of Indonesia—it is dificult to plan for the
future if there is uncertainty about the present.
CONTEMPORARY DEMOGRAPHIC UNCERTAINTY
In contrast with the relatively high level of certainty about Indonesian demographic trends that underpinned development planning in the 1970s and 1980s,
today there is a great deal of uncertainty. This uncertainty, which is hampering
the formulation of new policy initiatives, has arisen for several reasons. Most
important, dificulties associated with the conduct of the 2000 Population Census
32
Peter McDonald
TABLE 1 Intercensal Population Growth in Indonesia, 1971–2010
(%)
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1971–1980
1980–1990
1990–2000
2000–2010
Raw census counts
UN 2010 Revision
UN 2012 Revision
2.30
1.95
1.42
1.41
2.42
2.01
1.46
1.17
2.43
2.05
1.57
1.41
Source: Author’s calculations based on data from BPS (Badan Pusat Statistik) and the United Nations
(UN) Population Division’s World Population Prospects.
of Indonesia affected the results in ways that have not yet been adequately
assessed. The 2000 census was conducted relatively soon after the country moved
to a democratic political system and decentralised management of core-service
delivery (Hull 2001). While the need for data to be available at the district (kabupaten) level of government was expected, the 2000 census was carried out soon
after the 1997–98 Asian inancial crisis. As a result, the ambitious aims of the census extended well beyond the budget capacity to achieve them. Terry Hull has
reported on the deiciencies of the 2000 census:
The resulting data set was seriously lawed in at least two ways. First, shortcomings
in the training and management of interviewers meant that large numbers of people and households were not properly canvassed. It is known that some interviewers simply failed to cover their territories adequately, while others apparently illed
in ictitious material, or copied information from local government family registration data rather than seeking out and interviewing the householders. (Hull 2009)
In addition, enumeration was dificult in certain regions of the country, for reasons of political insecurity. The technology used to scan the paper questionnaires
was also not of suficiently high quality, and the scanning machines often confused digits such as 8, 3, and 5. The relatively low quality of the 2000 census discouraged analysis of its results and thus contributed to a vacuum of demographic
information that extends back at least to the 1990 census. This vacuum has led
to considerable contemporary uncertainty about Indonesia’s demography. Some
assert that Indonesia is now experiencing a new ‘population explosion’ (see discussion below). This assertion is based on intercensal population growth rates
derived from the raw counts of population in the successive censuses, as shown
in the second column of table 1. By these numbers, population growth stopped
falling in Indonesia as far back as 1990 and there has been a slight rise in the
past decade. The implication of this result is that the Indonesian fertility rate has
hardly fallen at all or has risen in the past two decades.
Uncertainty about the trend in the growth rate of the Indonesian population is
evidenced by the substantial changes that were made to the estimated intercensal
growth rates between the 2010 and the 2012 Revisions of World Population Prospects, prepared by the United Nations (UN) Population Division (table 1). Between
June 2011 and June 2013, the UN Population Division switched its viewpoint on
Indonesia’s population growth from a strong and steady downward trend to one
The Demography of Indonesia in Comparative Perspective
33
TABLE 2 Excess of United Nations Population Estimates over Raw Census Counts
(%)
UN 2010 Revision
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1971
1980
1990
2000
2010
1.5
2.6
3.2
3.6
1.1
UN 2012 Revision
–2.2
–1.0
0.0
1.5
1.5
Source: Author’s calculations based on data from BPS (Badan Pusat Statistik) and the United Nations
(UN) Population Division’s World Population Prospects.
that mirrors the trend based on the raw counts. Table 2 compares the raw census counts of population with the UN estimates in the 2010 and 2012 Revisions,
respectively. The UN in its 2012 Revision is implying that the 1971 and 1980 raw
counts overestimated the actual population, while the 1990 raw count was the
same as the UN estimates in the 2012 Revision. The extent of the undercount is
then considered to be the same in the carefully taken 2010 census (Hull 2010) as it
was in the poorly taken 2000 census. The logic of the changes in the UN estimates
is somewhat mystifying, which underlines the need for an intensive investigation of Indonesia’s demography from 1970 to 2010.1 Varying estimates continue to
appear with the new oficial population projections showing the estimated population of Indonesia in 2000 to be 205.1 million, lower than the census count and
almost four million lower than the latest UN estimate for 2000 (BPS 2014).
To add to the argument of uncertainty, as described in appendix 1, the recorded
population growth rates based on raw counts for many of the provinces of Indonesia over the past three decades (1980–90, 1990–2000, and 2000–2010) display
trajectories that challenge plausibility. For example, several provinces show a pattern in which the growth rates in 1990–2000 were considerably lower than those
in 1980–90 and 2000–2010.2
Uncertainty applies not only to the population total but also to some of its characteristics. From the results of the 2010 post-enumeration survey (PES), 20% of
the population had inconsistent ages reported between the census and the PES
and 35% had inconsistent levels of education. Marital status was inconsistently
reported for 10% of the population (BPS 2011a).
As discussed below, uncertainty about population growth in Indonesia is
founded on poor measurement of the components of its population change:
1. Such an intensive investigation will be undertaken through an Australian Research
Council Linkage Project grant awarded to researchers at The Australian National University and The University of Adelaide, in association with the Australian Government Department of Foreign Affairs and Trade, the United Nations Population Fund in Indonesia, BPS,
and Indonesia’s National Family Planning Coordination Agency (Badan Kependudukan
dan Keluarga Berencana Nasional).
2. West Sumatra, Jambi, Lampung, DKI Jakarta, DI Yogyakarta, South Kalimantan, East
Kalimantan, Southeast Sulawesi, Maluku, and West Papua.
34
Peter McDonald
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fertility and mortality rates and net international migration. Indonesia has failed
to develop reliable ways of measuring these components of change. Along with
the current age structure, these components of change are the determinants of
past and future population growth.
INDONESIA’S DEMOGRAPHY IN COMPARATIVE PERSPECTIVE
To place Indonesia in comparative perspective, I use demographic data provided
by the UN Population Division in its 2012 Revision.3 I compare Indonesia with
12 other countries in the Asia-Paciic region: Iran, India, Bangladesh, Myanmar
(Burma), Singapore, Malaysia, Thailand, Vietnam, China, Japan, the Philippines,
and Australia. This group includes all the major countries of Southeast Asia, as
well as China, India, and Iran as countries with large populations in Asia. It also
includes Japan, Singapore, and Australia as regional developed-country comparators. As shall be seen, the conventional wisdom that developing countries have
high rates of population growth and developed countries have low rates is not
borne out by this regional comparison.
Population Size
The irst and most obvious point to make is that Indonesia’s population is very
large, by now the fourth largest in the world. While population size tells us little about economic or social development, McNicoll (1999) and others (Jackson
and Howe 2008) argue that population size matters more and more as the economic disparities between countries become less divergent. Conventional military power also depends on how many soldiers a country has in its army, given
the increasing capacity to arm those soldiers relatively cheaply. Writing in 1999,
McNicoll said that Indonesia ‘is likely to retain an effectively heavyweight if not
hegemonic role in Southeast Asia’, very largely because of its population size
(McNicoll 1999, 423).
Conversely, any positive rate of growth applied to a very large population generates a very large number of additional people. This consideration has inluenced
the minds of policymakers in Indonesia for decades. Today, in Indonesia, there is
considerable concern in many circles that current population growth constitutes
a ‘population explosion’ (ledakan penduduk) that has negative implications for
almost every aspect of life.4 The concern has been expressed most signiicantly by
Sonny Harmadi, director of the Demographic Institute of the University of Indonesia (for one example, see Harmadi, ‘Pesan Kependudukan 2011’ (Kompas, 11
Jan 2011). Harmadi was expressing concern about a population explosion before
the release of the 2010 census count and, using raw rates similar to those shown
in the second column of table 1, he conirmed his fear after the census results
became available. His concerns have been mirrored by other luminaries such as
3. This is not to say that I endorse the estimates made by this organisation for Indonesia.
Indeed, prior to more intensive analysis, I ind the UN estimates over time to be very confusing. However, the 2012 Revision revised the UN’s prior estimates substantially for other
countries besides Indonesia. Thus, in the interests of maintaining cross-national consistency, I have used the estimates from the 2012 Revision.
4. This concern is immediately evident from an online search of ‘ledakan penduduk’.
The Demography of Indonesia in Comparative Perspective
35
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the then head of the Coordinating Board for National Family Planning (Badan
Koordinasi Keluarga Berencana Nasional [BKKBN]) Sugiri Syarief (Antara News,
25 Nov 2011) and presidential candidate Prabowo Subianto (Tribunnews.com, 30
May 2013).
Rates of Population Growth
In policy terms, the important issue is not so much the current level of Indonesia’s population growth as its trend. If the aim is to reduce population growth to
zero, the UN 2010 Revision data for Indonesia are evidence providing support
for more of the same policy approach; the raw data and the UN 2012 Revision
data are evidence calling for a radical change in policy. My own sense, subject to
revision after more intensive investigation, is that the Indonesian fertility decline
may have been exaggerated in the decades prior to 2000. The population growth
rate has probably been falling consistently, but with levels of growth higher than
those shown in table 1.
Figures 1 and 2 show Indonesia’s rate of population growth (based on UN 2012
Revision data) in comparison with those of 12 other countries of the region for
two periods of time. In 1970–75, the nine developing countries conirmed their
expected pattern of high rates of growth (above 2% per annum) while the three
more developed countries (Japan, Australia, and Singapore) had the lowest rates.
At 2.5%, Indonesia had the ifth highest rate. By 2005–10, Indonesia had the sixth
highest rate, 1.4%, but only because two of the developed countries, Singapore
and Australia, had jumped from the low end to the high end. Both these countries
were by then supporting higher population growth through large-scale migration
programs (igure 4). Both were also producing their own form of ‘demographic
dividend’ by importing workers directly into the younger working-age groups.
Indonesia’s 2005–10 growth rate was a little higher than that of Iran, a country in which recent policy debate has focused on whether the birth rate should
be stimulated (Abbasi-Shavazi, pers. comm.). Iran fears that its fertility is falling
below replacement levels and that it will experience the anguish about very low
fertility now expressed in countries such as Japan, South Korea, Singapore, and
Thailand. There is no such concern in Indonesia, despite the apparent similarity
of current population growth rates.5
Figure 4 shows the breakdown of recent population growth in the selected countries into net migration and natural increase. Most noticeable is Singapore’s very
high net migration rate of 1.9% per annum. Australia also has a high net migration rate of more than 1% per annum. The UN estimates that net international
migration for all the other countries is very small in relative terms. For Indonesia,
a net outmigration of 148,000 persons per annum is estimated for 2005–10, but
this may well be an underestimate. Hugo (2009), citing Ananta and Ariin (2008),
5. The UN projects Indonesia’s and Iran’s rates of population growth to be similarly positive in 2030–35 (igure 3). Indonesia’s rate of 0.66% per annum implies an increase of population at that time of almost two million people per annum. The 2030–35 projected population growth rates show that large countries like India, Bangladesh, and the Philippines
would still have quite high rates of growth. At the other extreme, Thailand, Japan, and
China will have relatively large negative rates of growth, which is highly concerning now
at least to Japan and Thailand and, predictably, to China at some future point.
FIGURE 1 Annual Rate of Population Growth, Selected Countries, 1970–75
(%)
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Philippines
Thailand
Iran
Bangladesh
Indonesia
Malaysia
Myanmar (Burma)
China
India
Vietnam
Singapore
Australia
Japan
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
FIGURE 2 Annual Rate of Population Growth, Selected Countries, 2005–10
(%)
Singapore
Australia
Malaysia
Philippines
India
Indonesia
Iran
Bangladesh
Vietnam
Myanmar (Burma)
China
Thailand
Japan
0.0
0.5
1.0
1.5
2.0
2.5
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
3.0
FIGURE 3 Annual Rate of Population Growth, Selected Countries, 2030–35
(%)
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Philippines
Australia
Malaysia
Indonesia
India
Bangladesh
Iran
Singapore
Vietnam
Myanmar (Burma)
China
Thailand
Japan
–0.5
0.0
0.5
1.0
1.5
2.0
2.5
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
FIGURE 4 Annual Rates of Net Migration and Natural Increase,
Selected Countries, 2005–10
(%)
Malaysia
Philippines
India
Indonesia
Iran
Bangladesh
Vietnam
Myanmar (Burma)
Australia
China
Singapore
Thailand
Japan
–0.5
Net migration
0.0
0.5
1.0
1.5
Natural increase
2.0
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
2.5
38
Peter McDonald
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states that there were 2.7 million documented migrants from Indonesia in other
countries, in addition to large numbers of undocumented migrants. In contrast,
if most of these migrants are temporary contract workers who will eventually
return to Indonesia, which seems to be the case, this would be consistent with low
net migration.
Age Distributions
Associations between economic development and demography are based most
often on the nature of the age distribution of the population—in particular, on
the balance between those of working age and those in the younger and older
dependent ages. Countries with high birth rates have relatively large numbers of
young dependents; countries with low birth rates, in time, have relatively large
numbers of old dependents. This section discusses Indonesia’s age distribution
in comparative perspective. Comparison is made with Thailand, in particular,
because it has recently moved to implement pronatalist policies, whereas debate
in Indonesia is concerned with policies to address a perceived births-led population explosion; yet both countries had similar age distributions around 1970, and
both have experienced substantial fertility declines.
In 1970, 43% of Indonesia’s population was aged 15 and under, compared with
44% of Thailand’s (igures 5 and 6). Thailand’s rate of population growth at the
time was a little higher (igure 1), because its fertility rate was higher. But, since
then, Thailand’s rate of growth (and its fertility) has fallen faster than that of Indonesia. The varying speeds of decline have had differing effects on the age structures of the two countries (igures 5 and 6) and important implications for policy.
The Thai age pyramid in 2010 is undercut at the younger ages; the largest iveyear age group is those aged 35–39. As the large cohort aged 30–49 in 2010 has
passed through the working ages, it has, in theory, generated the demographic
dividend in a classic form, because the numbers have been smaller at the younger
and older ages. As this age group moves into the older ages, also in classic fashion, the population will age considerably and population ageing will emerge as
a central issue of population policy. The UN projects that the percentage of the
population aged 65 and over in Thailand will increase from 9% in 2010 to 23% in
2050, a higher level than is projected for Australia in 2050 (igure 7). In Australia,
migrants and their subsequent births, along with a relatively high birth rate, are
projected to keep the population at the young end of the spectrum of developed
countries (McDonald and Temple 2010). In 2012, the Thai government shifted its
policy agenda to one that is similar in form to those of many countries in Europe
and East Asia, where fertility rates are very low (NESDB 2012). The policy proposals include pronatalist inancial measures (such as lower taxes for those with
more children) and family-friendly workplace policies, including lexible working hours, paid parental leave, and childcare.
The new Thai agenda also promotes policies for older people, including incentives to continue working rather than to retire, tax incentives for self-support
through personal savings, the development of a national income support scheme
for the aged, systems and incentives for the support of older people by their families, and better health and welfare infrastructure. The Thai government’s policy
document also focuses on improving the productivity of the economy through
higher human capital and higher multifactor productivity. The simple argument
is that a richer country, one with high GDP per capita, will be in a better position
FIGURE 5 Age Distributions of Indonesia, 1970, 2010, and 2050
(population in millions)
1970
Males
Females
85+
80–84
75–79
2010 and 2050
55–59
50–54
45–49
40–44
35–39
30–34
25–29
20–24
15–19
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
14
-14
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
14
10–14
5–9
0–4
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
Note: The projected age distribution for 2050 is represented by the dashed lines.
FIGURE 6 Age Distributions of Thailand, 1970 and 2010
(population in millions)
1970
Males
Females
85+
80–84
75–79
2010
70–74
65–69
60–64
55–59
50–54
45–49
40–44
35–39
30–34
25–29
20–24
15–19
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
4
3
2
1
0
-1
-2
-3
-4
4
3
2
1
0
-1
-2
-3
10–14
5–9
0–4
-4
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70–74
65–69
60–64
40
Peter McDonald
FIGURE 7 Share of Population Aged 65 and Over, Selected Countries, 2010 and 2050
(%)
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Japan
Singapore
China
Thailand
Australia
Vietnam
Iran
Indonesia
Myanmar (Burma)
Malaysia
Bangladesh
India
Philippines
0
2010
2050
5
10
15
20
25
30
35
40
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
to support its aged population (see Lutz and K. C. [2013] for an exposition of this
argument).
Population ageing will occur much more slowly in Indonesia. Owing to a
slower decline in fertility between 1970 and 2010 than was the case in Thailand,
Indonesia’s age pyramid in 2010 is not as undercut: the largest age group is the
youngest (those aged 0–4), and the size of this group may well be understated. By
2010, 30% of Indonesia’s population was aged 15 and under, compared with 19%
of Thailand’s. According to the UN projections, the percentage aged 15 and under
in Indonesia in 2050 will be 20%, still higher than the Thai percentage in 2010.
Having more time to adjust to an ageing population could be an advantage
for Indonesia. Figure 7 provides one view of the country’s demographic future.
It shows a projection of Indonesia’s present population and age structure to 2050,
based on the assumption that the fertility rate will fall to 2.1 births per woman by
2015. The result shows substantial population ageing by 2050; but the age structure remains relatively lat-sided, and the population growth rate at that time
would be approximately zero. By this projection, the total population of Indonesia in 2050 would be 323 million. The policy question for Indonesia is whether a
slow movement to zero population growth would provide better outcomes than
the pathway that Thailand is on, despite the ultimately large population size of
Indonesia. Should a country trade a larger population size for a more sustainable
longer-term age structure? The policy approaches being taken by countries facing
population decline and very rapid ageing suggest that they would prefer to trade
a somewhat higher population size for an age structure that was more amenable
to economic and social policy.
The projection in igure 5 is only one potential pathway for Indonesia. Some
would argue that Indonesia could attain low fertility and then face problems
similar to those of Thailand. Others would argue that Indonesia’s future may look
more like India’s, in which only 14% of the population would be aged 65 and over
in 2050 (igure 7). My own sense is that ageing in Indonesia will occur slowly, and
The Demography of Indonesia in Comparative Perspective
41
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that Indonesia’s fertility is very unlikely to be below 1.5 births per woman in the
foreseeable future, if ever. Nevertheless, the demographic future of Indonesia is
inherently uncertain and, because of poor data measurement and a lack of accuracy about the prevailing levels of fertility and mortality, more uncertain than for
other comparator countries. Demographic futures are important in areas of planning with long lead times, such as large-scale infrastructure and education and
health services.
Fertility
Fertility in Indonesia is estimated directly and indirectly. Direct estimates are
obtained from the results of the infrequent Indonesian Demographic and Health
Survey (IDHS). Indirect estimates are obtained every 10 years from the census
results, by using the own-children method, which links children in a household
to their mothers and produces a table showing the ages of children by the ages of
their mothers (see Abbasi-Shavazi [1997] for an evaluation of the method).
The census-based own-children method is not robust to under-enumeration in
the census of the number of children (for example, those aged 0–4) relative to the
number of women of childbearing age, and this may be a considerable problem in
Indonesia.6 In countries with relatively good vital registration data, such as India
and Iran, the own-children estimates of fertility are lower than those based on
birth registration data.
In the IDHS, a sample of women is asked to report the details of all their pregnancies, which makes it possible to calculate fertility directly from the number
of births reported by the women surveyed. The accuracy of the result depends
on whether the sample truly represents the population. In the last two IDHS collections, in 2007 and 2012, the age-speciic proportions of married women were
much higher than those recorded in other data collections, such as Susenas and
the 2000 and 2010 censuses. In other words, there is strong evidence that the IDHS
tends to miss women who are not married. Single women have few children, so
the fertility rates from the IDHS tend to be too high (assuming that the number of
births is accurately reported).7
In summary, the census-based own-children estimates of fertility are likely to
underestimate fertility in Indonesia, whereas the IDHS is likely to overestimate it.
IDHS estimates suggest that Indonesian fertility rates have hardly changed since
the mid-1980s, and that the decline has stalled at around 2.6 births per woman
(Hull and Hartanto 2009; Hull pers. comm.). By the own-children estimates from
the censuses, fertility fell to around 2.3 births in the late 1990s, but rose slightly to
about 2.4 births in the latter years of the 2000s (BPS 2011b).
6. For example, if we estimate the population aged 0–4 at the time of the 2000 census by
reverse surviving the population aged 10–14 at the 2010 census, this estimate is approximately 12% higher than that recorded in 2000. The own-children estimate of the total fertility rate from the 2000 census was 2.27 births per woman, but with a 12% correction it
would have been 2.54. This is a large variation to consider when trying to measure the
trend in fertility.
7. The 2007 IDHS estimated the total fertility rate to be 2.57 in 2002–3, and the 2012 IDHS
estimated it to be 2.60 in 2007–8. If the IDHS proportions married by age are adjusted to
those obtained in the 2000 and 2010 censuses, the IDHS estimates of fertility for these years
fall respectively to 2.35 and 2.20 (Hull and Hartanto 2009; Hull pers. comm.).
42
Peter McDonald
FIGURE 8 Total Fertility Rates, Selected Asian Countries, 1970, 1985, 1995, and 2010
(births per woman)
Philippines
Indonesia
India
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Malaysia
Bangladesh
Vietnam
Myanmar (Burma)
Australia
Iran
China
Thailand
1970
1985
1995
2010
Japan
Singapore
0
1
2
3
4
5
6
7
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
The argument has been made that Indonesia’s family-planning program has
been disrupted by decentralisation (Habsjah 2009; Hull and Hartanto 2009), and
that this is why fertility has remained constant for a long period (as shown by
the IDHS estimates). This argument has also been used to justify a rise in fertility, using own-children estimates, between the 2000 and 2010 censuses. It has
also been suggested that democracy has stimulated a shift to a more conservative
(Islamic) society, and that this shift has stimulated the birth rate. On the other side,
fertility has fallen sharply in almost all other Islamic countries, and sharp rises in
education and urbanisation are very likely to have pushed the Indonesian fertility
rate downwards. The age pattern of fertility also shifts to older ages between the
own-children estimates of 2000 and 2010 (BPS 2011b). This kind of shift in the age
pattern of fertility is usually associated with a fall in the fertility rate.
For comparative purposes, igure 8 uses the estimates provided by the UN Population Division (2012 Revision). The estimates show Indonesia’s fertility level
drifting up in rank from the ninth highest among the 13 countries around 1970 to
the second highest around 2010. The UN estimates are more in keeping with the
IDHS estimates than with the census-based estimates, despite the criticisms that
have been made of the IDHS estimates. As a consequence, Indonesia’s fertility
around 2010 is estimated to be above that of India, Malaysia, and Bangladesh.
Iran has the largest downward movement, from 7.0 births per woman in 1985 to
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The Demography of Indonesia in Comparative Perspective
43
1.85 in 2010 (see Abbasi-Shavazi, McDonald, and Hosseini-Chavoshi 2009). The
UN estimates that the fertility rates of China and Thailand have now fallen into
the ‘very low’ range, under 1.5 births per woman. The Philippines, not unexpectedly, has the highest fertility rate, and there are those who argue, in keeping with
the demographic-dividend theory, that high fertility has been an obstacle to economic growth in that country.
The latest UN estimates of fertility for Indonesia question the conventional
wisdom of rapidly declining fertility. They indicate that the Indonesian government may need to take stronger action in addressing the country’s stalling decline
in fertility. Yet if the UN estimates are too high, as some would argue they are,
an overly vigorous approach to fertility reduction may push Indonesian fertility
rates in the direction of ‘very low’ fertility—which is also not desirable. The ideal
outcome for Indonesia is to have fertility fall to around two births per woman
and then be sustained at that level. The countries that have achieved this (without
fertility falling to very low levels) have accepted that couples may have more than
two children, and have also provided support for families with children.
Mortality
While there is uncertainty about the level of fertility in Indonesia, there is no reliable information about mortality for people over the age of ive. Planners need
accurate information on adult mortality, both to project the numbers at older
ages and to plan aged-related services. This section shows that a change in the
method of measurement could transform Indonesia from one of the best performers among the comparator countries in reducing mortality to one of the worst.
The conventional way of measuring adult mortality in Indonesia is to associate a model life table—most commonly that of Coale and Demeny’s (1966) West
model—with the estimate of child mortality (mortality below age ive) to obtain
estimates of mortality at all other ages and life expectancy at birth. The West
model life tables are based very largely on the mortality experience in Europe,
Australia, and New Zealand in the 19th century, and questions remain about their
appropriateness to countries like Indonesia in the 21st century because the regime
of causes of death and the state of medical knowledge are very different in today’s
developing countries compared with 19th-century Western experience.
Child mortality in Indonesia is most commonly estimated by using data on the
number of live births that women have had and the number of those live births
that are still alive at the time of the census or the survey, according to the women’s
ages at the time of the survey. The methodology dates back to the 1960s and was
designed to measure child mortality in situations where mortality is very high—
say, around 200 deaths under the age of ive from 1,000 live births—and where
childbearing begins at a young age. When child mortality falls to a much lower
level and childbearing begins at older ages, as is the case in Indonesia today, this
method is not robust enough to measure the much smaller movements in child
mortality.8 Applying this method to 2010 census data, Statistics Indonesia (Badan
Pusat Statistik [BPS]) estimated the rate of child mortality to have been 30 deaths
per 1,000 births in 2006 (BPS 2011c). Another method of estimation, used in the
8. If the age distribution of mothers at the time of birth were to be older than the distribution assumed in the model, the level of child mortality would tend to be underestimated.
44
Peter McDonald
FIGURE 9 Life Expectancy at Birth, Selected Countries, 1970–75 and 2005–10
(years)
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Japan
Australia
Singapore
Vietnam
China
Malaysia
Thailand
Iran
Indonesia
Bangladesh
Philippines
India
Myanmar (Burma)
0
1970–75
2005–10
10
20
30
40
50
60
70
80
90
Source: United Nations Population Division, World Population Prospects: The 2012 Revision.
IDHS, involves asking women about the dates of birth and death (if applicable)
of each of their children. Such data can be used to make direct estimates of child
mortality. This method, however, tends to underestimate child mortality because
the birth and death of children who died shortly after birth are often not reported.
The most recent survey shows a child mortality rate, based on this method, of
32 deaths per 1,000 live births during 2008–12 (BPS et al. 2012). This estimate is
largely consistent with that of the 2010 census, but both may be consistently low.9
In its 2012 Revision, the UN Population Division estimated life expectancy in
Indonesia in 2005–10 to be 69.6 years (igure 9). This is consistent with the estimate
for 2006 (70.7 years) published by BPS (2011c). However, Muhidin and Nasrun’s
(2012) estimate of 60.8 years from the 2010 census, which also refers to about 2006,
is a very different result.10 These contrasting estimates show that the level of mortality in Indonesia is highly speculative, and much more so than the fertility rate.
Figure 9 shows that Indonesia’s life expectancy, at 60.8 years, would easily be the
lowest among the comparator countries, the lowest of which is currently Myanmar (Burma), at 64.2 years. Much consideration needs to be given to improving
the estimation of mortality in Indonesia.
Population Distribution and Internal Migration
The movement of population from densely settled Java to other islands is a policy
approach that originated in the Dutch colonial period, and the idea of population
9. There is little consistency at the provincial level between the census-based estimates and
the IDHS estimates—the former appears to be particularly low in the eastern provinces.
10. Muhidin and Nasrun (2012) also use West model life tables, but they include an analysis of the change in age cohort sizes between the 2000 and 2010 censuses (the intercensal
survival method).
The Demography of Indonesia in Comparative Perspective
45
TABLE 3 Growth of the Regions of Indonesia, 1971–2010
(ratio of population, 2010 to 1971)
Java
Kalimantan
Sulawesi
1.80
2.68
2.04
Sumatra
Remainder
Indonesia
2.43
2.23
1.99
Source: Author’s calculations based on data from BPS.
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TABLE 4 Net Migration, Provinces of Java, 2005–10
Banten
Central Java
DI Yogyakarta
DKI Jakarta
272,000
–678,000
124,000
–239,000
East Java
West Java
Java
–285,000
453,000
–354,000
Source: BPS (2011d).
redistribution is embedded in the minds of most Indonesians at primary school.
In addition, fertility fell earlier and further in the provinces of Java than in those
outside Java. For these reasons, we would expect a redistribution of population
away from Java. Yet urban economic development has been concentrated in Java’s
largest cities, which have grown substantially. The once-wide boundaries of DKI
Jakarta long ago became inadequate to contain the city’s growth, and Jakarta now
abuts on the neighbouring cities of Depok, Bekasi, and Tangerang. This section
considers the extent to which the redistribution of population from Java to the
outer islands is taking place today.
The net effect of these demographic trends is that Java has grown a lot more
slowly than all the other regions of Indonesia. The fastest growing region has
been Kalimantan; East Kalimantan’s population increased almost ive times
during 1971–2010 (table 3). Growth within Java is quite diverse, with West Java
(including Banten) increasing 2.5 times but Central and East Java each increasing
only 1.5 times. The high growth rate of West Java relects Jakarta’s spreading into
that province.
The slower growth of Java, at least in recent years, owes little to outmigration from Java. Table 4 shows that net migration from Java during 2005–2010
amounted to only 354,000, or just 71,000 per annum, a number that is trivial compared with the total population of the island (BPS 2011d). The table also shows
that DKI Jakarta, which has experienced net outmigration since the late 1980s,
recorded negative net migration of 239,000 in this period, as people moved out of
the province to housing estates in the areas of West Java and Banten contiguous
with DKI Jakarta. The even larger in-migration to West Java and Banten shown
in table 4 can also be attributed to the growth of the megacity of Jakarta. Central
Java is the largest source of out-migrants, with a net loss of 136,000 per annum in
the ive years before the 2010 census.
The dificulty of deining city boundaries hinders cross-country comparisons
of cities and their growth. For example, the UN Population Division recorded the
population of the urban agglomeration of Jakarta in 2010 to be 9.6 million, which
46
Peter McDonald
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FIGURE 10 Share of Population Living in Urban Areas, Selected Countries,
1970, 2010, and 2030
(%)
Singapore
Australia
Malaysia
Iran
Japan
China
Philippines
Indonesia
Myanmar (Burma)
Thailand
Vietnam
Bangladesh
India
0
1970
2010
2030
10
20
30
40
50
60
70
80
90
100
Source: United Nations Population Division, World Urbanization Prospects: The 2011 Revision.
is precisely the population recorded for the province at the 2010 census. Yet it is
accepted that the city has now sprawled into West Java and Bantan, and that its
real urban agglomeration is considerably larger.11
Deinitions of rural and urban areas are also notoriously inconsistent across
countries. Glossing over this problem, igure 10 shows that urbanisation has been
a very powerful force in Indonesia since 1970. Yet in 2010, the urban population
remained below 50% of the total population (a higher proportion than in ive
of the comparator countries: Myanmar [Burma], Thailand, Vietnam, Bangladesh,
and India). The World Bank has recently argued that urban agglomerations provide major advantages for development, and that Indonesia’s relatively high
level of urbanisation may present it with considerable opportunities to increase
productivity (World Bank 2013). However, the UN’s projections of urbanisation
suggest that the growth of the urban segment will be slow in all the developing
countries shown in igure 10. In Indonesia, for example, the urban proportion is
projected to increase from 44% to just 54% in the next 20 years. This slow rate of
urbanisation does not seem to be in keeping with the increases in education that
will take place in this period. The UN projections also do not take into account the
results of the 2010 Indonesian census, whic