B. Hunter and J. C. Altman
The analysis of the geography of unemployment-related benefits and employment related to the Community Development Employment Projects (CDEP) scheme yields several insights into Indigenous labour market activity. By simultaneously examining both, it is possible to estimate the proportion of the Indigenous labour force which depends on some form of government assistance. The analysis also shows that the CDEP scheme alters geographic patterns of unemployment and long-term unemployment, and appears to partially redress the spatial mismatch of employment demand and Indigenous labour supply.
The disproportionate presence of Indigenous peoples in remote and rural Australia means that spatial analysis is required to understand Indigenous labour-market experience. Such analysis has added policy significance in Indigenous affairs with the political, administrative and program structures of the Aboriginal and Torres Strait Islander Commission (ATSIC) which intentionally reflect the concept of re- gionalism.[1] This article examines the inter-relationships between the location of Department of Social Security's (DSS's) Indigenous unemployment-related beneficiaries and the ATSIC administered Community Development Employment Projects (CDEP) scheme employment. The purpose is to assist understanding of the institutional and labour market processes which, partially at least, underpin In- digenous welfare. By combining regional data from the 1991 Census, DSS, ATSIC and the Australian Bureau of Statistics (ABS) it is also possible to shed light on how local employment demand affects In- digenous unemployment and welfare outcomes. The data also provide, for the first time, a preliminary insight into the Indigenous labour force's dependence on unemployment-related government assistance. For Australia as a whole, 38 per cent of the Indigenous labour force were either receiving unemployment related benefits or participating in CDEP-scheme employment (see Table 1).
[Table 1]
Clearly, the CDEP scheme has become an important element of Indigenous labour-market experience since it was established in 1977 as a response to the spread of unemployment benefits to remote Aboriginal communities. It offers participating communities an alternative to social security payments by making grants to community organisations to employ members in community development projects. Despite numerous links and references to unemployment-related benefits in its original and existing guidelines, the CDEP scheme is not tightly linked to DSS's benefit system and it should be considered both a welfare and workforce program.[2]
The geographic dimension of the CDEP scheme has potentially important implications for both the level and com- position of unemployment-related beneficiaries. Given that over 27,000 people currently participate in the scheme Australia-wide, it is quite probable that both the level and the composition of unemployment-related beneficiaries will be severely distorted in areas where the scheme provides a significant proportion of employment'. Clearly, the displacement of unemployment-related benefits by CDEP-scheme employment will also directly affect the geographic distribution of DSS's welfare expenditure.
DATA
The Centre for Population and Urban Research at Monash University generated a data file based on the postcode level of aggregation for all 24,121 Indigenous people identified as receiving unemployment-related benefits from DSS in August 1995. Table 2 provides a detailed description of the type of unemployment-related benefit being received by DSS's Indigenous clients. Only 1,422 clients, or 5.9 per cent of the Indigenous client base, were Torres Strait Islanders with the remainder recorded as Aboriginal.
The majority of DSS clients (91 per cent) in Table 2 either receive Job Search Allowance (JSA) or Newstart Allowance (NA). All the benefits listed in Table 2 refer to either unemployment-related benefits' or DSS welfare payments which are based on potential employment or labour market participation (hereafter all these payments are referred to as unem- ployment-related benefits). For example, sickness benefit recipients are included because they are temporarily displaced from the possibility of employment by sickness or illness. The potential for substitution between benefits mean that all unemployment-related benefits need to be analysed simultaneously.
Males predominated in the DSS file, with only 30.2 per cent of the people recorded in the DSS data being female. This is higher than the male proportion of Indigenous unemployed persons recorded by the National Aboriginal and Torres Strait Islander Survey (NATSIS) which was only 60 per cent. Since females in Indigenous society, as in non-Indigenous society, are more likely to be considered the secondary income earner in the family, the new parenting allowance introduced one month before the DSS data were collected may have imparted a gender bias in the DSS data, relative to NATSIS, towards males.
A large number of Indigenous clients had a limited experience in the labour force with over 30 per cent (or 7,300 clients) having had no previous employment. Of these, 38 per cent (or 2,784 clients) had not secured employment since leaving school. The majority of Indigenous clients had been wage and salary earners in previous employment (14,981 clients or 62.1 per cent). Only 0.5 per cent (or 104 clients) were self-employed before they became unemployed.
The high rate of long-term unemployment among Indigenous people is reflected in the fact that almost 40 per cent of DSS's Indigenous clients have been without employment for more than 12 months. This rate of long-term unemployment is well above the 31 per cent of all unemployed Australians who had been out of work for more than 12 months at August 1995. The average unemployment duration for these DSS Indigenous clients is roughly equivalent to those measured in other data sets.[3]
The other major data sources used are the 1991 Census and the NATSIS. The 1991 Census Collection District (CD) summary file was aggregated to the post- code, section-of-State and ATSIC region levels for this analysis. The only variables used from the 1991 Census were the overall level of employment and the size of the Indigenous populations in the respective areas. The NATSIS data provided recent data on the Indigenous population aged 15 years-and-over and CDEP-scheme employment across geographic units (part-of-State or ATSIC region). All data are adjusted to the 1995 equivalents using the estimated resident population growth published by the ABS at the State/Territory level of aggregation.[4]
Geographic scale
An important question is at what level the regional analysis should be conducted. The answer involves a trade-off between the level of detail and range of data required for useful policy evaluation, on the one hand, and issues such as the level of non-response to questions and the complexities involved in handling and analysing disaggregated data sets, on the other. While the DSS data are available at the postcode level, it is not possible to utilise this fine level of detail because of the problem of small numbers in each postcode.[5] ATSIC regional council areas provide a convenient intermediary framework for analysis which has the added advantage of providing data to match the ATSIC administrative structure. Therefore, in order to fully utilise the data from ATSIC and the ABS, the smallest possible aggregations are examined including section-of-State and ATSIC regional-council levels.
The examination of unemployment duration across the section-of-State classification used in the 1991 Census reveals relatively small differences in the patterns of Indigenous unemployment between urban and rural areas.[6] While the pattern of unemployment duration is consistent with a low level of employment demand in rural and remote areas, the differences across sections-of-State are not as large as might be expected. The most likely explanation for this lack of variation is that the CDEP scheme is disproportionately affecting the composition of the pool of Indigenous unemployed with many potentially long-term unemployed participating in the CDEP scheme. The NATSIS data confirm that there is little variation in unemployment duration across capital cities, other urban, and rural areas. Given that these higher levels of aggregation are not capturing some of the important variations in Indigenous unemployment, the remainder of this article focuses on ATSIC regions. (See Figure 1.)
(note: maps not reproduced in on-line version)
Data quality issues
In the DSS data set the Indigenous status of clients is self-designated. This means that care should be exercised in interpreting these data. However, the large number of Indigenous people receiving DSS benefits means selectivity should not represent a significant problem. As long as the identification rate is reasonably similar in all areas being analysed this geographic analysis should not be significantly biased.
Another concern with the DSS data is the extent to which the level of unemployment is understated. The DSS data set contains about 60 per cent of the 40,000 Indigenous people estimated to be unemployed by NATSIS in 1994. There are several reasons why DSS data show fewer unemployed persons than the NATSIS figures.
First, the DSS results may understate the actual number of unemployed because self-identification may only partially reveal the actual population of Indigenous unemployed. Second, the definitions adopted by NATSIS mean that its data tend to give a relatively high estimate of the number of unemployed relative to the Monthly Labour Force Survey (MLFS) conducted by the ABS. NATSIS respondents were classified as unemployed if they were registered with the Commonwealth Employment Service (CES) irrespective of whether they claimed to be looking for work.[7] This means that approximately 20 per cent of the people classified as unemployed by NATSIS would be reclassified as not in the labour force if the strict MLFS definitions applied.[8] This of itself will account for a large amount of the difference in number of unemployed.
Third, NATSIS and DSS data are measuring different things. This is because the spouses of unemployed may not receive unemployment-related benefits but may have been classified as unemployed for the purposes of NATSIS. For example, the new parenting allowance is paid to spouses of the unemployed with parental responsibility, even if the spouse is actively seeking employment at the local CES. Finally, the overall fall in the level of unemployment for all Australians between the times of data collection may tend to lower the measured level of unemployment for Indigenous Australians. Given that Indigenous people are over-represented in the ranks of the unemployed, the fall in the national level of unemployment by 1.5 per cent between June 1994 and August 1995 may partially explain why the measured level of unemployed from DSS data is less than that in NATSIS.[9]
On balance, the level of Indigenous unemployment reported to DSS will understate the actual unemployment/ population ratio. Notwithstanding these qualifications, the DSS data represent a large component of the Indigenous un- employed which should provide a useful insight into the regional variation of unemployment.
EDUCATIONAL, EMPLOYMENT AND WELFARE PATTERNS ACROSS ATSIC REGIONS
(note: maps not reproduced in on-line version)
The examination of data at the ATSIC regional-council level allows the pres- entation of a national picture of spatial patterns in key educational and labour market indicators. These patterns are presented in a series of maps starting with Figure 2 which shows the proportion of the Indigenous population aged 15 years and over with a post-school qualification by ATSIC region. In each case, the data have been organised around a uniform frequency distribution to create three categories of relative rates low, average and high ranges. That is, the 36 ATSIC regions are ordered and put into three groups of 12 regions. For example, in Figure 2, the 12 ATSIC regions with the lowest proportion of population with a post-school quali- fication are classified in the low range, and the two other sets of 12 ATSIC regions are classified in the middle and high ranges respectively.
The geographic distribution of post-school qualifications illustrated in Figure 2 shows that the least-qualified Indigenous people are found in remote regions in northern Australia. Indeed the level of qualifications in the group of regions without shading, which so predominate in the north of the continent, is about a third of the level apparent in the most qualified group of regions. Since educational level is an important determinant of employment outcomes, all else being equal, we would expect this pattern to be reflected in a concentration of unemployment in northern remote regions and stronger employment prospects in other regions. NATSIS allows the proportion of a population aged 15 years and over in CDEP-scheme employment to be estimated for each ATSIC region.
Figure 3 indicates that CDEP-scheme employment is a prominent influence on the Indigenous labour market in many remote and rural regions such as the Kimberleys, Western Desert, east Arnhem Land, central Aus- tralia, Cape York Peninsula, Murdi Paaki and Wangka-Wilurrara regions.[11] In these regions, as many as 60 per cent of the population aged 15 years and over were employed in CDEP schemes. Most of these areas with high level of CDEP-scheme participation have a limited access to mainstream labour market opportunities.
(note: maps not reproduced in on-line version)
Participation in the CDEP scheme is either very limited or non-existent in the south-eastern corner of the continent in- cluding Sydney, south-eastern New South Wales, western Victoria and Tasmania. Most of Australia's metropolitan areas have very low levels of participation in the CDEP scheme. This pattern is not surprising given the historical link of the CDEP scheme to remote rural areas.
In addition to CDEP-scheme employment, another important factor determining Indigenous unemployment is the overall level of employment demand in the local area. The level of non-CDEP-scheme employment held by either Indigenous or non-Indigenous residents in a region is a direct indication of the number jobs available in a region. If we accept that the labour market is constrained on the demand side, then the level of employment is a measure of labour demand in an area. Since the population size varies between ATSIC regions we have to standardise the level of employment in some way. For this article, employment demand is estimated by dividing the number employed by the total population aged 15 and over in a respective area. This is the probability, for the average resident, of being employed in mainstream employment and it is calculated by adjusting the 1991 Census employment/population ratios for the local level of employment in the CDEP scheme. The very fact that the employment/ population ratio in Figure 4 is calculated for the whole population means that it will not be sensitive to supply-side factors in the Indigenous population and therefore provides a reasonable proxy for local employment demand faced by Indigenous residents.
As hypothesised earlier, there ia a relatively high employment demand in the south-east corner of Australia. However, urbanised areas outside Sydney and Melbourne tend to have only average employment/population ratios. This points to a potential weakness of employ- ment/population ratio as a measure of demand because the high range is dominated by remote areas with substantial mining and associated activities, such as Mount Isa, Pilbara and Kalgoorlie. Since the majority of the non-Indigenous population in such remote communities live there because of employment opportunities, why aren't the Indigenous population securing employment in the same areas? The historical lack of Indigenous people in the mining and growth' industries such as tourism is clearly indicated in other research and may mean that there is no simple relationship between Indigenous employment opportunities and employment demand.[13]
In addition, the high employment demand in Mount Isa and other mining areas may not translate into effective employment opportunities for Indigenous people because mining operations fre- quently require highly-trained professionals and other skilled workers. The general absence of Indigenous workers in growth industries results in a mismatch of the skills of Indigenous workers and employment demand.[14] Indeed, in the extreme, occupational and industrial mismatch may mean that the Indigenous labour force constitutes a separate, secondary labour market in some areas.
(note: maps not reproduced in on-line version)
Figures 3 and 4 illustrate that there is a strong inverse association between employment demand and CDEP-scheme employment with high employment demand areas, such as urban and mining regions, having relatively low levels of participation in the scheme. The correlation coefficient between these two variables of minus 0.52 confirms this is the case.
Despite the consistently low levels of qualifications in remote northern Australia, there is substantial variation in the proportions of the Indigenous population who receive unemployment-related ben- efits in these regions (Figure 5). Outside the Northern Territory, many people in northern Australia, including Cape York Peninsula in Queensland and Kullarri, Derby, Wunan and the Western Desert in Western Australia, have low unemploy- ment/population ratios with between four and 11 per cent receiving unemployment-related benefits. Average unemployment-related benefit ratios of between 11 and 14 per cent were found in areas with low levels of education in many other areas of northern Australia, including Geraldton, Goolburri and Yapakurlangu. It is no coincidence that most of these remote areas have a high level of participation in the CDEP scheme. There appears to be a displacement of the Indigenous un- employed into CDEP-scheme employment in these areas. However, above average rates of employment in the CDEP scheme do not necessarily produce low unemployment/population ratios. For example, Alice Springs and the Papunya region of the Northern Territory and north-west New South Wales had an above average unemployment-related benefit ratio despite having above average employment in the CDEP scheme. Clearly, many CDEP workers in these areas are drawn from those previously outside the labour force. There is also little consistency between ATSIC regions in the high range of between 15 and 27 per cent. In particular, many people in southern Australia have relatively high benefit rates despite the expectations based on Figure 2. The north coast of New South Wales and the Perth area (Icarlarnyiny) also show relatively high unemployment/ population ratios compared to the proportion of the population with post-school qualification. Both of these areas have low levels of participation in the CDEP scheme. Therefore, while the CDEP scheme may largely explain the low levels of unemployment in remote areas, it only plays a small part in explaining the level of unemployment in metropolitan areas and areas in the south-east corner of the continent which have access to more developed mainstream labour markets. Despite the limits of the CDEP-scheme influence in many situations, it still needs to be accounted for in any regional analysis of Indigenous labour-market experience,[16] and in any analysis of the distribution of DSS unemployment-related benefits.
OVERALL IMPACT OF DSS AND CDEP ASSISTANCE TO THE INDIGENOUS WORK FORCE
The extent of government involvement in the Indigenous labour market can be captured by adding the proportion of the population aged 15 years and over in CDEP-scheme employment and the proportion on unemployment-related benefits and comparing these proportions to the share of the Indigenous population aged 15 years and over in the labour force. The resulting assistance rates for each ATSIC region are noted in Table 1. Overall, 38 per cent of the Indigenous work force were being assisted by such benefits. Government involvement is the dominant influence in remote areas with over 50 per cent of the labour force receiving some form of assistance from either ATSIC (via CDEP) or DSS in most of the Northern Territory, Cape York Peninsula, the Western Desert, the Kimberleys, north-west New South Wales and the Nullarbor. Indeed, these areas represent a third of all ATSIC regions. The Indigenous labour force in remote areas is probably more dependent on government assistance because of limited access to mainstream employment.
The CDEP scheme may be affecting the composition of unemployment as well as the level of unemployment in the various areas. It may be that the existence of substantial participation in the CDEP scheme in many remote areas absorbs those people who are most likely to be unemployed for prolonged periods. The pattern of long-term Indigenous unemployment in Figure 6 suggests that this is the case with many remote areas having low or average levels of long-term unemployment.
The CDEP scheme provides one ex- planation for this anomaly. Since the CDEP scheme gives employment to those people with a high chance of being long-term unemployed in remote Australia, then the availability of the scheme in an area may transform the overall pool of unemployed so that there are fewer Indigenous unemployed who have been out of work for prolonged periods. That is, the problem of accessing mainstream labour markets in many remote areas, for example Cape York Peninsula and the Kimberleys, is balanced out, for Indigenous residents at least, by enhanced accessibility to CDEP scheme jobs.
A striking aspect of Figure 6 is that almost all of south-eastern Australia shows relatively high long-term unemployment-population ratios, including the Sydney and Melbourne (Binjirru) areas. This is surprising given that most of these areas in the south-eastern corner of the continent have reasonable access to mainstream labour market opportunities. However, it is consistent with the a general lack of CDEP-scheme jobs in cities. Another possible explanation is that the urban Indigenous population live in locationally disadvantaged areas where there is limited or expensive access to existing jobs.[17]
POLICY DISCUSSION
This article emphasises the importance of geography through analysis of the spatial distributions of CDEP-scheme employment and unemployment-related benefits. CDEP-scheme employment appears to provide an effective substitute for employment demand in areas where this demand is deficient. The strong inverse association between regional employment opportunities and the location of CDEP-scheme employment is evidence that CDEP is extremely important in addressing the spatial mismatch of Indigenous workers and jobs.
The general lack of inter-regional mobility of the Indigenous population, noted elsewhere,[18] tends to reinforce this spatial mismatch across ATSIC regions. One alternative to CDEP for redressing spatial mismatch is to encourage labour mobility to areas where job opportunities exist. However, this may not be a realistic option given the strong attachment many Indigenous people in rural and remote regions have towards their traditional lands and their complex kin networks.
Many CDEP scheme participants are drawn from outside the labour force rather than from the pool of Indigenous unemployed.[19] Clearly, the multi-faceted nature of the scheme means that CDEP-scheme employment addresses several needs in the community and cannot be considered as just another source of unemployment-related welfare.
The growth of CDEP-scheme par- ticipation has complicated the analysis of Indigenous unemployment. This article shows that the CEDP program affects the number of DSS clients on unemployment-related benefits and the extent to which these clients are long-term recipients.
While the pattern of Indigenous un- employment may differ from that of other Australians, care should be exercised in interpreting these results. The Royal Commission into Aboriginal Deaths in Custody repeatedly expressed concern about the extent to which Indigenous people endure chronic unemployment and the potential social pathology that arises from this.[20] Our analysis indicates that the problem of long-term unemployment among Indigenous people is greater in the more developed parts of the continent in south-east Australia. However, while the measured level of chronic unemployment may be relatively low in many remote areas, there are still valid questions about the extent to which CDEP is merely ar- tificially altering the number rather than addressing the core issues relating to the potential social pathology.[21]
Nevertheless, to understand the patterns of dependence of Indigenous people on government unemployment-related support, one cannot simply add the CDEP and DSS benefit numbers. Indeed, even with respect to Indigenous welfare dependence one cannot view CDEP as a simple welfare tool. The scheme has a clear role in addressing the adverse employment demand conditions in remote areas and can be viewed as both a labour market and welfare program.[22]
We have also established that there is only a limited relationship between em- ployment demand in the area and the number of unemployment beneficiaries. Indigenous unemployment appears in- sensitive to conditions in the mainstream labour market.[23] The lack of a significant relationship between employment demand and unemployment-related benefits indicates that the Indigenous and non-Indigenous labour markets are largely separate with little substitution between the two types of labour. The lack of sub- stitutability of Indigenous and non-In- digenous labour, or more formally, the mismatch of the Indigenous labour supply and employment demand across industries and occupations are the most likely factors explaining the distinctive Indigenous labour-market outcomes in many ATSIC regions.
Given the limited physical mobility of Indigenous workers, it may be more fruitful to address educational training opportunities which facilitate mobility of employment across sectors. Several recent studies of Indigenous employment outcomes point to the significant im- provements that can occur with educational and training enhancements.[24] However, education needs to be focussed on increasing employment opportunities for Indigenous workers in the local area, and to this end it must be sensitive to the skills required by local firms with potential for employment growth.
References
1. M.C. Dillon, 'Program evaluation and monitoring in Aboriginal and Torres Strait Islander affairs: a strategic overview', in C. O'Faircheallaigh and B. Ryan (eds) Program Evaluation and Performance Monitoring: An Australian Perspective, Macmillan, Melbourne, 1992, p102.
2. J.C. Altman and W. Sanders 'The CDEP scheme: administrative and policy issues', Australian Journal of Public Administration, vol. 50 no. 4, 1991, pp. 515-25.
3. P.N. Junankar and C.A. Kapuscinski, 'Aboriginal employment and unemployment: an overview', Economic Papers, vol. 10, no. 4, 1991, p39.
4. Australian Bureau Statistics (ABS), Estimated resident population , ABS cat. no._3208, Canberra, 1995.
5. See B. Hunter, 'Indigenous Australians and the socioeconomic status of urban neighbourhoods', Centre for Aboriginal Economic Policy Research (CAEPR) Discussion Paper No. 106, CAEPR, ANU, Canberra, 1996. The population of unemployment-related beneficiaries in each postcode is quite small on average (less than ten) with many postcodes having only one Indigenous person who is unemployed. This is too small to base an estimate of the distribution of unemployment-related benefits.
6. Also see ABS, Better Employment Outcomes for Indigenous People: Findings from the National Aboriginal and Torres Strait Islander Survey , ABS, cat. no. 4199.0, Canberra, 1996. The NATSIS results also indicate that there is little variation in long-term Indigenous un- employment across areas. However, the NATSIS results are not strictly comparable with the DSS results because it is based on the part-of-State rather than the section-of-State geographic classification.
7. The number of unemployed identified by NATSIS should be considerably higher than the DSS figure simply because not all registered CES clients will be receiving unemployment-related benefits from DSS.
8. ABS, ibid.
9. National unemployment rates fell from 9.6 to 8.1 per cent between the collection of NATSIS and the DSS data. 1 ABS, National Aboriginal and Torres Strait Islander Survey 1994: Detailed Findings, ABS cat. no._4190.
10. ABS, Canberra, 1995.
11. See Figure A1 for correspondences between names and location for all ATSIC region.
12. Commonwealth of Australia, Indigenous Australians Today: a statistical focus by ATSIC regions, Aboriginal and Torres Strait Islander Commission, Canberra, 1994.
13 J. Taylor, The Relative Economic Status of Indigenous Australians, 1986-91, Research Monograph No. 5, CAEPR, ANU, Canberra, 1993.
14. J. Taylor and J. Lui, 'Changes in the relative distribution of Indigenous employment by industry, 1986-96', CAEPR Discussion Paper No. 96, CAEPR, ANU, Canberra, 1995. Also see J. Taylor and J. Lui, 'Changes in the relative occupational status of Indigenous workers, 1986-96' CAEPR Discussion Paper No. 104, CAEPR, ANU, Canberra, 1996.
15. ABS, 1995, op. cit.
16. See ABS, 1996, op. cit.
17. B. Hunter, op. cit.
18. M. Bell and J. Taylor, 'The mobility status of Indigenous Australians' CAEPR Discussion Paper No. 78, CAEPR, ANU, Canberra, 1994.
19. J.C. Altman and B. Hunter, 'The Comparative economic status of CDEP and non-CDEP community residents in the Northern Territory in 1991', CAEPR Discussion Paper No. 107, ANU, Canberra, 1996.
20. Commonwealth of Australia, Royal Commission into Aboriginal Deaths in Custody, National Report , Australian Government Publishing Service, Canberra 1991, pp. 380-383.
21. See D. Smith , 'Redfern works: the policy and community challenges of an urban CDEP scheme' CAEPR Discussion Paper No. 99, CAEPR, ANU, Canberra, 1995.
22. These themes are fully developed in W. Sanders, 'The rise and rise of the CDEP scheme: an Aboriginal "workfare" program in times of persistent unemployment' CAEPR Discussion Paper No. 54, CAEPR, ANU, Canberra, 1993.
23. J.C. Altman and A.E. Daly, 'Do fluctuations in the Australian macroeconomy influence Aboriginal employment status?', Economic Papers, vol. 11, no. 4, 1992, pp. 32-48.
24. The most recent study is ABS, 1996, op. cit.
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