Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education

National Centre for Social and Economic Modelling University of Canberra Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education Binod Nepal Laurie Brown Paper presented at Australian Population Association 14th Biennial Conference, 30 June - 3 July 2008

About NATSEM The National Centre for Social and Economic Modelling was established on 1 January 1993, and supports its activities through research grants, commissioned research and longer term contracts for model maintenance and development with the federal departments of Family and Community Services, Employment and Workplace Relations, Treasury, and Education, Science and Training. NATSEM aims to be a key contributor to social and economic policy debate and analysis by developing models of the highest quality, undertaking independent and impartial research, and supplying valued consultancy services. Policy changes often have to be made without sufficient information about either the current environment or the consequences of change. NATSEM specialises in analysing data and producing models so that decision makers have the best possible quantitative information on which to base their decisions. NATSEM has an international reputation as a centre of excellence for analysing microdata and constructing microsimulation models. Such data and models commence with the records of real (but unidentifiable) Australians. Analysis typically begins by looking at either the characteristics or the impact of a policy change on an individual household, building up to the bigger picture by looking at many individual cases through the use of large datasets. It must be emphasised that NATSEM does not have views on policy. All opinions are the authors own and are not necessarily shared by NATSEM. Director: Ann Harding NATSEM, University of Canberra 2008 National Centre for Social and Economic Modelling University of Canberra ACT 2601 Australia 170 Haydon Drive Bruce ACT 2617 Phone + 61 2 6201 2780 Fax + 61 2 6201 2751 Email natsem@natsem.canberra.edu.au Website www.natsem.canberra.edu.au

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education iii Abstract This study compares lifetime employment and labour income outcomes for Indigenous Australians against all people in Australia. The method involves lifetable analysis in which employment rates are combined with life-table indicators. This allows factoring mortality differentials between Indigenous and other populations. Age-specific employment rates and average annual income were derived from the 2006 Census separately for those with certificate or higher education, Year 12 and less than Year 12 education. Life tables for Indigenous and total Australians were taken from the Australian Bureau of Statistics. Males with certificate or higher education are likely to spend the longest years in work and earn the highest amount over a lifetime. They are likely to earn almost 10 times the Indigenous females with below 12 years of education who fall at the bottom in terms of work and earning, if the current pattern of employment and earning prevails. Author note Binod Nepal is a Research Fellow and Laurie Brown is a Professor and Research Director Health at National Centre for Social and Economic Modelling (NATSEM), University of Canberra. Acknowledgments This study was supported through NATSEM s internal research grant. Employment and income data used in this study were derived from the specially requested 2006 Census tables and the 2005-06 Survey of Income and Housing confidential unit record files, both from the Australian Bureau of Statistics (ABS). The results based on further calculations of this data and the views expressed in this paper are those of the author, and not necessarily those of ABS and NATSEM. Thanks are due to Mandy Yap who contributed to the development of the modelling approach taken in this study. An earlier version of this paper was presented at the 14th Biennial Conference of the Australian Population Association, 30 June 3 July 2008, Alice Springs.

iv Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education General caveat NATSEM research findings are generally based on estimated characteristics of the population. Such estimates are usually derived from the application of microsimulation modelling techniques to microdata based on sample surveys. These estimates may be different from the actual characteristics of the population because of sampling and nonsampling errors in the microdata and because of the assumptions underlying the modelling techniques. The microdata do not contain any information that enables identification of the individuals or families to which they refer.

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 1 Contents Abstract Author note Acknowledgments General caveat iii iii iii iv 1 Introduction 2 2 Methods and materials 2 2.1 General life tables and life expectancy 3 2.2 Educational qualification 4 2.3 Proportion employed and expected lifetime employment 5 2.4 Average annual income and lifetime labour income 7 3 Results 9 4 Discussion 14 References 16 List of Figures Figure 1 Most recent estimates of life expectancy of indigenous and all Australians 3 Figure 2 Percentage distribution of Indigenous and all males and females by highest level of educational qualification 5 Figure 3 Percentage employed out of total population by highest level of education, Australia, 2006 6 Figure 4 Average annual income from full-time equivalent employment 8 Figure 5 Average expected years of full time work over the working life 10 Figure 6 Expected labour income over the working life 11 Figure 7 Lifetime labour income at age 25 and 35 for various groups as compared to all male with certificate or higher education 12 Figure 8 Expected labour income over the working life, without applying a discount rate 13 Figure 9 Lifetime labour income at age 25 and 35 for various groups as compared to all male with certificate or higher education, without applying a discount rate 13

2 Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 1 Introduction Aboriginal and Torres Strait Islanders are perhaps the most disadvantaged group in Australian society. The extent of disadvantage experienced by the Indigenous population is reflected in the statistics on a wide range of social and economic indicators. Most widely cited by academics as well as policy makers is the life expectancy gap of 17 years between Indigenous and other Australians. Life expectancy at birth was estimated to be 59.4 years for Indigenous males and 64.8 years for indigenous females for the period 1996-2001, compared with 76.6 years for all males and 82.0 years for all females for the period 1998 2000 (ABS and AIHW 2005). Mortality rate for Indigenous infants over the period 2000-2004 was 12.2 per 1,000 live births, almost three times the rate for non-indigenous infants (AIHW 2007). Indigenous populations are also lagging behind the non-indigenous populations in socio-economic areas such as education, employment, and income. Recent analysis by the Steering Committee for the Review of Government Service Provision (SCRGSP 2007) showed that in 2004-05, a smaller proportion (22%) of Indigenous people than non-indigenous people (47%) had completed year 12; and non- Indigenous people were more than twice as likely as Indigenous people to have completed a post secondary qualification of certificate level 3 or above. It also found that labour force participation rate for Indigenous people (59%) was just about three quarters of that for non-indigenous people (78%). Median gross equivalised income of Indigenous households was also found to be much lower ($340) than that of non-indigenous households ($618) in 2004-05. This evidence establishes that Indigenous people are far behind other Australians in many dimensions of socio-economic wellbeing. Yet little is known about how these gaps influence lifetime socio-economic outcomes. This study compares lifetime outcomes in employment and labour income by broad educational categories between indigenous people and all people in Australia. The purpose here is not to derive free-standing precise estimates for any of the population subgroups considered but to compare the outcomes among them. The remainder of the paper is structured as follows. Section 2 describes the data sources and the life-table modelling approach taken in this study. A brief overview of the input data is also included in this section. Section 3 presents the results from the modelling exercise. Finally, Section 4 discuses the main findings and limitations. 2 Methods and materials This section describes the approaches taken to compute indicators related to survival, work and earnings over the life time. These indicators are: life expectancy (average years of survival); average expected years of employment; and average

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 3 income over the work-life. These indicators were estimated using an Excel spreadsheet developed by the authors. Along with the description of the method, this section provides a brief overview of the input data used in this modelling. 2.1 General life tables and life expectancy Separate sets of period life tables were used for Indigenous and all Australian males and females. The life tables describe the mortality schedule of these populations and calculate average life expectancy at various ages. For the purpose of this study, abridged life tables were reconstructed by aggregating up values from complete (single-age) life tables constructed by the Australian Bureau of Statistics (ABS 2006; 2007a). The ages were grouped into five-year groups expect at the beginning (0 and 1-4 years) and at the end (85+). The life table columns used for further analysis were number of survivors at the beginning of each age group (generally denoted as l x) and number of surviving persons in the age interval (generally denoted as nl x). Average expected year of employment were subsequently constructed on the basis of these life table indicators and age-specific employment rates. This analysis focused on employment and labour income outcomes of working age population between 15 and 64 years of age. Life expectancies of the populations considered in this analysis are presented in Figure 1. It shows that the Indigenous people have lower life expectancy than all Australians at all ages considered. Females are expected to live longer than males do, among Indigenous as well as other populations. Indigenous males have the lowest life expectancy across all ages considered. Figure 1 Most recent estimates of life expectancy of indigenous and all Australians Life expectancy (years) 80 60 40 20 All Male All Female Indigenous Male Indigenous Female 0 15 20 25 30 35 40 45 50 55 60 Age (years) Source: Data from ABS life tables (ABS 2006; 2007a). Reference period is 1996-2001 for Indigenous Australians and 2004-06 for all Australians.

4 Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education There are some limitations regarding comparability of the life tables of Indigenous and other Australians. These life tables refer to different time periods. In case of the entire Australian population, life tables are available for the period 2004 2006 (ABS 2007a). They are based on a sufficiently large and accurately reported database. But for Indigenous Australians, life tables are only available for the period 1996 2001 at the latest (ABS 2006). They are also designated as experimental suggesting that mortality estimates for Indigenous populations need to be interpreted with caution. In the absence of up-to-date life tables for Indigenous population, it is assumed that mortality pattern estimated for the period 1996-2001 remain applicable for 2006. 2.2 Educational qualification Lifetime economic outcomes to be calculated in this study are disaggregated into broad educational groups. The distributions of population by educational categories considered in this study are shown in Figure 2. The Figure shows that the share of people with a certificate or higher educational qualification is the highest among all males. More than half of these people have achieved a certificate or higher education, except those below 25 years of age. Many of these younger people are likely to be studying. Proportion of all women who have a certificate or higher education is comparable with that of males 25-29 and 30-34 years of age but drops steadily at later ages. This suggests that women s participation in higher education has increased in the recent past. Indigenous males and females are far behind their non-indigenous counterparts in terms of attaining a certificate or higher educational qualification. A large proportion of them only have low (less than 12 years) or no education. Educational qualification could not be determined for about one-tenth to one-fifth of the population. This category has been omitted from the modelling.

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 5 Figure 2 Percentage distribution of Indigenous and all males and females by highest level of educational qualification 100% 80% 60% Certif icate or above Year 12 40% Below Year 12 Not know n 20% 0% 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Male Female Age (years) Male Female All Australians Indigenous Source: Authors calculation from 2006 Census tables obtained on special request from ABS. 2.3 Proportion employed and expected lifetime employment Average expected years of employment were calculated by using data on the stationary population from the general life-tables and age-specific employment rates. The employment rates were calculated from the full enumeration tables from the 2006 Census of Population and Housing. These were calculated for the 5-year age group from 15-19 to 60-64 years. Figure 3 presents age-specific employment rates used as the input data in the life table modelling. These rates vary by education, gender, and Indigenous status. Age-specific employment pattern among males exhibits a curvature shape, with a plateau between late 20s to late 40s. But, among women, this is bimodal, with peaks at late 20s and late 40s and a trough at late 30s. The bimodal shape among women reflects the drop-out from, and returns to, work influenced by their reproductive roles. Employment rates are lower for Indigenous males and females compared to that for average Australians.

6 Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education Figure 3 Percentage employed out of total population by highest level of education, Australia, 2006 100% Certificate or above Year 12 Below Year 12 Proportion employed fulltime 80% 60% 40% 20% 0% 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Age (years) Male Female Male Female All Indigenous Source: Authors calculation from 2006 Census tables obtained on special request from ABS. Most of the results in the next section are presented for ages 25 years and over. This was aimed to take account of the fact that many people below this age are still studying or are likely to obtain qualification at certificate or higher level. Employment rates refer to full-time equivalent employment. Two part-time workers were assumed to be equivalent to one full-time worker. Those reported as employed but away from work were proportionately distributed to full-time and part-time categories. Employment rate, nw x = 100 x (Full time + 0.5 x Part Time) / Total population nw x: employment rates in the age group x to x+n. nl wx: number of persons in age x to x+n who are employed. This is obtained by multiplying stationary population from general life table by employment rates. nl wx = nl x nw x. T wx: number of persons employed at age x and after. This is obtained by cumulative addition of nl wx values starting from the age group 60 64. e wx: average number of years employed. e wx = T wx / l x.

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 7 It was assumed that mortality rates were the same for people in any labour force status. It was a strong but necessary assumption in view of the absence of age-specific mortality rates by labour force status of Indigenous and other populations, and also in view of computational complexity. Unlike some work-life tables which are based on the hypothetical proportions of labour force participation rates, the work-life tables in this study are computed by using actual proportions of employed and unemployed populations out of the total population. If longitudinal data providing annual changes in employment status by educational qualifications were available for the populations groups being examined, more refined estimates of work years could be calculated by using increment-decrement methods. The purpose here is not to derive accurate absolute value but to obtain a comparative insight on life time gaps in economic outcomes arising from the gap in survival and education between Indigenous and other Australians. This was due to limitations in data, particularly the income data. 2.4 Average annual income and lifetime labour income Expected income streams were derived by using cross-sectional information on labour income and employment rates disaggregated by level of education. As the Census tables only provide income ranges, average dollar amount within each range was imputed by using data form the 2005-06 Survey of Income and Housing (SIH)(ABS 2007b). Since SIH only gives data for all Australians, indigenous income was imputed by applying the ratio ($669/$800) of median incomes of indigenous to all Australians working full time as reported in the 2006 wave of the Household, Income and labour Dynamics in Australia (HILDA) Survey (Melbourne Institute 2008). The reason for using SIH rather than HILDA for deriving age-specific average income is that the later could not provide enough samples to generate tables disgregated by the variables of interest. 1 The base year for the modelling is taken to be 2006 for which the employment and income data are available from Census. Average annual income used as input data in this modelling are show in Figure 4. As this Figure shows, all males with certificate or higher qualification are the highest earners and the Indigenous females with less then Year 12 education are the lowest earners. An unexplained drop was observed in the income of all females with Year 12 education. 1 HILDA is perhaps the most up-to-date data that identifies Indigenous status of the respondents. Another source of income data for Indigenous people could be the 2002 National Aboriginal and Torres Strait Islander Survey conducted by ABS. We did not look at how different the results would be based on the income data from these two surveys.

8 Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education Figure 4 Average annual income from full-time equivalent employment 80,000 All Male Cert 70,000 60,000 All Male Y12 All Male <Y12 All Female Cert Annual income ($) 50,000 40,000 30,000 20,000 10,000 ` All Female Y12 All Female <Y12 Indigenous Male Cert Indigenous Male Y12 Indigenous Male <Y12 Indigenous Female Cert Indigenous Female Y12 - Indigenous Female <Y12 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Age (years) Source: Derived from 2006 Census tables obtained on special request from ABS, Survey of Income and Housing 2006, and Household Income and Labour Dynamics in Australia Survey, Wave 6. The results (Section 3) should be interpreted as what happens to lifetime labour income if the current schedules of mortality, employment, and income prevail over the life of an individual aged 25 years in 2006. Rate of wage growth is assumed to be 1.04%. This figure was derived from the index numbers of average weekly earning of adults working full time (ABS 2008). Net present value of current lifetime labour income Monetary flows over time and future benefits are generally discounted and the results presented as net present value (NPV). NPV of a cash stream over a given period of time is the sum of the discounted values in each year of the period. Discounting essentially gives more weight to costs and benefits that occur in the near future and less weight to those that occur more distant in time. For example, as Trendle (2007) points out before valuing a decision of whether or not to undertake additional education, people will tend to discount future earnings, i.e. an additional $100 in a years time is not valued as much as an additional $100 now. If a person values a dollar next year at 90 cents now, their discount rate is 10%. For this reason, the value of the additional wages accruing from additional education must be discounted. Discounting is higher the further into the future the person s earnings accrue. The higher the discount rate, the lower the values of future incomes. The choice of an appropriate discount rate is open to debate conventional practice in many health economic studies has been to use a discount rate of either 3 or 5%

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 9 (Drummond et al. 2005). In lifetime labour income studies, a discount rate for future earnings of 5% is common. Hence, a figure of 5% is used in this study. The net present value of lifetime labour income was calculated as follows: where I ewx = [ ni x * nl wx + ( ni x+n * nl wx+n) (1+r) n / (1+d) n ]/l x I ewx = life time labour income estimated at age x, ni x = Average annual income of working people in the age group x to x+n, ni x+n = Average annual income in the next age group, nl wx = Life table working population in the age group x to x+n, r = rate of wage growth, d = discount rate, l x = number of persons survived to exact age x 3 Results This section presents the results from the life-table modelling of employment and labour income outcomes disaggregated by broad levels of educational qualifications. Figure 5 presents estimated average duration of employment over the working life at various ages. At age 25 years, Australian males with certificate or higher level of educational qualification are likely to spend the longest duration in gainful work, over 30 years. At the bottom are the Indigenous females with less than 12 years of education who are likely to be employed for less than 10 years on average.

10Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education Figure 5 Average expected years of full time work over the working life 35 All Male Cert All Male <Y12 All Male Y12 All Female Cert Expected years of employment 30 25 20 15 10 5 All Female Y12 All Female <Y12 Indigenous Male Cert Indigenous Male Y12 Indigenous Male <Y12 Indigenous Female Cert Indigenous Female Y12 Indigenous Female <Y12 0 25 30 35 40 45 50 55 60 Age (years) Notes: cert = certificate or higher education, y12 = Year 12, <y12 = less than Year 12 education Source: Authors calculation. Figure 6 presents estimated life time earnings from full-time equivalent employment. These estimates are derived by applying the annual income growth rate of 1.04 per cent and discount rate of five per cent (as mentioned in methodology section above). Income was imputed by using the median income from 2005-06 SIH data to the equivalent income ranges in Census tables. As the Figure 6 shows, like employment, males who have a certificate or higher educational qualification are expected to earn the highest amount throughout the working life, followed by males with 12 years of education. Indigenous females with less than 12 years of education are expected to have the lowest lifetime earning prospect.

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 11 Figure 6 Expected labour income over the working life All Male Cert All Male Y12 $1,400 All Male <Y12 All Female Cert All Female Y12 All Female <Y12 $1,200 Indigenous Male Cert Indigenous Male <Y12 Indigenous Male Y12 Indigenous Female Cert Life time labour income (Thousands $) $1,000 $800 $600 $400 Indigenous Female Y12 Indigenous Female <Y12 $200 $0 25 30 35 40 45 50 55 60 Age (years) Notes: cert = certificate or higher education, y12 = Year 12, <y12 = less than Year 12 education. Assumptions: annual 1.04% income growth and 5% discount rate. Source: Authors calculation Figure 7 compares average lifetime earnings of various groups against all males with certificate or higher education at ages 25 and 35 years. Age 35 years coincides with the trough in the employment cycle among women. At age 25, Indigenous females with less than Year 12 education and no further training are expected to earn just around one-tenth of what all males with certificate or higher education earn. Indigenous males with a certificate or higher education are better off than other Indigenous subgroups considered here but their lifetime earning is likely to be only about half of their non-indigenous counterparts. The gaps remain broadly the same at age 35 years, expect for all female with certificate or higher education. The economic prospect of these women would appear to be slightly better off at age 35 years than at age 25 years. This is due to an upward jump in employment and earning in their late 40s followed by a dip in their 30s.

12Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education Figure 7 Lifetime labour income at age 25 and 35 for various groups as compared to all male with certificate or higher education Lifetime labour income index 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 All Male Cert All Male Y12 All Female Cert All Male <Y12 Indigenous Male Cert Indigenous Male Y12 All Female Y12 ` Indigenous Female Cert All Female <Y12 Indigenous Female Y12 Indigenous Male <Y12 Indigenous Female <Y12 At age 25 At age 35 Notes: cert = certificate or higher education, y12 = Year 12, <y12 = less than Year 12 education. Assumptions: 1.04 per cent annual income growth and five per cent discount rate. Expected lifetime labour incomes for all the groups are indexed to those of all male with certificate or higher education. Source: Authors calculation. Sensitivity analysis A sensitivity analysis was conducted to assess the variations arising from applying no discount rate in estimating expected lifetime labour income. The results are presented in Figure 8 and Figure 9. As shown in Figure 8, absolute values of the expected lifetime labour income estimates are much higher without a discount rate compared with five per cent discount rate, except the last age group (see Figure 6 for comparison). But, comparing Figure 9 and Figure 7, it becomes evident that the gaps in lifetime income among the population groups considered here remain almost the same. It can be noted that the order could be changed slightly as all female with certificate or higher education is expected move two positions upward. This is due to increased employment and income of this group of women at the later phase of the working life.

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 13 Figure 8 Expected labour income over the working life, without applying a discount rate Life time labour income (Thousands $) $3,000 $2,500 $2,000 $1,500 $1,000 All Male Cert All Male Y12 All Male <Y12 All Female Cert All Female Y12 All Female <Y12 Indigenous Male Cert Indigenous Male Y12 Indigenous Male <Y12 Indigenous Female Cert Indigenous Female Y12 Indigenous Female <Y12 $500 $0 25 30 35 40 45 50 55 60 Age (years) Notes: cert = certificate or higher education, y12 = Year 12, <y12 = less than Year 12 education. Assumptions: 1.04 per cent annual income growth and no discount rate. Expected lifetime labour incomes for all the groups are indexed to those of all male with certificate or higher education. Source: Authors calculation. Figure 9 Lifetime labour income at age 25 and 35 for various groups as compared to all male with certificate or higher education, without applying a discount rate Lifetime labour income index 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 All Male Cert All Male Y12 All Female Cert All Male <Y12 Indigenous Male Cert Indigenous Male Y12 All Female Y12 ` Indigenous Female Cert All Female <Y12 Indigenous Female Y12 Indigenous Male <Y12 Indigenous Female <Y12 At age 25 At age 35 Notes: cert = certificate or higher education, y12 = Year 12, <y12 = less than Year 12 education. Assumptions: 1.04 per cent annual income growth and no discount rate. Expected lifetime labour incomes for all the groups are indexed to those of all male with certificate or higher education. Source: Authors calculation.

14Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 4 Discussion This study provided an insight on lifetime economic disadvantages to Indigenous people as compared to average Australians. The purpose here is to look at the differences among the subgroups considered rather than to obtain an absolute dollar amount. The modelling suggests that lifetime labour income outcomes for a 25-year old Indigenous female with less than Year 12 education could be as low as one-tenth of that for an average 25-years-old Australian male with a certificate or higher education. These are the most and least advantaged subgroups considered in this modelling. In summary, in terms of lifetime economic prospects, males are better of than females, more educated are better off than less educated, and Indigenous are worse off than all Australians. These estimates are, however, synthetic. They suggest what may happen if the current age-specific patter of mortality, employment, and earning continues into the future. Unlike many studies that only offer cross-sectional perspective, this study offers lifetime perspective by bringing age-specific mortality, employment, and income patterns together. Taking mortality into account was important as it was substantially different between Indigenous and other people, and between males and females. A limitation, however, is that mortality rates are not adjusted by educational status. They are likely to be different for people in different educational categories, as is the case in the United States, for example (Meara et al. 2008). Future studies should attempt to adjust age-specific adult mortality by educational level. Another limitation of this analysis is due to the lack of life tables for Indigenous and other Australians for the same period of time. Life tables for Indigenous people refer to the period 1996-2001; for other all Australians, they refer to 2004-2006. The use of these life tables limits the comparability but was assumed to be acceptable as there was no evidence that mortality in any group fluctuated significantly between these periods. This analysis can be updated once more comparable life tables become available. The value of the study could have been enhanced if the analysis had distinguished non-indigenous people from all Australians. Yet the results for all people can be broadly ascribed to non-indigenous because almost 98 per cent of Australians are non-indigenous. The contribution of the study may also have been broadened by breaking down certificate or higher education category into two or more categories. This was considered at the planning stage but it was soon realised to be inappropriate as there was a small number of Indigenous people, especially, Indigenous females, who had this level of education.

Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education 15 Yet the findings of the study are expected to make a positive contribution to the current debate among academicians as well as policy makers regarding the socio-economic gap between Indigenous and other Australians. The importance of this issue cannot be understated, with overcoming Indigenous disadvantage now placed firmly at the centre of the Federal Government s reform agenda.

16Estimating lifetime socio-economic disadvantage in the Australian Indigenous population and returns to education References ABS (Australian Bureau of Statistics) and AIHW (Australian Institute of Health and Welfare) 2005, The Health and Welfare of Australia s Aboriginal and Torres Strait Islander Peoples 2005, ABS cat. no. 4704.0, Canberra, ABS and AIHW. ABS (Australian Bureau of Statistics) 2006, Deaths, Australia, 2005, ABS cat. no. 3302.0, Canberra, ABS. ABS (Australian Bureau of Statistics) 2007a, Life Tables, Australia, 2006 ABS cat no. 3302.0.55.001, Canberra, ABS. ABS (Australian Bureau of Statistics) 2007b, Survey of Income and Housing, User Guide, Australia, 2005-06, cat. no. 6553.0, Canberra, ABS. ABS (Australian Bureau of Statistics) 2008, Average Weekly Earnings, Australia, ABS cat no. 6302.0 Canberrra, ABS. AIHW (Australian Institute of Health and Welfare) 2007, Aboriginal and Torres Strait Islander Health Performance Framework, 2006 report: detailed analyses, AIHW cat. no. IHW 20, Canberra, AIHW. Drummond, M., Sculpher, M., Torrance, G., O'Brien, B. and Stoddart, G. 2005, Methods for the economic evaluation of health care programmes. Third edition, Oxford, Oxford University Press. Meara, E.R., Richards, S. and Cutler, D.M. 2008, The gap gets bigger: changes in mortality and life expectancy, by education, 1981-2000, Health Affairs, vol.27, no. 2, pp. 350-360. Melbourne Institute 2008, The Household, Income and Labour Dynamics in Australia (HILDA) Survey, http://www.melbourneinstitute.com/hilda/, Accessed 5 April 2008. SCRGSP (Steering Committee for the Review of Government Service Provision) 2007, Overcoming Indigenous Disadvantage: Key Indicators 2007, Canberra, Productivity Commission. Trendle, B. 2007, The labour market and apprenticeship retention in Queensland traditional trades, Labour Market Research Unit, Department of Education, Training and the Arts, Queensland