DISCUSSION PAPERThe determinants of Indigenous employment outcomes: the importance of education and training B. Hunter
No. 115/1996
ISSN 1036-1774
ISBN 0 7315 1789 XSERIES NOTE
The Centre for Aboriginal Economic Policy Research (CAEPR) was established in March 1990 under an agreement between The Australian
National University (ANU) and the Aboriginal and Torres Strait Islander
Commission (ATSIC). CAEPR operates as an independent research unit within the University's Faculty of Arts and is funded by ATSIC, the
Commonwealth Department of Social Security and the ANU. CAEPR's principal objectives are to undertake research to:
• investigate the stimulation of Aboriginal and Torres Strait Islander economic development and issues relating to Aboriginal and Torres
Strait Islander employment and unemployment;
• identify and analyse the factors affecting Aboriginal and Torres Strait
Islander participation in the labour force; and
• assist in the development of government strategies aimed at raising the level of Aboriginal and Torres Strait Islander participation in the labour market.
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Professor Jon Altman
Director, CAEPR
The Australian National University
October 1996ABSTRACT
The National Aboriginal and Torres Strait Islander Survey provided a unique opportunity to re-examine the underlying determinants of
Indigenous employment. The recent Centre for Aboriginal Economic
Policy Research/Australian Bureau Statistics publication Employment
Outcomes for Indigenous People emphasises the importance of education and training in securing better employment outcomes for Indigenous
Australians. Regression analysis is used to highlight the large potential gains to Indigenous employment that can accrue through improved access to education. This paper argues that labour force statistics which compare
Indigenous and non-Indigenous outcomes should be adjusted, using a simple technique, to account for the large differences in educational attainment in the respective population.
Acknowledgments
I am clearly indebted to all the people who participated in the preparation of Employment Outcomes for Indigenous People including: Tony Barnes,
Joan Cunningham, Kate Ross, John Taylor and Cathie Thorp. Special thanks to Roger Jones whose incessant badgering at several seminars provided the intellectual impetus for the second part of this paper. I would also like to thank Bruce Chapman, Ngaire Hosking, Will Sanders and John
Taylor for their comments on earlier drafts. Editorial assistance was provided by Krystyna Szokalski, Linda Roach and Hilary Bek.
Boyd Hunter is a Post-Doctoral Fellow at the Centre for Aboriginal
Economic Policy Research, Faculty of Arts, The Australian National
University, Canberra.Poor employment outcomes for Indigenous people have been one of the core concerns for government policy relating to Indigenous people for a very long time. While there was a marked improvement between the past two censuses, recent studies point to a reversal of this trend with negligible growth in Indigenous employment in the mainstream labour market between 1991 and 1994 (Taylor and Liu 1995; Australian Bureau of
Statistics (ABS) 1996).
The 1994 National Aboriginal and Torres Strait Islander Survey (NATSIS) provides a unique opportunity to re-examine the underlying determinants of Indigenous employment. The recent Centre for Aboriginal Economic
Policy Research (CAEPR)/ABS publication Employment Outcomes for
Indigenous People, emphasises the importance of education and training in securing better employment outcomes for Indigenous Australians (ABS
1996). NATSIS also permits the analysis, for the first time, of relationships between employment and several social factors, including recent arrest and health, as well as quantifying the effect of the major determinants of employment, including education, training, demography and geography
(ABS 1996).
This discussion paper provides a detailed review of the regression analysis in Employment Outcomes for Indigenous People (EOIP) to further debate on the Indigenous employment problem. While the technical results from
EOIP are reproduced in Appendix A, this paper presents a more detailed interpretation of the implications for policy makers. New material is presented which underscores the importance of education in determining employment outcomes.
The primacy of education as an underlying determinant of Indigenous employment status means that it should be accounted for in even the most elementary analysis of Indigenous employment or, indeed, labour force status in general. Given the large differences in educational attainment between Indigenous and other Australians this paper suggests that all comparisons of labour force status should account for the proportional differences in each educational category.
Data and methodology
The regression analysis in EOIP is merely a statistical description of the stylised relationships underlying Indigenous employment outcomes for
NATSIS respondents. Multivariate techniques such as regression analysis allow the quantification of the strength of the relationship between various factors and employment after controlling for all other relevant factors. For example, regression techniques allow researchers to determine the extent to which education affects the chances of employment after controlling for other relevant factors.Previous empirical research points to several major influences which, together, can largely explain Indigenous employment outcomes including education, demography, geography and other social factors (Daly 1995).
NATSIS data provides several variables which capture these influences.
The influence of education on employment was included in three major forms: highest level of schooling completed, the highest educational qualification received and whether a person has attended a training course.
Other studies have also found that poor English skills reduced the chances of being in employment (Jones 1991; Daly 1993, 1995). The ability to communicate in English was included as an additional measure of education because it is a fundamental job skill in the mainstream labour market. The major demographic influence on employment status is the age variable which captures not only the effects of labour market experience on employment, but also broader life cycle effects. Other demographic factors such as the number of children may also influence employment outcomes.
It is usually expected that having dependent children will increase the chances of females being outside the labour force and therefore having less opportunity to secure employment. However, the effect of dependent children on male employment is not so clear. Children may encourage a greater search effort to find employment or, by raising welfare entitlement, reduce the incentives to find employment. Nevertheless, in general, the presence of dependent children may increase the intensity of job search for persons, predominantly males, without child-rearing duties while reducing the intensity of job search for those with child-rearing responsibilities.
Geography is also an important determinant of employment outcomes for
Indigenous people. Two measures of geography were used in this analysis. The first is the part-of-State variable used by the ABS which divides
Australia into three categories according to settlement size and type: capital city, other urban, and rural. The second geographic variable measures whether the respondent lives in a household which is more than
100 kilometres away from a TAPE institution. This variable attempts to capture the extent to which opportunities for paid employment are limited in very remote areas.
The NATSIS also enables, for the first time, the examination of several social factors which may, directly or indirectly, influence the chance of employment. For example, was a history of arrest and poor health adversely related to the chances of employment? These factors are proxied by the experience of being arrested in the previous five years and whether individual respondents have a specified, long-term health condition.
The rise of the Community Development Employment Program (CDEP) scheme complicates the analysis of Indigenous employment because it canbe viewed as work and welfare (Sanders 1993). Given the uncertain status of CDEP scheme participation as a labour market state and that CDEP scheme employment forms a large component of total employment in many remote and rural areas, the regression models in EOIP were conducted separately for both total employment and non-CDEP scheme employment. The regression for non-CDEP scheme employment is estimated using a restricted sample which excludes CDEP scheme employees. This allowed the analysis to focus, specifically, on employment in die mainstream labour market.
Summarising major impacts on Indigenous employment
The simplest way of summarising the major factors underlying employment from the regression results is to examine what happens to the chance of employment as the characteristics of Indigenous people are varied (Table 1). The affect of the changes in characteristics are measured relative to a hypothetical reference person who:
• completed schooling to year 10 or 11
• did not possess a post-school qualification
• had not completed a training course did not have difficulty speaking English
• was between 25 and 44 years of age
• did not have children
• resided in a capital city lived within 100 kilometres of a TAPE institution
• had not been arrested in the last five years and
• did not have a long-term medical condition.
The remainder of this section examines the determinants of all Indigenous employment (see Table 1, columns 2 and 4). The next section focuses solely on the determinants of non-CDEP scheme employment.
The first line of Table 1 indicates that the reference male has a 61.1 per cent chance of being employed in any job. The reference female has a 47.4 per cent chance of being employed. These probabilities of being employed reflect the overall conditions faced by the reference person. The rest of
Table 1 addresses what happens to the chance of employment for this reference person as each of the major characteristics of this person varies.
The education variables are the largest single factor influencing Indigenous employment. Completing school to year 10 or year 11 increases the reference person's chance of being in employment relative to a person without any education by around 40 per cent. Completing year 12 further improves the chance of being in employment by 12.9 per cent for females, although the employment chances for males are not significantly affected.Table 1. The impact on employment of a change in selected characteristics, 1994."'"
Male Total Excluding employment CDEP
Female Total Excluding employment CDEP
Reference person's employment probability 61.1 60.8
Change in probability resulting from a change in selected variables
Education and training
No education -38.2 -43.9
Below year 6 -17.2 -16.6
Years 6 to 9 -8.4 -8.9
Year 12 * 9.8
Any other qualifications 13.0 15.1
Any vocational 18.1 21.3
Diploma/degree 17.6 18.2
English difficulty *
Training 9.4 11.7
Demographics
Age 15-24 years -8.8 -13.7
Age 45-64 years * *
One child 5.3 5.6
Two or three children
Four or more children -6.6 -9.9
Geography
Other urban area -7.0 -9.8
Rural area (