Report on Government Services 2025

PART A, SECTION 2: RELEASED ON 30 JANUARY 2025

2 Statistical context

In this section

Population
Family and household
Income and employment
Statistical concepts
References

The Statistical context contains information to assist interpretation of the performance information in this report. It includes information and data on population, families and households, and income and employment. Information on some of the statistical concepts that are used in the report is available in the Statistical concepts note.

Data referenced by a ‘2A’ prefix (for example, table 2A.1) is included in the data tables, which can be downloaded below.

Section 2 Data tables (XLSX 567.2 KB)
Section 2 dataset (CSV 1.4 MB)
Refer to the Statistical concepts document and corresponding table number in the data tables above for detailed definitions, caveats, footnotes and data source(s).

Population

The Australian people are the principal recipients of the government services covered by this report. The size, trends and characteristics of the population can have significant influences on the demand for government services and the cost of service delivery.

Population size and trends

More than three‑quarters of Australia’s 26.6 million people lived in the eastern mainland states as at 30 June 2023. As the majority of Australia’s population lives in the eastern mainland states, data for these jurisdictions generally has a large influence on national averages. Nationally, the average annual growth rate of the population between 2019 and 2023 was approximately 1.3% (table 2A.1).

As in most other developed economies, greater life expectancy and declining fertility have contributed to an ‘ageing’ of Australia’s population. However, the age distribution of Aboriginal and Torres Strait Islander people is markedly different to that of all Australians (figure 2.1). At 30 June 2023, 12.1% of Australia’s population was aged 70 years or over, compared with just 3.1% of Australia’s Aboriginal and Torres Strait Islander population as at 30 June 2021 (tables 2A.1 and 2A.4).

The most recent Census count of the Aboriginal and Torres Strait Islander population (2021) is used to make comparisons with the estimated Australian population for the same year (2021). Annual data is based on the 2021 Census of Population and Housing and is available in tables 2A.1 and 2A.4.

Aboriginal and Torres Strait Islander population

There were an estimated 983,709 Aboriginal and Torres Strait Islander people (49.8% female, similar to the total population) in Australia at 30 June 2021, accounting for approximately 3.8% of the total Australian population in 2021 (figure 2.2).

Population, by ethnicity and proficiency in English

Some new Australians face specific problems when accessing government services. Language and cultural differences can be formidable barriers for otherwise capable people. Cultural backgrounds can also have a significant influence on the support networks offered by extended families.

People born outside Australia accounted for 27.7% of the population in August 2021 (8.0% from the main English speaking countries and 19.7% from other countries) (table 2A.7). Of those born outside Australia, 89.4% spoke only English, or spoke another language as well as speaking English well or very well (table 2A.6). Approximately 22.3% of Australians spoke a language other than English at home in August 2021 (table 2A.8).

Population, by geographic location

Those living in remote areas can have greater difficulty in accessing government services, often needing to travel long distances, or facing lower service levels than provided in major cities. The Australian population is highly urbanised, with 72.6% of the population located in major cities as at 30 June 2023 (table 2A.3).

Family and household

Family structure

There were 7.6 million families in Australia in June 2024. Nationally, 36.2% of families had at least one child aged under 15 years, and 15.7% of families had at least one child aged under five years (table 2A.10). Lone parent families might have a greater need for government support and particular types of government services (such as childcare for respite reasons). Nationally in June 2024, 20.4% of families with children aged under 15 years were lone parent families (table 2A.11).

Employment status also has implications for the financial independence of families. Nationally in June 2024, in 3.4% of couple families with children aged under 15 years neither parent was employed and in 4.0% of lone parent families with children aged under 15 years, the parent was unemployed (table 2A.12).

Household profile

There were a projected 10.5 million households in Australia at 30 June 2024 (based on the 2021 Census), and 26.5% of these were lone person households (table 2A.14). As at 30 June 2024, the proportion of people aged 65 years or over who lived alone (24.8%) was around three times higher than the proportion for people aged 15–64 years (9.2%).

Income and employment

Income

Nationally in August 2021, 16.8% of people aged 15 years or over had a relatively low weekly individual income of $299 or less (table 2A.16). The proportion was higher for Aboriginal and Torres Strait Islander people (24.7%) and more than four times higher for younger people (73.9% for people aged 15–19 years) (tables 2A.17 and 2A.18).

Nationally, 17.0% of the total population was receiving income support in June 2024, an increase from 16.9% in June 2023 due to the increase in the proportion of people receiving single-parent payments (an increase from 0.9% in 2023 to 1.2% in 2024). The age pension was received by 9.6% of the population (63.5% of the qualifying population), while 2.9% received a disability support pension and a further 3.3% of the population received some form of labour market allowance (table 2A.19).

Employment and workforce participation

Of the 15.0 million people aged 15 years or over in the labour force in Australia in June 2024, 96.1% were employed. The majority of employed people (68.9%) were in full-time employment. Nationally, the unemployment rate was 3.9% (table 2A.24). The unemployment rate needs to be interpreted within the context of labour force participation rates (the proportion of the working age population either in employment or actively looking for work). The labour force participation rate for Australia was 67.0% in June 2024 (table 2A.24). When compared to June 2023, the unemployment rate has increased (from 3.3%) and the labour force participation rate has remained stable.

Income and employment are strongly influenced by education. Census data on highest level of schooling and type of educational institution attended is available in tables 2A.20–23. Additional educational data is also available in Part B of this report (Child care, education and training).

Statistical concepts

Expand all Collapse all

Adjusting financial data to real dollars

Time series financial data is adjusted to real dollars using an appropriate chain price deflator so that comparisons over time are not affected by inflation.

Most financial data in the report is deflated using the Australian Bureau of Statistics (ABS) general government final consumption expenditure (GGFCE) deflator. The exceptions are the Public hospitals section, the Services for mental health section, the Vocational education and training section and the Emergency services section (insurance claim tables only), which use service specific ABS deflators to calculate real dollars. All sections use an identical process for deflating financial data which consists of two steps: re-basing the deflator and converting nominal dollars to real dollars (box 1).

Box 1 – Deflator formulas

Step 1. The formula used to re-base deflators is

D_{t} = 100 \times \frac{O_{t}}{B}

where:

$D_{t}$ is the re-based deflator in financial year $t$ ; $O_{t}$ is the index in June of financial year $t$ ; $B$ is the index in June of the financial year that will be the new base.

Step 2. The formula to convert nominal dollars to real dollars is

$R_{t} = \frac{N_{t}}{D_{t}} \times 100$

where, for financial year $t$ :

$R_{t}$ is real dollars; $N_{t}$ is nominal dollars; $D_{t}$ is the deflator.

The process used for deflating financial data is demonstrated below, using the GGFCE deflator as an example.

Step 1. Re-basing a deflator (table 1).

The ABS publishes the GGFCE deflator with the base year lagged two years (for example, for June 2024 the available deflator has a base year of June 2022 = 100). This report requires a base year of 2022-23 and 2023-24. Table 1 shows how the GGFCE deflator is rebased for use in this report. Five GGFCE deflator series are published, from 2019-20 = 100 to 2023-24 = 100 (table 2A.26).

**Table 1 – Re-basing the GGFCE deflator^a**
Year	ABS chain price index (June 2022 = 100)	Calculation	Financial year	Re-based GGFCE deflator (June 2024 = 100)
June 2020	96.1	96.1∕109.7 × 100	2019-20	87.6
June 2021	97.2	97.2/109.7 × 100	2020-21	88.6
June 2022	100.0	100.0/109.7 × 100	2021-22	91.2
June 2023	104.6	104.6/109.7 × 100	2022-23	95.4
June 2024	109.7	109.7/109.7 × 100	2023-24	100.0

a Based on the chain price index values from ABS (2024).

Source: ABS (2024), ‘Table 36. Expenditure on Gross Domestic Product (GDP), Chain volume measures and Current prices, Annual’ [time series spreadsheet], Australian National Accounts: National Income, Expenditure and Product, June 2024, https://www.abs.gov.au/statistics/economy/national-accounts/australian-national-accounts-national-income-expenditure-and-product/jun-2024, accessed 4 September 2024; table 2A.26.

Step 2. Converting nominal dollars into real dollars (table 2).

Nominal dollars are converted into real dollars by dividing the nominal dollars by the GGFCE deflator for the applicable financial year and multiplying by 100. The deflator used may vary according to the most current year for which financial data is available. For example, if the most current data is for 2022‑23 then the data is deflated using the deflator series for 2022-23 = 100. If the most current data is for 2023‑24 then the data is deflated using the deflator series for 2023‑24 = 100. Table 2 shows how the GGFCE deflator for 2023‑24= 100 is applied.

**Table 2 – Applying the GGFCE deflator to derive real dollars^a**
Financial year	Nominal expenditure	GGFCE deflator (2023-24 = 100)	Calculation	Real expenditure
2019-20	6,300	87.6	(6,300/87.6) × 100	7,192
2020-21	6,350	88.6	(6,350/88.6) × 100	7,167
2021-22	6,485	91.2	(6,485/91.2) × 100	7,111
2022-23	7,020	95.4	(7,020/95.4) × 100	7,358
2023-24	7,200	100.0	(7,200/100.0) × 100	7,200

a Based on the chain price index values from ABS (2024).

Source: Table 1.

Reliability of estimates

Data for some indicators in this report is based on samples, either from surveys or observations from, for example, administrative data sets. The potential for sampling error (the error that occurs by chance because the data is obtained from a sample and not the entire population) means that the reported estimates might not accurately reflect the true value.

This report indicates the reliability of estimates based on samples generally by reporting either relative standard errors (RSEs) or confidence intervals (CIs). RSEs and CIs are calculated based on the standard error (SE). The larger the SE, RSE or CI, the less reliable the estimate is as an indicator for the whole population (ABS 2015).

Standard error

The SE measures the sampling error of an estimate (box 2). (There can also be non‑sampling error, or systematic biases, in data.) There are several types of SE. A commonly used type of SE in this report is the SE of the mean (average), which measures how much the estimated mean value might differ from the true population mean value.

Box 2 – Standard error

The SE of a method of measurement or estimation is the estimated standard deviation of the error in that method. Specifically, it estimates the standard deviation of the difference between the measured or estimated values and the true values. Standard deviation is a measure of how spread out the data is, that is, a measure of variability.

The SE of the mean, an unbiased estimate of expected error in the sample estimate of a population mean, is the sample estimate of the population standard deviation (sample standard deviation) divided by the square root of the sample size (assuming statistical independence of the values in the sample):

${SE}_{\bar{x}} = \frac{s}{\sqrt{n}}$

Where:

${SE}_{\bar{x}}$ is the SE of the sample estimate of a population mean, $S$ is the sample’s standard deviation (the sample based estimate of the standard deviation of the population), and $n$ is the size (number of items) of the sample.

Decreasing the uncertainty of a mean value estimate by a factor of two requires the sample size to increase fourfold. Decreasing SE by a factor of ten requires the sample size to increase hundredfold.

Relative standard error

The RSE is used to indicate the reliability of an estimate (box 3). The RSE shows the size of the error relative to the estimate and is derived by dividing the SE of the estimate by the estimate. The higher the RSE, the less confidence there is that the sample estimate is close to the true value of the population mean. A rule adopted in this report is that estimates with an RSE of less than 25% are considered reliable, estimates with an RSE between 25% and 50% are to be used with caution, and estimates with an RSE greater than 50% are considered too unreliable for general use.

Box 3 – Relative standard error

The SE can be expressed as a proportion of the estimate – known as the RSE. The formula for the RSE of an estimate is:

$RSE (x) = \frac{SE (x)}{x}$

Where:

$x$ is the estimate and $SE (x)$ is the SE of the estimate.

RSEs are multiplied by 100 and expressed as a percentage.

Proportions and percentages formed from the ratio of two estimates are also subject to sampling error. The size of the error depends on the accuracy of both the numerator and the denominator.

For proportions where the numerator is a subset of the denominator, for example the ratio of people who completed a certification over the people who attended the training to get the certification, then an approximation of the RSE can be calculated using the following formula:

$RSE (\frac{x}{y}) = \sqrt{{[RSE (x)]}^{2} - {[RSE (y)]}^{2}}$

Where:

$x$ is the numerator, and $y$ is the denominator, of the estimated proportion.

For proportions where the denominator and numerator are independent estimates (for example, a ratio of rates regarding two separate populations such as Aboriginal and/or Torres Strait Islander and non-Indigenous), and where the RSEs on the denominator and numerator are small, an approximation of the RSE can be calculated using the following formula:

$RSE (\frac{x}{y}) = \sqrt{{[RSE (x)]}^{2} + {[RSE (y)]}^{2}}$

Note that the formulas shown above for approximating the RSE of a proportion are considered unsuitable when the RSE of the numerator is close to, or below, the RSE of the denominator. In this case, it is recommended to use the following formula to calculate the RSE of the proportion:

$RSE (\frac{x}{y}) = \sqrt{{[RSE (x)]}^{2} + (1 - \frac{2 x}{y}) \times {[RSE (y)]}^{2}}$

Source: ABS (2019).

Confidence intervals

Confidence intervals (CIs) are used to indicate the reliability of an estimate. A CI is a specified interval, with the sample statistic at the centre, within which the corresponding population value can be said to lie with a given level of confidence (ABS 2015). Increasing the desired confidence level will widen the CIs (figure 2.3). CIs are useful because a range, rather than a single estimate, is more likely to encompass the real figure for the population value being estimated.

CIs are calculated from the population estimate and its associated SE. The CI used most commonly is calculated for 95% levels of probability, with 95% of all values falling within 1.96 standard errors of the mean. For example, if the estimate from a survey was that 628,300 people report having their needs fully met by a government service, and the associated SE of the estimate was 10,600 people, then the 95% CI would be calculated by:

$lower confidence limit = 628,300 - (1.96 \times 10,600) = 628,300 - 20,776 = 607,524$
$upper confidence limit = 628,300 + (1.96 \times 10,600) = 628,300 + 20,776 = 649,076$

This indicates that we can be 95% sure the true number of people who perceive that their needs are met by a government service is between 607,524 and 649,076.

The smaller the SE of the estimate, the narrower the CIs and the closer the estimate can be expected to be to the true value.

Figure 2.3 – Normal distribution with 95% confidence intervals

CIs also test for statistical differences between sample results (box 4).

Box 4 – Using confidence intervals to test for statistical significance

The CIs – the value ranges within which estimates are likely to fall – can be used to test whether the results reported for two estimated proportions are statistically different. If the CIs for the results do not overlap, then there can be confidence that the estimated proportions differ from each other. To test whether the 95% CIs of two estimates overlap, a range is derived using the following formulas:

$R_{1} = (\frac{x_{2}}{y_{2}} - \frac{x_{1}}{y_{1}}) - 1.96 \sqrt{{(RSE (\frac{x_{2}}{y_{2}}) \times (\frac{x_{2}}{y_{2}}))}^{2} + {(RSE (\frac{x_{1}}{y_{1}}) \times (\frac{x_{1}}{y_{1}}))}^{2}}$

and

$R_{2} = (\frac{x_{2}}{y_{2}} - \frac{x_{1}}{y_{1}}) + 1.96 \sqrt{{(RSE (\frac{x_{2}}{y_{2}}) \times (\frac{x_{2}}{y_{2}}))}^{2} + {(RSE (\frac{x_{1}}{y_{1}}) \times (\frac{x_{1}}{y_{1}}))}^{2}}$

If none of the values in this range is zero, then the difference between the two estimated proportions is statistically significant.

For example, consider survey data that estimated that the proportion of people who perceived that their needs were met by government services was 50% in jurisdiction A, with a 95% CI of ±5%, and 25% of people in jurisdiction B, with a 95% CI of ±10%. These results imply that we can be 95% sure the true result for jurisdiction A lies between 55% and 45%, and the true result for jurisdiction B lies between 15% and 35%. As these two ranges do not overlap, it can be said that the results for jurisdiction A and jurisdiction B are statistically significantly different.

Variability bands

Rates derived from administrative data counts are not subject to sampling error but might be subject to natural random variation, especially for small counts. For mortality data, variability bands are used to account for this variation (box 5).

Box 5 – Variability bands

The variability bands to be calculated using the standard method for estimating 95% confidence intervals are:

Crude rate (CR)

$CI {(CR)}_{95 %} = CR \pm 1.96 \frac{CR}{\sqrt{\sum_{i = 1}^{I} d}}$

Where:

$d$ is the numerator of the estimated proportion.

Age-standardised rate (ASR)

$CI {(ASR)}_{95 %} = ASR \pm 1.96 \sqrt{\sum_{i = 1}^{I} \frac{w_{i}^{2} d_{i}}{n_{i}^{2}}}$

Where:

$w_{i}$ is the proportion of the standard population in age group $i$

$d_{i}$ is the number of deaths in age group $i$

$n_{i}$ is the number of people in the population in age group $i$ .

Infant mortality rate (IMR)

$CI {(IMR)}_{95 %} = IMR \pm 1.96 \frac{IMR}{\sqrt{d_{0}}}$

Where:

$d_{0}$ is the number of deaths in infants aged less than one year.

Variability bands accompanying mortality data should be used for the purpose of within jurisdiction analysis at a point in time and over time. They should not be used for comparing mortality rates at a single point in time or over time between jurisdictions as they do not account for differences in under identification of Aboriginal and Torres Strait Islander people’s deaths between jurisdictions.

Typically, in this standard method, the observed rate is assumed to have natural variability in the numerator count (for example, deaths) but not in the population denominator count. Variations in Aboriginal and Torres Strait Islander people’s death rates may arise from uncertainty in the recording of Indigenous status on the death registration forms (in particular, under‑identification of Aboriginal and Torres Strait Islander people’s deaths) and in the ABS Census of Population and Housing, from which population estimates are derived. These variations are not considered in this method. Also, the rate is assumed to have been generated from a normal distribution (figure 2.3). Random variation in the numerator count is assumed to be centred around the true value – that is, there is no systematic bias.

Population measures

Data is frequently expressed relative to population in this report. For example, expenditure per person, or proportion of people who utilise a service or who benefit from a service. This enables comparison of data across populations of different sizes using relative numbers – standardised by population size – as distinct from absolute numbers.

Estimated Resident Population (ERP) data is available quarterly – that is, at end March, June, September, and December of each year. The midpoint ERP is typically used for the calculation of population rates in this report – for example, the 30 June ERP for calendar year data (table 2A.1) and the 31 December ERP for financial year data (table 2A.2).

This report uses first preliminary ERP data wherever possible and replaces this with final rebased data when available. For the 2025 report, this equates to:

for June, ERP for 2014 to 2016 are final based on the 2016 Census of Population and Housing; ERP for 2017 to 2021 are final based on the 2021 Census; ERP from 2022 are first preliminary based on the 2021 Census
for December, ERP for 2014 to 2015 are final based on the 2016 Census of Population and Housing; ERP for 2016 to 2020 are final based on the 2021 Census; ERP from 2021 are first preliminary based on the 2021 Census.

Aboriginal and Torres Strait Islander population

This year’s Report on Government Services uses data from the ABS’ estimates and projections of the Aboriginal and Torres Strait Islander population, based on the 2021 Census. The 2021 Census-based population data include the estimated resident population as at 30 June 2021, plus an updated time series for previous periods (‘backcast’) and for forward periods (‘projections’). This approach is consistent with RoGS’ use of the most up-to-date Aboriginal and Torres Strait Islander population data available from the ABS at the time of publication.

The use of the 2021 Census-based population series has had a material impact on the Aboriginal and Torres Strait Islander rates in the report. Across the time series, the 2021 Census-based estimates and projections of the Aboriginal and Torres Strait Islander population are about 12% higher than the those based on the 2016 Census. This is due to the growth in the Aboriginal and Torres Strait Islander population, which increased by 25.2% between 2016 and 2021. Non-demographic factors (such as changes in the propensity of people to identify as an Aboriginal and Torres Strait Islander person) accounted for the majority of this growth (ABS 2023).

As a result, Aboriginal and Torres Strait Islander rates in this report are generally lower than rates in the 2024 report and may differ from results published elsewhere. Based on advice from the ABS, the time series for indicators and measures which draw on Aboriginal and Torres Strait Islander population data in this report have been shortened (generally no further back than the penultimate (2016) Census).

Average annual growth rate

This report presents a growth rate to facilitate meaningful comparisons of changes over time. The method used is the average annual growth rate (AAGR) which is the uniform growth rate that would need to have applied each year for the value in the first year to grow to the value in the final year of the period of analysis (box 6).

Box 6 – Average annual growth rate

The formula for calculating a compound average annual growth rate (AAGR) is:

${AAGR}_{(t_{0}, t_{n})} = [{(\frac{P_{(t_{n})}}{P_{(t_{0})}})}^{(\frac{1}{t_{n} - t_{0}})} - 1] \times 100$

Where:

$P_{(t_{0})}$ is the value in the initial period, $P_{(t_{n})}$ is the value in the last period and $t_{n} - t_{0}$ is the number of periods (which will be one less than the total number of years).

Age-standardisation of data

Rationale for age-standardisation of data

The age profile of Australian people varies across jurisdictions, periods of time, geographic areas and/or population subgroups (for example, between Aboriginal and Torres Strait Islander people and non‑Indigenous people). Variations in age profiles are important because they can affect the likelihood of using a particular service (such as a public hospital) or particular ‘events’ occurring (such as death, incidence of disease or incarceration). Age‑standardisation adjusts for the effect of variations in age profiles when comparing service usage, or rates of particular events across different populations.

Calculating age-standardised rates

Age‑standardisation adjusts each of the comparison/study populations (for example, Aboriginal and Torres Strait Islander people and non‑Indigenous people) against a standard population (box 7). The latest standard population used is the final 30 June ERP for the 2001 (AIHW 2015)¹. The result is a standardised estimate for each of the comparison/study populations.

The report generally publishes age‑standardised rates that have been calculated using either one of two methods, as appropriate.

The direct method is generally used for comparisons between study groups and is recommended by the AIHW (2011) for the purposes of comparing health and welfare outcome measures (for example, mortality rates, life expectancy, hospital separation rates and disease incidence rates) of Aboriginal and Torres Strait Islander people and non‑Indigenous people.
The indirect method is recommended when the age‑specific rates for the population being studied are not known (or are unreliable), but the total number of events is known (AIHW 2015).

The direct method has three steps:

Step 1: Calculate the age‑specific rate for each age group for the study/comparison group.
Step 2: Calculate the expected number of ‘events’ in each age group by multiplying the age‑specific rates by the corresponding standard population.
Step 3: Sum the expected number of cases in each age group and divide by the total of the standard population.

The indirect method has four steps:

Step 1: Calculate the age‑specific rates for each age group in the standard population.
Step 2: Apply the age‑specific rates resulting from step 1 to the number in each age group of the study population and sum to derive the total ‘expected’ number of cases for the study population.
Step 3: Divide the observed number of events in the study population by the ‘expected’ number of cases for the study population derived in step 2.
Step 4: Multiply the result of step 3 by the crude rate in the standard population.

Box 7 – Direct and indirect age-standardisation

The formula for deriving the age-standardised rate using the direct method is:

ASR = \frac{\sum (r_{i} P_{i})}{\sum P_{i}}

The formula for deriving the age-standardised rate using the indirect method is:

$ASR = \frac{C}{\sum (R_{i} p_{i})} \times R$

Where:

$ASR$ is the age-standardised rate for the population being studied

$r_{i}$ is the age group specific rate for age group $i$ in the population being studied

$P_{i}$ is the population of age group $i$ in the standard population

$C$ is the observed number of events in the population being studied

$\sum (R_{i} p_{i})$ is the expected number of events in the population being studied

$R_{i}$ is the age group specific rate for age group $i$ in the standard population

$p_{i}$ is the population for age group $i$ in the population being studied

$R$ is the crude rate in the standard population.

Source: AIHW (2015).

Tables 3–4 contain examples of the application of direct and indirect age‑standardisation, respectively. Age‑standardised rates are generally multiplied by 1,000 or 100,000 to avoid small decimal fractions. They are then reported as age‑standardised rates per 1,000 or 100,000 people (AIHW 2015).

Table 3 – Age-standardisation of data using the direct method

**Step 1**
Age groups	Aboriginal and Torres Strait Islander people			Non‑Indigenous people
	Population	People with severe / profound limitations	Age‑specific severe / profound limitations	Population	People with severe / profound limitations	Age‑specific severe / profound limitations
	$C1$	$C2$	$C3 = C2 ∕ C1 \times 100$	$C4$	$C5$	$C6 = C5 ∕ C4 \times 100$
18–24	54,400	2,800	5.1	1,869,200	34,200	1.8
25–29	36,300	1,600	4.4	1,389,700	24,700	1.8
30–34	34,800	2,800	8.0	1,458,500	37,100	2.5
35–39	31,200	1,600	5.1	1,432,000	43,900	3.1
40–44	26,600	2,800	10.5	1,475,000	70,200	4.8
45–49	20,600	2,000	9.7	1,366,300	43,800	3.2
50–54	17,700	3,000	16.9	1,263,900	47,900	3.8
55–59	12,400	1,400	11.3	1,060,700	63,500	6.0
60–64	7,000	1,100	15.7	816,400	49,700	6.1
65+	12,900	3,200	24.8	2,222,200	283,400	12.8
Total	253,900	22,300	8.8	14,353,900	698,400	4.9

**Step 2**
Age groups	Standard population	Aboriginal and Torres Strait Islander people expected number of ‘events’	Non‑Indigenous people expected number of ‘events’
	$C7$	$C8 = C7 \times C3 ∕ 100$	$C9 = C7 \times C6 ∕ 100$
18–24	1,844,162	94,920	33,742
25–29	1,407,081	62,020	25,009
30–34	1,466,615	118,004	37,306
35–39	1,492,204	76,523	45,746
40–44	1,479,257	155,711	70,403
45–49	1,358,594	131,902	43,553
50–54	1,300,777	220,471	49,298
55–59	1,008,799	113,897	60,393
60–64	822,024	129,175	50,042
65+	2,435,534	604,163	310,607
Total	14,615,047	1,706,787	726,098

**Step 3**
	Aboriginal and Torres Strait Islander people age-standardised rate	Non Indigenous people age-standardised rate
	$C10 = \sum C8 ∕ \sum C7 \times 100$	$C11 = \sum C9 ∕ \sum C7 \times 100$
Total	11.7	5.0

Source: AIHW (Australian Institute of Health and Welfare) 2006, ‘Potential Population’– Updating the Indigenous factor in disability services performance indicator denominators, Welfare Working Paper Series Number 50, Cat. no. DIS 45, Canberra;
ABS (2008) Population by Age and Sex, Australian states and territories , June 2007, Cat. no. 3201.0, Canberra.

Table 4 – Age‑standardisation of data using the indirect method^a,b

Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
$C$ – Observed number of imprisonments
Aboriginal and Torres Strait Islander people	3,467.0	715.1	3,442.0	2,564.6	728.1	154.3	101.4	1,609.4	12,781.8
Non-Indigenous people	8,906.0	5,800.3	6,146.6	3,821.3	2,227.3	479.3	284.7	256.3	27,921.7

Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
$p_{i}$ – Study populations^c
Aboriginal and Torres Strait Islander people
18–19 years	12,862	2,921	10,239	4,277	1,930	1,180	422	2,826	36,659
20–24 years	30,115	7,377	24,177	10,358	4,617	2,752	1,030	6,916	87,359
25–29 years	26,569	6,815	21,728	9,868	4,247	2,380	939	6,752	79,312
30–34 years	22,176	5,693	18,287	9,037	3,723	2,215	762	6,328	68,228
35–39 years	18,630	4,480	15,621	7,797	3,128	2,023	618	5,545	57,851
40–44 years	15,950	3,798	13,615	6,650	2,461	1,659	518	4,825	49,480
45–54 years	32,845	7,573	27,223	12,118	5,149	3,379	920	8,658	97,902
55+ years	46,708	10,093	34,495	14,758	6,540	5,476	1,035	9,257	128,437
Non‑Indigenous people
18–19 years	168,615	143,731	114,320	57,397	38,107	10,552	10,958	3,137	546,876
20–24 years	468,803	406,987	306,583	154,291	106,107	28,905	33,297	10,072	1,515,231
25–29 years	532,331	475,941	334,619	173,927	115,474	37,411	38,594	16,227	1,724,790
30–34 years	570,246	503,758	348,032	195,839	117,388	37,346	38,174	17,505	1,828,592
35–39 years	565,466	493,192	351,447	202,406	118,528	33,995	36,546	15,425	1,817,348
40–44 years	509,679	430,074	325,301	179,727	106,942	30,589	31,730	12,685	1,627,016
45–54 years	979,947	819,490	656,091	346,796	220,710	66,679	54,848	23,101	3,168,279
55+ years	2,317,824	1,821,544	1,469,114	747,141	578,738	188,368	104,926	38,295	7,267,584

Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
$N_{i}$ – Number of prisoners (30 June 2001)
All people
18–19 years									972
20–24 years									4,681
25–29 years									4,856
30–34 years									3,986
35–39 years									2,889
40–44 years									1,947
45–54 years									2,056
55+ years									1,002
Total									22,389

Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
$S_{i}$ – Standard population (30 June 2001)
All people
18–19 years									541,750
20–24 years									1,302,412
25–29 years									1,407,081
30–34 years									1,466,615
35–39 years									1,492,204
40–44 years									1,479,257
45–54 years									2,659,371
55+ years									4,266,357
Total									14,615,047

**Step 1: Calculate $R_{i}$ as $N_{i} / S_{i} * 100,000$**
Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
$R_{i}$ – Standard population age‑specific imprisonment rates per 100,000 adults (30 June 2001)
18–19 years									179.42
20–24 years									359.41
25–29 years									345.11
30–34 years									271.78
35–39 years									193.61
40–44 years									131.62
45–54 years									77.31
55+ years									23.49
Total									153.19

**Step 2: $(R_{i} ⁢ p_{i}) ∕ 100,000$**
Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
Aboriginal and Torres Strait Islander people
18–19 years	23.1	5.2	18.4	7.7	3.5	2.1	0.8	5.1	65.8
20–24 years	108.2	26.5	86.9	37.2	16.6	9.9	3.7	24.9	314.0
25–29 years	91.7	23.5	75.0	34.1	14.7	8.2	3.2	23.3	273.7
30–34 years	60.3	15.5	49.7	24.6	10.1	6.0	2.1	17.2	185.4
35–39 years	36.1	8.7	30.2	15.1	6.1	3.9	1.2	10.7	112.0
40–44 years	21.0	5.0	17.9	8.8	3.2	2.2	0.7	6.4	65.1
45–54 years	25.4	5.9	21.0	9.4	4.0	2.6	0.7	6.7	75.7
55+ years	11.0	2.4	8.1	3.5	1.5	1.3	0.2	2.2	30.2
Total	376.7	92.6	307.3	140.2	59.6	36.2	12.6	96.4	1,121.9
Non‑Indigenous people
18–19 years	302.5	257.9	205.1	103.0	68.4	18.9	19.7	5.6	981.2
20–24 years	1,684.9	1,462.8	1,101.9	554.5	381.4	103.9	119.7	36.2	5,445.9
25–29 years	1,837.1	1,642.5	1,154.8	600.2	398.5	129.1	133.2	56.0	5,952.4
30–34 years	1,549.8	1,369.1	945.9	532.3	319.0	101.5	103.7	47.6	4,969.8
35–39 years	1,094.8	954.9	680.4	391.9	229.5	65.8	70.8	29.9	3,518.5
40–44 years	670.8	566.1	428.2	236.6	140.8	40.3	41.8	16.7	2,141.5
45–54 years	757.6	633.6	507.2	268.1	170.6	51.6	42.4	17.9	2,449.4
55+ years	544.4	427.8	345.0	175.5	135.9	44.2	24.6	9.0	1,706.9
Total	8,442.0	7,314.6	5,368.6	2,862.0	1,844.1	555.3	555.8	218.8	27,165.6

**Step 3: $C ∕ ('Total' from Step 2) ⁢$**
Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
Aboriginal and Torres Strait Islander people	9.2	7.7	11.2	18.3	12.2	4.3	8.0	16.7	11.4
Non-Indigenous people	1.1	0.8	1.1	1.3	1.2	0.9	0.5	1.2	1.0

**Step 4: $(Result of Step 3) \times ('Total' from Step 1)$**
Variable	NSW	Vic	Qld	WA	SA	Tas	ACT	NT	Aust
Age‑standardised rate (per 100,000 adults)
Aboriginal and Torres Strait Islander people	1,409.9	1,182.4	1,716.1	2,802.3	1,870.1	652.1	1,232.4	2,558.2	1,745.3
Non-Indigenous people	161.6	121.5	175.4	204.5	185.0	132.2	78.5	179.4	157.5

a Rates are based on the indirect standardisation method, applying age group imprisonment rates derived from Prison Census data. b Rates are based on the 2021-22 daily average prisoner populations supplied by states and territories, calculated against adult population figures at December 2021 for people aged 18 or over, reflecting the age at which people are remanded or sentenced to adult custody. c The Aboriginal and Torres Strait Islander study population as at 31 December 2021 is derived as the average of two June projections based on the 2021 Census of Population and Housing, and on the medium series for the fertility assumption. The non‑Indigenous study population is calculated by subtracting the Aboriginal and Torres Strait Islander study population from the total preliminary estimated resident population as at 31 December 2021 based on the 2021 Census. Australia total population includes other territories.

Source: State and territory governments (unpublished); ABS 2024, ‘Table 4’ [data set] and ‘Projected resident population’ [Data Explorer], Estimates and Projections, Aboriginal and Torres Strait Islander Australians, 2011 to 2031, https://www.abs.gov.au/statistics/people/aboriginal-and-torres-strait-islander-peoples/estimates-and-projections-aboriginal-and-torres-strait-islander-australians/2011-2031, accessed 11 October 2024; ABS 2022 'Quarterly Population Estimates (ERP)' [Data Explorer], National, state and territory population, December 2021, https://www.abs.gov.au/statistics/people/population/national-state-and-territory-population/dec-2021, accessed 22 August 2022; ABS 2013, 'Standard population for use in age-standardisation table' [data set], Australian Demographic Statistics, June 2001, https://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/3101.0Main+Features1Mar%202013?OpenDocument, accessed 23 July 2024; ABS 2002, 'Summary information of all prisoners, by demographic and legal characteristics' [data set], Prisoners in Australia, 2001, https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/4517.02001?OpenDocument, accessed 21 October 2024; Steering Committee for the Review of Government Service Provision 2025, Report on Government Services 2025, table 8A.5.

Refer to page 2.27 in SCRGSP (2015) for the background on choice of year for the standard population and timeline for revision. Locate Footnote 1 above

References

ABS (Australian Bureau of Statistics) 2015, Statistical Language – Statistical Language Glossary, https://www.abs.gov.au/websitedbs/a3121120.nsf/ 00000000000000000000000000000000/1cf6fb476c3de1c7ca257b55002261f2 (accessed 14 September 2015).

—— 2019, TableBuilder, User Guide, https://www.abs.gov.au/ausstats/abs@.nsf/Lookup/1406.0.55.005main+features110User+Guide (accessed 4 October 2021).

—— 2023, Understanding change in counts of Aboriginal and Torres Strait Islander Australians: Census, https://www.abs.gov.au/statistics/people/aboriginal-and-torres-strait-islander-peoples/understanding-change-counts-aboriginal-and-torres-strait-islander-australians-census/2021 (accessed 16 October 2024).

—— 2024, ‘Table 36. Expenditure on Gross Domestic Product (GDP), Chain volume measures and Current prices, Annual’ [time series spreadsheet], Australian National Accounts: National Income, Expenditure and Product, June 2024, https://www.abs.gov.au/statistics/economy/national-accounts/australian-national-accounts-national-income-expenditure-and-product/jun-2024 (accessed 4 September 2024).

AIHW (Australian Institute of Health and Welfare) 2011, Principles on the use of direct age-standardisation in administrative data collections: for measuring the gap between Indigenous and non-Indigenous Australians, Cat. no. CSI 12.

—— 2015, Age‑standardised rate, METeOR, https://meteor.aihw.gov.au/content/index.phtml/itemId/327276 (accessed 18 September 2019).

SCRGSP (Steering Committee for the Review of Government Service Provision) 2015, Report on Government Services 2015, Productivity Commission.

A PDF of Part A Approach to performance reporting can be downloaded from the Part A Approach to performance reporting page.