EXPLORING THE GAP IN LABOUR MARKET OUTCOMES FOR ABORIGINAL AND TORRES STRAIT ISLANDER PEOPLES


CONTENTS
- Introduction
- What is the Gap?
- Two different populations
- 'All things being equal...'
- Standardising for labour force participation
- Standardising for unemployment
- Other factors
- Looking ahead

EXPLANATORY INFORMATION
- Endnotes
- Data sources and definitions

Related terms

Closing the Gap, Indigenous, non-Indigenous, employed, unemployed, education, participation rate, unemployment rate, employment outcomes, remoteness, health


INTRODUCTION

In 2008, the Council of Australian Governments (COAG) agreed to a number of targets to address disadvantage faced by Indigenous Australians. This included halving the gap in employment outcomes between Indigenous and other Australians by 2018.¹

Understanding this gap is key to addressing it - what factors contribute to it? How much does any one factor contribute? What can be changed?

This article looks at the differences between the labour market outcomes of Aboriginal and Torres Strait Islander and non-Indigenous people by examining some key characteristics that may influence labour force participation and unemployment levels. It then creates a number of 'what if' scenarios that show what the gap in participation and unemployment rates would look like if characteristics like health or education were the same for both Aboriginal and Torres Strait Islander and non-Indigenous people.
WHAT IS THE GAP?

In 2011, Aboriginal and Torres Strait Islander people aged 15-64 were less likely to be participating in the labour force than non-Indigenous people of the same age by a gap of 20.5 percentage points (55.9% compared with 76.4%). For both populations, women were less likely than men to be participating in the labour force.
Aboriginal and Torres Strait Islander people aged 15-64 were more than three times as likely as non-Indigenous people in the same age group to be unemployed (17.2% of those in the labour force compared with 5.5% - a gap of 11.7 percentage points). Aboriginal and Torres Strait Islander men were more likely to be unemployed (18.2%) than Aboriginal and Torres Strait Islander women (16.1%), while rates for non-Indigenous men and women were the same.

TWO DIFFERENT POPULATIONS

The Aboriginal and Torres Strait Islander and non-Indigenous populations are quite different in structure. Most notably, Aboriginal and Torres Strait Islander peoples have a younger age profile than non-Indigenous people:
Labour force participation may differ depending on how old someone is and what stage of their lives they are at. Younger people, for example, may be studying rather than working or looking for work, while older people may be retired (and therefore no longer in the labour force). Populations with more younger or older people generally have lower overall participation rates than those with higher proportions of people aged 25-54.

Levels of unemployment also tend to vary across age groups. Young people aged 15-24 have higher unemployment rates,² partly reflecting their lack of relevant work experience compared with older jobseekers. As the Aboriginal and Torres Strait Islander population has a larger proportion of young people than the non-Indigenous population, this is likely to be influencing the higher unemployment rate for this population.

Remoteness

Work opportunities in regional and remote areas of Australia differ from those in major cities because of the nature of their labour markets, with differing types and availability of work. As Aboriginal and Torres Strait Islander peoples are more likely to live in remote areas of Australia than non-Indigenous people, this may have an effect on their labour market outcomes.

In 2011, Aboriginal and Torres Strait Islander people were twelve times as likely to live in remote or very remote areas as non-Indigenous people (22.1% compared with 1.8%), while seven out of ten non-Indigenous people (71.9%) lived in major cities: more than double the proportion of Aboriginal and Torres Strait Islander people (34.9%).


Labour force participation across remoteness areas has also been shown to vary with age³ so the combination of younger age and remoteness for the Aboriginal and Torres Strait Islander population may have a greater effect on outcomes.

Education

Education has an effect on labour market outcomes. In 2011, 83.3% of people aged 15 to 64 with Year 12 or higher qualifications were participating in the labour force, compared with 60.8% of those with qualifications below Year 12. Just under 5% of people with Year 12 or higher qualifications were unemployed, compared with 9.1% of those with qualifications lower than Year 12.

Aboriginal and Torres Strait Islander people were far less likely than non-Indigenous people to have completed Year 12 or higher qualifications (35.9% compared with 67.3%).


Health and disability

Poor health or disability may have an impact on labour market outcomes. In 2012-13, after adjusting for age, Aboriginal and Torres Strait Islander people were more likely than non-Indigenous people to have chronic health conditions such as diabetes, kidney disease and heart disease, and in 2009, again adjusting for age, they were almost twice as likely as non-Indigenous people to be living with disability.

Using self-assessed health as an overall indicator of health, Aboriginal and Torres Strait Islander people aged 15-64 were almost twice as likely as non-Indigenous working age people to have reported only fair or poor health in 2012-13 (23.1% compared with 11.8%).


In 2012-13, 44.6% of Aboriginal and Torres Strait Islander people and 60.2% of non-Indigenous people who reported fair or poor health were in the labour force, compared with 64.8% of Aboriginal and Torres Strait Islander people and 82.6% of non-Indigenous people reporting good, very good or excellent health.
'ALL THINGS BEING EQUAL...'

One of the ways to understand how much the different characteristics of the Aboriginal and Torres Strait Islander and non-Indigenous populations contribute to the gap in employment outcomes is to remove the effect of these differences. That is, to look at factors which influence outcomes, such as health or education, to see whether there would still be different outcomes if these factors were exactly the same for both populations.

The effect of contributing factors can be removed by standardisation, that is, weighting each factor or group of factors for the Aboriginal and Torres Strait Islander population to give it the same structure as the non-Indigenous population. For example, after adjusting in this way for the effects of age, both populations would have the same proportion of people in each age group, so any differences between the two populations for a characteristic would not be due to age differences.

This article uses the technique of standardisation to show the effect on labour force participation and unemployment levels if the key contributing factors of age, education, remoteness or health were the same for Aboriginal and Torres Strait Islander people as they were for non-Indigenous people. The technique is then extended to see what effect it would have if grouped factors were the same for both populations (that is, if the Aboriginal and Torres Strait Islander population had the same age structure and education outcomes and geographic dispersion as the non-Indigenous population). This is achieved through multiple standardisation. As well as showing the combined effect of these factors on the participation and unemployment gaps, the multiple standardisations also indicate whether the factors affect each other. Because there is interaction between the factors, (for example, Aboriginal and Torres Strait Islander people in major cities were more likely than those living in regional or remote areas to have completed Year 12 or have attained a non-school qualification⁴), the differences each contribute singly will not add up to the combined difference.

To be able to include health in the analysis, standardisations for participation rates use data from the 2011-12 Australian Health Survey (AHS) and the 2012-13 Australian Aboriginal and Torres Strait Islander Health Survey (AATSIHS). However, as unemployed people are a small subset of those participating in the labour force, it was not possible to use the health survey data for multiple standardisations, so except for the single health standardisation, analysis of unemployment rates uses 2011 Census data.

Also, as labour force participation does not consistently increase or decrease as people get older, analysis for age is only included when examining unemployment (which consistently decreases with age).
STANDARDISING FOR LABOUR FORCE PARTICIPATION

Using 2012-13 health survey data, the gap in labour force participation rates between the Aboriginal and Torres Strait islander and non-Indigenous populations was 19.9 percentage points, similar to the 2011 Census figure of 20.5 percentage points.

In general, Aboriginal and Torres Strait Islander people living in remote or very remote areas had lower labour force participation rates than those in regional or urban areas. The opposite was true for non-Indigenous people, who may have moved to a remote area specifically for work purposes (such as mining jobs). After adjusting for remoteness, (that is, creating a scenario where geographic dispersion was proportionally the same for Aboriginal and Torres Strait Islander and non-Indigenous people), the gap in participation rates decreased by 2.6 percentage points.

With a higher proportion of Aboriginal and Torres Strait Islander people reporting fair or poor health than non-Indigenous people, the effect of poor health on participation rates may be greater for this population. After adjusting for self-assessed health (that is, creating a scenario where the same proportion of people in each of the two populations felt they had good, very good or excellent health, or fair or poor health), the gap in labour force participation rates for the two populations decreased by 2.3 percentage points.

Recent research from the Australian Institute of Health and Welfare found that the difference in educational attainment between Aboriginal and Torres Strait Islander and non-Indigenous people was a critical factor in the difference in employment rates.⁵ This finding is supported by the ABS analysis, as adjusting for education had the largest effect on the gap in labour force participation rates between the two populations. With the same proportion of people in each education category as non-Indigenous people, Aboriginal and Torres Strait Islander people were still less likely to be in the labour force (69.9% compared with 80%), but the gap decreased by half (to 10 percentage points).

Once a certain level of education has been reached, however, differences in participation rates between the two populations become negligible. In 2011, the gap between Aboriginal and Torres Strait Islander and non-Indigenous people with only Year 12 qualifications was 8.1 percentage points, however for those with a bachelor degree or higher qualification, it dropped to 0.4 of a percentage point.

Combined effects

After adjusting for a combination of remoteness and education, the gap in labour force participation rates fell from 19.9 to 9.0 percentage points (with the rate now 71% for Aboriginal and Torres Strait Islander people compared with 80% for non-Indigenous people). Including self-assessed health in the standardisation decreased the gap by a further 2.7 percentage points.

A scenario where education levels, geographic dispersion and self-assessed health status were the same for Aboriginal and Torres Strait Islander people as they were for non-Indigenous people would result in the gap in labour force participation rates dropping by two-thirds, from 19.9 to 6.3 percentage points.


STANDARDISING FOR UNEMPLOYMENT

According to the 2011 Census of Population and Housing, the gap in unemployment rates between Aboriginal and Torres Strait Islander and non-Indigenous people was 11.7 percentage points. After adjusting for age, this gap decreased by 1.9 percentage points, however Aboriginal and Torres Strait Islander people were still almost three times as likely as non-Indigenous people to be unemployed (15.3% compared with 5.5%).

Across all Remoteness Areas, Aboriginal and Torres Strait Islander people were more likely than non-Indigenous people to be unemployed, however the difference in unemployment rates was smallest in major cities and largest in very remote areas. After adjusting for remoteness, the gap for unemployment overall decreased by 1.4 percentage points.

As with participation rates, standardising education level data for the Aboriginal and Torres Strait Islander population had the greatest effect on unemployment rates. After adjusting for education levels, the gap decreased by 4.3 percentage points (now 13.0% compared with 5.5%).

Combined effects

After adjusting for the combined effect of age, education levels and remoteness, the gap between unemployment rates decreased by more than half - down 6.4 percentage points. Even with these things held equal, Aboriginal and Torres Strait islander people were still twice as likely as non-Indigenous people to be unemployed (10.8% compared with 5.5%).
Health and unemployment

In 2012-13, people with fair or poor health were more likely to be unemployed than people with good or better health, and Aboriginal and Torres Strait Islander people with fair or poor health were the most likely to be unemployed (28.9% compared with 6.7% of non-Indigenous people with fair or poor health). Although it was not possible to include health data in the multiple standardisation, it was possible to standardise for it singly. After adjusting for the effect of health, the gap in unemployment rates between Aboriginal and Torres Strait Islander and non-Indigenous people decreased by 0.8 of a percentage point.
OTHER FACTORS

The factors discussed above only account for some of the differences which exist between the two populations. Other factors such as having a criminal record or discrimination may have an effect on labour market outcomes. For example, people with a criminal record may face significant barriers when trying to find a job. In 2013, after adjusting for age, Aboriginal and Torres Strait Islander people were 15 times more likely to be imprisoned (1,959 prisoners per 100,000 people) than non-Indigenous people (131 per 100,000 people).⁶

Experiencing discrimination may also discourage participation in the labour force. In 2008, around one in four Aboriginal and Torres Strait Islander people (27.3%) reported they had experienced discrimination in the last 12 months,⁴ and in 2012-13, 16.2% reported they had been treated badly in the last 12 months. Almost a third of these people (28.9%) said they were treated unfairly when applying for work or at work.
LOOKING AHEAD

When looking at influences on the labour market outcomes of Aboriginal and Torres Strait Islander people, this article explores the effect of some factors that cannot easily change, such as age, and some that can, such as education. Of those things that can change, the analysis shows that education (or the lack of it) makes the greatest contribution to the gap in labour market outcomes between Aboriginal and Torres Strait Islander and non-Indigenous people. The analysis also shows that health and remoteness have an effect, albeit a lesser one, on labour market outcomes. This understanding can help provide direction for future policy decisions.
ENDNOTES

1. Council of Australian Governments, Closing the Gap in Indigenous Disadvantage, <https://www.coag.gov.au/closing_the_gap_in_indigenous_disadvantage>, Last accessed 22/08/2014
2. Australian Bureau of Statistics, 2014, Labour Force, Australia, Detailed - Electronic Delivery, Feb 2014, cat. no. 6291.0.55.001
3. Australian Bureau of Statistics, 2008, Labour force participation across Australia, cat. no. 4102.0
4. Australian Bureau of Statistics, 2011, The Health and Welfare of Australia's Aboriginal and Torres Strait Islander Peoples, Oct 2010, cat. no. 4704.0
5. Australian Institute of Health and Welfare, 2014, Improving labour market outcomes through education and training, February 2014, Issues paper no. 9, <http://www.aihw.gov.au/closingthegap/publications/>, Last accessed 22/08/2014
6. Australian Bureau of Statistics, 2013, Prisoners in Australia, 2013, cat. no. 4517.0

DATA SOURCES AND DEFINITIONS This article uses data for people aged 15-64 years from the 2011-12 Australian Health Survey (AHS), the 2012-13 Australian Aboriginal and Torres Strait Islander Health Survey (AATSIHS) and the 2011 Census. For Census data, people whose labour force status and/or Indigenous status were not stated were excluded from analysis. Aboriginal and Torres Strait Islander peoples are Australia's first peoples. The Commonwealth defines an Aboriginal or Torres Strait Islander person as person of Aboriginal or Torres Strait Islander descent who identifies as an Aboriginal and Torres Strait Islander and is accepted as such by the community in which he or she lives. In statistical collections and most administrative collections, it is not feasible to collect information on the community acceptance component of the nominal definition. The operational definition of Indigenous status is 'Indigenous status indicates whether or not a person identifies as being of Aboriginal or Torres Strait Islander origin'. Participating in the labour force Either working or looking for work. Labour force participation rate The number of people in the labour force (either employed or unemployed), expressed as a percentage of the total population. Unemployed A person is unemployed if they were not employed during the week prior to Census or survey date, and: had actively looked for full-time or part-time work at any time in the four weeks up to the end of the week prior to Census or survey date; and were available for work in the week prior to Census or survey date. Unemployment rate The number of unemployed people expressed as a percentage of the number of people in the labour force. Remoteness Area Remoteness is determined by measuring the road distance to different classes of service centres. Different geographic areas which share common characteristics of remoteness are then grouped together into six categories of remoteness areas: Major Cities, Inner Regional, Outer Regional, Remote, Very Remote and Migratory. Details about Remoteness Areas are provided in the ABS Australian Statistical Geography Standard (ASGS): Volume 5 - Remoteness Structure, July 2011 (cat. no. 1270.0.55.055). Year 12 or higher educational attainment in this article refers to whether a person has attained a Year 12 Certificate or equivalent or Australian Qualifications Framework (AQF) Certificate III or above. Year 11 and below includes people with no educational attainment. Disability In the Survey of Disability, Ageing and Carers (SDAC), disability is defined as 'any limitation, restriction or impairment which restricts everyday activities and has lasted or is likely to last for at least six months'. In the Census, disability was designed to be conceptually comparable to the SDAC concept of 'profound or severe core activity limitation', the population for whom service delivery has the most consequence. Details about disability in the SDAC and Census are provided in the Information Paper ABS Sources of Disability Information, 2003-2008 (cat. no. 4431.0.55.002). 'if all factors were the same'. Factors such as age, education, remoteness and health do not work in isolation to each other, as they impact upon each other. This article presents multiple and single standardisation 'what if' scenarios in order to see where the biggest impacts are. The key contributing factors to labour market outcomes of age structure, education level, remoteness and self-assessed health were standardised for the Aboriginal and Torres Strait Islander population to the non-Indigenous population. To see what effect it would have on labour market outcomes if all factors were the same for both populations, multiple standardisations were performed (effectively giving the Aboriginal and Torres Strait Islander population the same age structure, education outcomes, geographical dispersion or health status as the non-Indigenous population). The multiple standardisations show that factors affect each other. As there is interaction between them, the difference each factor contributes singly will not add up to the combined difference. To be able to include health in the analysis, standardisations for labour force participation rates use data from the 2011-12 Australian Health Survey (AHS) and the 2012-13 Australian Aboriginal and Torres Strait Islander Health Survey (AATSIHS). While participation and unemployment rates differ slightly between the Census and these surveys, the percentage point differences between the Aboriginal and Torres Strait Islander and non-Indigenous populations were similar for all factors. While there are differences in labour market outcomes in both populations for gender, (for example, men are more likely to be in the labour force than women), it is not possible to standardise for these differences as the gender distributions for each population are very similar and standardisation would have negligible effect. Other factors that are known to have an impact on labour force status, such as whether or not a person has children, affect Aboriginal and Torres Strait Islanders and non-Indigenous people in a similar way and are not discussed in this article. Standardisation Standardisation removes the effect of a factor, such as age, to allow comparisons between two or more populations which have different distributions for that factor (effectively making the two populations have the same distribution of that factor). Any remaining differences between the two populations will not be due to the differences in that factor (that is, if age structures are the same, any remaining difference will not be due to age). In this article, the 2011-12 Australian Health Survey non-Indigenous population aged 15-64 years was used as the standard population when analysing labour force participation rates, and the 2011 Census non-Indigenous population aged 15-64 years was used as the standard population when analysing unemployment rates. Back to top