Full Text

Demographic Consequences of the ‘Closing the Gap’Indigenous Policy in Australia

Nicholas Biddle • John Taylor

Received: 25 October 2010 / Accepted: 17 April 2012 / Published online: 27 April 2012

� Springer Science+Business Media B.V. 2012

Abstract The demography of Indigenous Australians is distinguished from that of

other Australians by relatively high mortality and fertility leading to very different

composition by age. This is beginning to change as movement towards a conver-

gence in vital rates is observed. In the meantime, the Australian government has

established targets for Indigenous socioeconomic outcomes that simultaneously

impact on, and are affected by, the course of demographic change. This paper

examines the relationship between these targets and projected Indigenous demo-

graphic outcomes that arise from incipient population ageing. The most likely

scenario is movement into an indeterminate period of potential demographic divi-

dend. If demand for Indigenous labour expands alongside reductions in age

dependency this could provide for dramatic improvement in Indigenous economic

circumstances. However, caution is warranted as disparities in adult mortality

require long-term solutions and movement into a second phase of demographic

transition appears likely to be delayed.

Keywords Indigenous Australians � Population projections �Demographic dividend � Demographic transition

Introduction

In 2011, Australia ranked 2nd in the world out of 187 countries according to the

United Nation’s Human Development Index (UNDP 2008). By contrast, if

equivalent ranking were possible, the Indigenous population in Australia would

fare much worse, probably in line with a country like Fiji which was ranked 100th in

N. Biddle (&) � J. Taylor

Centre for Aboriginal Economic Policy Research, Australian National University,

Canberra, ACT, 0200, Australia

e-mail: [email protected]

123

Popul Res Policy Rev (2012) 31:571–585

DOI 10.1007/s11113-012-9235-8

2011 in terms of health (as measured by life expectancy), education, income and

multidimensional poverty. Thus, the most recent estimates of life expectancy

for Indigenous Australians produced by the Australian Bureau of Statistics

(ABS 2009a) reveal a gap with the non-Indigenous population of 11.8 years for

males (66.9 years compared to 78.6 years) and 10.0 years for females (72.6

compared 82.6 years). Furthermore, Altman et al. (2009) have shown that

Indigenous Australians are 3.06 times more likely to be unemployed, 0.41 times

less likely to own their own home and have median personal incomes that are just

0.58 of the level of non-Indigenous Australians.

Statistically, Indigenous Australians are those who self-identify though census

processes as descendants of the first inhabitants of the Australian continent and

nearby islands. This includes both Aboriginal Australians and Torres Strait

Islanders. According to the most recent census estimates, there were 517,174

Indigenous Australians as of July 2006, representing around 2.5 % of the total

Australian population (ABS 2008a). This estimated resident population (ERP) was

12.8 % higher than the corresponding figure in 2001—a population growth rate that

far outstrips that of the non-Indigenous population.

In recent decades, the demography of Indigenous Australians has been

characterised by persistently higher mortality and fertility despite some indication

of movement towards convergence, especially in infant mortality and fertility rates

(Taylor 2003). The outcome of these differentials is well reflected in resultant age

distributions as shown in Fig. 1.

While 38 % of Indigenous Australians were aged under 15 at the time of the last

census, only 3 % were aged 65 years and over. On the other hand, 19 % of non-

Indigenous Australians were aged under 15, with 13 % of the population aged

65 years and over. On balance, then, with an age dependency ratio of 1.5, there are

fewer Indigenous Australians of working age relative to those under 15 or over 65

Fig. 1 Age distribution of Indigenous and non-Indigenous Australians, 2006

572 N. Biddle, J. Taylor

123

than among the non-Indigenous population (with a ratio of 2.1).1 However, as the

latter ratio continues to fall with further expansion of the aged population, and as the

former ratio rises with an increased proportion in working ages, the relative

demographic fortune of the Indigenous population is beginning to shift in a

favourable way.

These statistics on socioeconomic and demographic relativities are well known

by both researchers and policymakers in Australia. Furthermore, keen attention is

paid to how the relevant outcomes are trending through time with a major report to

parliament (Overcoming Indigenous Disadvantage) now tabled every 2 years

(SCRGSP 2009) and a formal statement of progress towards the achievement of

specified targets aimed at ‘Closing the Gap’ between Indigenous and non-

Indigenous Australians made by the Prime Minister each year (Australian

Government 2012).

Specifically, the aim is to: close the life expectancy gap within a generation (that

is by 2031), halve the gap in mortality rates for Indigenous children under five

within a decade (2018), ensure access to early childhood education for all

Indigenous four-year-olds in remote communities within 5 years (2013), halve the

gap in reading, writing and numeracy achievements for children within a decade

(2018), halve the gap for Indigenous students in year 12 attainment or equivalent

attainment rates by 2020, and halve the gap in employment outcomes between

Indigenous and non-Indigenous Australians within a decade (2018).

If achieved, this Closing the Gap agenda would rank as one of the more

significant achievements in Indigenous affairs policy, both within Australia and

internationally. Not only do Indigenous Australians fare relatively poorly compared

to non-Indigenous Australians, they also have substantially worse outcomes than

other comparable groups in Canada, New Zealand and the US (Cooke et al. 2007).

One aspect of this Closing the Gap framework that has hitherto been ignored is

its interaction with demography despite the obvious links that exist between levels

of Indigenous disadvantage and demographic outcomes. For example, the current

high child-dependency ratio (number of children relative to the working age

population) means that in order to substantially reduce the education achievement

gap between Indigenous and non-Indigenous students substantial resources will

need to be found from outside the homes of Indigenous youth. Also, continued high

teenage fertility among Indigenous females is likely to place severe constraints on

labour supply (Biddle and Yap 2010).

Movement towards achieving the Closing the Gap targets is also likely to have a

substantial impact on a number of demographic variables. In this calculation the

reduction in Indigenous deaths that would arise from a closing of the gap in life

1 In our analysis, we use age dependency ratios rather than economic support ratios which focus on the

ratio of the working population to the consuming population (with those aged under 15 weighted at 0.5 or

0). There are a number of reasons for this. First, the largest expenditure items for governments with

regards to the Indigenous population are education services and housing, both of which are poorly

captured in economic support ratios. The second reason is that employment is ambiguously defined in the

Australian census with uncertainty around whether a common labour market program for the Indigenous

population (the community development and employment program (CDEP) scheme is undercounted.

Third, a large minority of Indigenous Australians participate in hunting, fishing and gathering with the

resources gained contributing to household consumption in ways unknown.

Consequences of the ‘Closing the Gap’ Indigenous Policy in Australia 573

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expectancy is an obvious impact. Less obvious is any impact on fertility rates that

might arise from improvements in Indigenous educational attainment and employ-

ment participation. Strong positive association between an index of childlessness

and such attainment and participation has been observed among Indigenous females

(Gray 1990) and further achievement in these areas is likely to substantially increase

the opportunity cost of having children (especially when young) and improve the

ability of Indigenous females to make informed fertility decisions (Diamond et al.

1999; Brewster and Rindfuss 2000).

Combining these effects, perhaps the biggest demographic effect of achieving the

Closing the Gap targets would be on the age structure of the Indigenous population.

On the one hand, reductions in fertility should lead to a decline in the child

dependency ratio. On the other hand, reductions in mortality rates should lead to an

increase in the aged dependency ratio. In combination these processes should

therefore provide for a period of potential demographic dividend (Bloom and

Williamson 1998; Jackson and Felmingham 2004), although the precise composi-

tion and period of this opportunity will depend on the scale and timing of these two

effects. More certain, in the context of an ageing Australian population overall

(Commonwealth Treasury 2010), is the fact that the Australian workforce has the

potential to become more ‘Indigenous’ than ever before in the decades ahead.

With this prospect in mind, the aim of this paper is threefold. First, to document

the projected Indigenous population over the period from 2006–2031 under

different mortality and fertility assumptions that derive from the Closing the Gap

targets. Second, to consider the implications of these population projections in terms

of other demographic outcomes including deaths, births to teenage mothers and

dependency ratios. Finally, to reflect on the overall prospects for achieving the

Closing the Gap targets from a demographic perspective.

Projection methodology

Several methods are available for population projections ranging from simple

mathematical methods using historic growth rates and assuming that these will

continue into the future, to more complex microsimulation methods that apply

maximum amounts of information to interactions with age structure (Wilson and

Rees 2005). Those most appropriate for projections of the Australian Indigenous

population are cohort-component methods since these examine interactions with age

structure but require only basic data inputs, all of which are readily available.2 We

apply this methodology to create a set of population projections for the Indigenous

2 There are however limitations with the data available all of which are common to self-identified

populations. In particular, there is a strong potential for numerator-denominator bias in calculating

Indigenous life tables with Indigenous status on the census (the denominator) self identified but

Indigenous status on the deaths registry (the numerator) often filled out by a third party. This issue is

mitigated to a certain extent by the ABS linking administrative data on deaths to census data at the unit

record level to calculate Indigenous life expectancy (ABS (2009b). However, this only reduces the

problem rather than eliminating it as the method is highly dependent on the quality of the name and

address information on both the census and deaths records.


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(and non-Indigenous population) for the period over which the Closing the Gap

targets have been set (2006–2031).

Of the main components of the standard demographic equation, we set overseas

immigration and emigration to zero for the Indigenous population in the absence of

any data to the contrary.3 In the parallel projections for the non-Indigenous population

(which are used to calculate births to non-Indigenous mothers and as a benchmark for

the Indigenous projections) we use the assumed migration rates from ABS (2008b),

with the age structure and geographic location within Australian jurisdictions

determined by the age structure and geography of recent migrants in the census. We

use official estimated resident population (ERP) figures in 2006 (from ABS 2008c) as

the base population and undertake the projection concurrently for 37 Indigenous

Regions to allow for local differences in births and deaths. As the projection results are

presented at a national level we assume zero net internal migration.

An interesting feature of socially-constructed populations, such as the Australian

Indigenous population, is that cohort-component methods tend to contain a sizeable

error term (Taylor 2011, p. 289). This represents the amount needed to balance

intercensal increase in population counts after accounting for demographic change

due to births, deaths and migration. For the most part this ‘error of closure’, as the

American demographer Passel (1996) has described it, is usually small, but in

Australia it accounted for fully 50 % of Indigenous population change between

1991 and 1996, and 31 % between 1996 and 2001. While this error was relatively

small and in line with natural increase over most recent intercensal period of

2001–2006, there remains an inherent uncertainty in self-identified counts.

There are two main sources for this error term. The first arises from individuals

who change their recorded Indigenous identification across census periods. Where

this has been studied it has been assumed that this ‘ethnic mobility’ has tended to

result in Indigenous peoples being more likely to identify as such through time

(Guimond 2006). The second source is increased coverage of Indigenous

populations as statistical agencies improve their capacity to enumerate them in

remote and difficult-to-survey areas. In Australia, estimates of error closure have

been applied to subsequent periods in official projection methodology to produce a

high series projection. Results are then provided alongside a low series that has no

such estimate. Given the low error of closure observed between 2001 and 2006, here

we apply the latter, more conservative, assumption. The assumptions for the

remaining two components (births and deaths) vary across three scenarios. These

are summarised in Table 1 with projections made iteratively for the five intercensal

periods between 2006 and 2031.

Scenario 1 assumes constant Indigenous rates throughout. This is the situation

that is likely to occur in the absence of substantial improvements in health and other

Closing the Gap targets and it represents an upper bound in terms of deaths and

births. Scenario 2 assumes that Indigenous fertility and mortality rates will converge

to non-Indigenous rates by 2031, representing the demographic outcome of the

government meeting its Closing the Gap targets. For fertility we hold current

3 Net overseas migration in Australia is derived from international departure and arrivals cards. These do

not include the standard Indigenous identifier question.


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non-Indigenous rates constant, but for mortality we use survival rates for the total

population as a proxy for non-Indigenous rates and assume that these will rise over

time in line with official projections (ABS 2008b). While Scenario 2 would

represent a sizable policy achievement, there would still be a number of excess

births and deaths relative to the non-Indigenous population over the period. This

excess is demonstrated using Scenario 3 which assumes that non-Indigenous fertility

and mortality rates apply to the Indigenous population throughout. While this

scenario is clearly unrealistic, it is used here simply to generate an illustrative lower

bound for births and deaths.

Projection results

Between 2006 and 2031 the Indigenous population is projected to increase from just

over 517,000 to almost 848,000 (Fig. 2). This growth is reasonably steady over the

Table 1 Assumptions used for births and deaths in population projections

Component Assumption

Scenario 1: Indigenous rates throughout

Fertility Two birth categories are estimated: births of Indigenous children to Indigenous mothers

and births of Indigenous children to non-Indigenous mothers. For the first category, 2006

State and Territory age-specific fertility rates are calculated using a yearly average of the

2005–2007 births (ABS 2008d) divided by the 2006 ERP, which are then applied to

Indigenous Regions as appropriate and held constant for the projection period. After

excluding births to Indigenous mothers, the average of the remainder of the Indigenous

births over the period are divided first by the Indigenous male ERP and then the non-

Indigenous female ERP. The average of the two is used as the second category of births

Mortality Age-specific survival rates are derived from the most recent experimental Indigenous life

tables (ABS 2009a) and held constant. 2006 State and Territory age-specific rates are

applied to Indigenous Regions as appropriate

Scenario 2: Convergence in rates

Fertility Under the assumption that convergence in employment and education outcomes will also

lead to a convergence in fertility rates, Indigenous fertility rates are applied to the

Indigenous population for the 2006–2011 period, whereas current non-Indigenous

fertility rates are applied for the 2026–2031 period. Age-specific rates are assumed to

converge linearly over the period. Births of Indigenous children to non-Indigenous

mothers are assumed to occur at the same rate throughout the period

Mortality Non-Indigenous mortality rates are assumed to fall over the period, following the pattern

outlined in ABS (2008b). Current Indigenous rates are used for the 2006–2011 period and

projected rates for the total population are used for the 2026–2031 period. The two rates

are assumed to converge linearly over the period

Scenario 3: Non-Indigenous rates throughout

Fertility Births of Indigenous children to Indigenous mothers for all projection intervals are

calculated by applying current non-Indigenous age-specific fertility rates to the

Indigenous age cohorts. Births of Indigenous children to non-Indigenous mothers are also

assumed to follow the same pattern throughout

Mortality Projected mortality rates for the total population from ABS (2008b) are applied to both the

Indigenous and non-Indigenous population


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period and it represents an annualised rate of 2.0 %. By way of comparison,

between 2001 and 2006, the Indigenous population was estimated to have grown

from 458,500 at an implied annual growth rate of 2.4 % (ABS 2008a). Clearly, the

model projects a decline in the rate of growth. Over the same period to 2031, the

non-Indigenous population is projected to increase from around 20,179,000 to

around 25,621,000. This represents a much lower growth rate compared to the

Indigenous population resulting in an increase in the Indigenous share of total

population from 2.5 to 3.2 %.

Not surprisingly, projected numbers based on the ‘Closing the Gap’ convergence

scenario are somewhat lower at 833,000 while those produced using non-Indigenous

rates throughout are lower still at 810,000. While differences in overall size of the

projected Indigenous population are therefore reasonably small, it would seem that

the increased life expectancy implied in these alternate scenarios is more than

counterbalanced by the reduction in births.

Demographic outcomes

While the differences across the scenarios in the overall size of the projected

Indigenous population are reasonably small, there is greater variation in the

components of change. This is demonstrated in Table 2 (the projected number of

deaths over the period) and in Table 3 (the projected number of births to Indigenous

mothers aged 15–19 and 20–24).

If Indigenous age-specific mortality rates stayed constant throughout the period,

then the model projects that there will be 86,824 Indigenous deaths from 2006 to

2031. However, if the Closing the Gap targets were to be met then this number

would fall to 64,312 deaths. Looking at this another way, to achieve this target, a

total of 22,512 Indigenous deaths would need to be avoided. While this would

represent a considerable achievement considering the size of the Indigenous

Fig. 2 Projected Indigenous population and share of total population (Scenario 1)


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population, this scenario still represents 14,004 additional deaths than would occur

if the Indigenous population had the same mortality rates as the non-Indigenous

population throughout (Scenario 3).

While the reduction in Indigenous deaths implied by the Closing the Gap

scenario is therefore substantial, the implied reduction in births to teenage and

young mothers is greater still. Under Scenario 1, there were 56,692 births to

Indigenous mothers aged 15–19 years. Combined with the 97,263 births to

Indigenous mothers aged 20–24 years, this represents a considerable constraint on

education participation. If fertility rates converged over the period (Scenario 2), the

projected number of births falls to 32,299 (for 15–19 year olds) and 64,884

(for 20–24 year olds). Once again though, Scenario 2 still represents a substantial

number of additional births compared to a situation of non-Indigenous rates

throughout. This is particularly the case for the 15–19 year age group.

As discussed in the previous section, in terms of the overall projected size of the

population, these differences in births and deaths cancel each other out to a large

degree. However, the same cannot be said for the age structure. Under all three

scenarios, the Indigenous population is projected to age relative to the base period.

This is demonstrated in Fig. 3, which shows the age distribution in 2006 alongside

Table 2 Projected Indigenous deaths under different mortality and fertility assumptions

Scenario 2006–2011 2011–2016 2016–2021 2021–2026 2026–2031 2006–2031

1. Indigenous rates 11,252 13,820 16,943 20,496 24,314 86,824

2. Convergence in

rates

10,635 11,650 12,809 14,033 15,185 64,312

3. Non-Indigenous

rates

6,063 7,399 9,441 12,122 15,284 50,308

Table 3 Projected Indigenous births under different mortality and fertility assumptions, Indigenous

mothers aged 15–19 and 20–24

Scenario 2006–2011 2011–2016 2016–2021 2021–2026 2026–2031 2006–2031

Indigenous mothers aged 15–19


2. Convergence in

rates

10,217 8,841 6,573 4,439 2,228 32,299

3. Non-Indigenous

rates

1,838 2,001 2,007 1,876 1,849 9,572

Indigenous mothers aged 20–24


2. Convergence in

rates

15,894 15,943 14,136 10,935 7,976 64,884

3. Non-Indigenous

rates

5,938 7,067 7,696 7,720 7,214 35,636


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the projected age structure under Scenario 1 (Indigenous fertility and mortality rates

throughout). Figure 4 compares Scenario 1 with Scenario 2.4

While a reduction in mortality and fertility rates inevitably leads to an ageing

population, the net effect in terms of dependency ratios is a lot more difficult to

predict a priori. As shown in Fig. 5, this net effect depends in part on the timing of

demographic changes, including the particular age at which mortality gaps exist, as

well as the relative gap in fertility (Bloom et al. 2003). To demonstrate this, the

number of people aged 15–64 years relative to those under 15 or 65 years and over

(the inverse dependency ratio) is shown in Fig. 5 for the three projection scenarios.

For comparison, the current and projected ratio for the non-Indigenous population is

also indicated.

The first thing to note is the more favourable inverse dependency ratio for the

non-Indigenous population at the start of the period. That there are fewer Indigenous

Australians of working age relative to those of non-working age (and, in particular,

those aged under 15) is likely to have contributed to ongoing relative Indigenous

disadvantage. Proportionally, there are many more Indigenous children across

which educational and other resources need to be spread.

Under all three scenarios, there are projected to be more Indigenous Australians

of working age relative to those of non-working age by the end of the period.

However, this increase is likely to be somewhat greater if the Closing the Gap

targets are met, especially towards the end of the projection period. Obviously, in

order to maximise benefit from this favourable age structure, it is necessary that

those entering working-age over the period are able to fully participate in Australian

society and this places a special focus on the role of Indigenous youth in

contributing to the overall strategy of Closing the Gap. To reflect on this, Fig. 6

Fig. 3 Age distribution of Indigenous Australians, 2006 estimated and 2031 projection (Scenario 1)

4 Unfortunately, the data that this analysis is based on does not give more detailed information for the

Indigenous population aged 65 years and over.


123

shows the per cent of the projected Indigenous population that is aged 15–29 years

under the various scenarios, as well as the projected per cent of the non-Indigenous

population in the same age group.

Under all three scenarios, the proportion of the Indigenous population

aged 15–29 years peaks at close to 30 % by 2016, 15 years earlier than the

projected peak in the inverse dependency ratio. Thus, the ability of government

to improve Indigenous education participation and attainment and facilitate

successful youth transitions during the next 5 years will have important policy

implications for the remainder of the projection period. This suggests a need for

immediacy in public policy impacts if the benefits of demographic transition are

to be realised.

Fig. 4 Age distribution of Indigenous Australians, 2031 projection (Scenarios 1, 2)

Fig. 5 Indigenous and non-Indigenous inverse dependency ratios, 2006–2031


123

Prospects for a demographic dividend

As so often demonstrated in Australian public policy, setting targets for Indigenous

population outcomes is one thing, actually achieving these can be quite another (Altman

et al. 2009). While the Scenario 2 projections above reflect success in meeting targets

there are a number of reasons to believe that actual outcomes will fall somewhere

between these and the Scenario 1 projections. Aside from the urgency attached to youth

participation noted above, there are broader underlying features of Indigenous

demographic transition in Australia that suggest some limits on likely impacts of policy.

The first issue to consider is the scale and underlying causes of disparity in adult

mortality. While prospects for convergence in infant mortality rates appear optimistic

(though not necessarily within the specified time frame—see Altman et al. 2009; Hoy

2009) there is less optimism with regard to the improvements necessary in Indigenous

adult mortality which is the overwhelming contributor to excess Indigenous deaths.

Lifestyle diseases such as cardiovascular disease, injury and poisoning and renal

failure account for a significant share of the mortality differential and age-specific

death rates for many of these conditions can be up to 20 times higher for both

Indigenous males and females (ABS/AIHW 2010). What is more, the preconditions

for such disparities are often established in the conditions of maternal health and early

childhood requiring whole-of-population improvement not least in the levels of

proximate socioeconomic determinants (Hoy 2009; Gray et al. 2004).

Also of note is the entrenched youthfulness of Indigenous fertility. While the

overall Indigenous TFR has fallen steadily since the 1980s and now sits at below

replacement level (Taylor and Kinfu 2005), the median age of Indigenous mothers

has remained largely unchanged since the 1970s at around 24 years (Smith 1980,

p. 261). In 2010, the median age of Indigenous mothers was 24.6 years which is

equivalent to the median for all mothers in Australia back in 1976. Furthermore,

fully 20 % of Indigenous births in 2010 were to teenage mothers compared to just

4 % for all mothers-the Indigenous teenage fertility rate was almost 5 times higher

at 76 per ‘000 compared to just 16 per ‘000 (ABS 2011).

Fig. 6 Proportion of Indigenous and non-Indigenous population aged 15–29 years, 2006–2031


123

This raises an issue about lack of movement into the second demographic

transition which is characterised by full control over fertility and a fall to well below

replacement level involving a shift in childbearing from younger to older ages.

Primary causes are attributed to a weakening of community, family and marriage as

the key institutions governing fertility choices against the rising influence of post-

transition factors such as gender equity, career building, self-actualization,

consumption and leisure aspirations (van de Kaa 2003; Lutz 2006; Lesthaege

2010). The extent to which the Indigenous fertility regime appears stuck in the first

transition may be construed as a measure of the degree to which these social

changes have yet to permeate Indigenous society (although there remains the

possibility of an Indigenous variant). Either way, current levels of Indigenous

participation in mainstream institutions of work and education remain relatively low

and it will require an increase in both the volume and quality of such participation if

current policy targets are to have their predicted effect on demography.

Discussion

Policy development in Indigenous affairs in Australia often proceeds with dated

population estimates and with little understanding of the likely impact of changing

demographic parameters on future Indigenous population size and composition. To

the extent that policy itself can influence demographic outcomes, this represents a

significant deficiency in current planning methodology. To stimulate a dialogue

around such issues, the present analysis models the demographic impact of the

current policy focus on ‘Closing the Gap’ between Indigenous and non-Indigenous

socioeconomic outcomes. The scenarios presented are heuristic only. They simply

reflect the logic of sustaining into the future recently observed demographic

parameters, compared to following through on the idea of convergence in socio-

demographic outcomes over timescales that reflect stated policy ambitions.

If current rates of fertility and mortality were to continue over the 25-year period

from 2006 to 2031, then the Indigenous population as a whole would increase from

517,023 to 847,915—a total increase of 64 %. This is necessarily a conservative

estimate, since it does not allow for any future error of census closure. This is partly

because this error is unpredictable, and partly because the longitudinal data required to

estimate shifting census capture are not available. Nonetheless, the annualised growth

rate of 2.0 % implied by this projection is lower than that observed in recent years.

Aside from the obvious impact of overall population size in setting the scale and

scope of policy liabilities, the main implications from the projections summarised in

this paper arise from shifts in age structure. Specifically, while our Closing the Gap

convergence scenario has little impact on overall future population levels, it does

affect the age composition of the population quite noticeably. This becomes much

older in profile than would otherwise be the case with enhanced rates of growth in

the populations of prime working age and old age and reduced growth in the infant

and school-age groups.

The Indigenous population in Australia is not large enough for this favourable

dependency ratio to translate to substantial improvements in economic growth rates


123

for Australia as a whole. However, it does have the potential to ameliorate labour

market shortages in particular geographic locations where Indigenous Australians

make up a sizable share of the population.

This enhancement of structural ageing in the Indigenous population raises a number

of issues regarding the urgency that might be afforded to policy efforts on education,

employment and retirement. As Jackson (2008, p. 225) has poignantly noted in regard

to the first of these, the non-Indigenous population was educated before it became ‘old’

and the risk now is that the Indigenous population will become old before it becomes

educated. This clearly has implications for future workforce participation and in this

regard Jackson (2008, p. 231) has also noted the potential for relative improvement in

Indigenous economic status presented by a demographic dividend—that period in

demographic transition when the bulk of the population is found in the key workforce

age groups with work, savings and investments potentially highest and dependency

ratios lowest (Bloom and Williamson 1998).

Against a background of population ageing, it is not only the level, but also the

nature of workforce participation that requires attention. The higher incidence of

poverty and shorter life expectancy may mean that Indigenous workers may have

access superannuation earlier than non-Indigenous workers (Pragnell 2002). None-

theless, the key constraint on retirement savings remains the relatively low Indigenous

occupational status and income alongside intermittent workforce participation

(Pragnell 2002). Thus, in order to counter a projected increased burden on pensions,

convergence of socioeconomic status will be required to manage the effects of

demographic convergence (Kirk 1996; Gray 1990 Caldwell 2002).

This somewhat optimistic Closing the Gap scenario still involves substantial

Indigenous disadvantage with 14,004 additional deaths and 51,945 additional births

compared to the scenario where Indigenous and non-Indigenous Australians had the

same age-specific fertility and mortality rates over the period. There are two ways to

look at the excess deaths and births that would occur if the scenario of no change in

Indigenous/non-Indigenous relativities transpired. On the one hand, it shows the

massive task ahead for all levels of Australian government. Given the poor record of

achieving substantial improvement in relative Indigenous outcomes historically, these

targets are clearly not going to be met without substantial structural change. The

second way to frame these projected excess deaths, however, is as a warning of the

development loss that would occur if the government was not able to achieve their aim.

Acknowledgments The authors would like to acknowledge that funding for this paper came from the

Australian Commonwealth and State/Territory governments through the Indigenous Populations Project.

In addition we would like to thank Professor Martin Bell and Dr Jeromey Temple for constructive

comments on earlier drafts of the paper and associated methodology. We would like to thank Gillian

Cosgrove who gave editorial assistance and prepared the final document as well as Mandy Yap and Hilary

Bek for detailed proofing. Finally, we would like to thank the two anonymous reviewers of the paper who

gave a number of thoughtful and insightful comments.

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