4102.0 - Australian Social Trends, 2003
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 03/06/2003
Page tools:
 Print Page
 Print All
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Underutilised labour: Geographic distribution of unemployment
UNEMPLOYMENT RATE IN STATISTICAL LOCAL AREAS - 2001 Source: ABS 2001 Census of Population and Housing. RANGE OF UNEMPLOYMENT RATES AMONG STATISTICAL LOCAL AREAS - 2001
Source: ABS 2001 Census of Population and Housing. Unemployment across Statistical Local Areas In August 2001, unemployment rates ranged widely across Statistical Local Areas (SLAs). However, while there was variation within states and territories, there was also a tendency for some adjoining SLAs within a state or territory to share similar rates of unemployment. For example, set against a national unemployment rate of 7.4% (as measured in the 2001 Census), most Tasmanian SLAs (84%) had above average unemployment, with the majority (57%) having a rate of at least 10%. On the mainland, a long belt of coastal and coastal hinterland SLAs in northern New South Wales and southern Queensland had an unemployment rate of 10% or higher. On the other hand, below average rates were common in inland SLAs on the mainland, with lower than 5% unemployment prevailing in many of the more remote SLAs, particularly those in central Queensland, the Riverina and the more arid parts of South Australia and Western Australia. Many of these SLAs had small populations, characterised by self employment in agriculture, and an above average labour force participation rate. The outward migration of some unemployed people may also have contributed to the comparatively low rate of unemployment in these SLAs.
STATISTICAL SUBDIVISIONS WITH THE LOWEST AND HIGHEST UNEMPLOYMENT RATE - 2001
Source: ABS 2001 Census of Population and Housing. Broader regions The unemployment rate varies considerably between small areas such as SLAs, due to the tendency for residential clustering of people with similar demographic, socioeconomic and/or labour market characteristics, and because of very localised labour markets. Hence it is also useful to look at broader geographic areas when considering unemployment. At the broader Statistical Subdivision (SSD) level in 2001, each state and territory (with the exception of Tasmania and the Australian Capital Territory) comprised SSDs with unemployment rates ranging from lows of between 2.5% and 4.1%, to highs of between 12.0% and 15.0%. Of the exceptions, each Tasmanian SSD had an unemployment rate above the national average (ranging from 9.2% to 12.5%) while those in the Australian Capital Territory were all below the average (ranging from 3.8% to 6.9%). Across all SSDs in 2001, a low unemployment rate tended to be accompanied by a high labour force participation rate, and a high unemployment rate tended to be accompanied by a low labour force participation rate. Further, for each of the six states, the SSD with the highest rate of unemployment was either one of two types of areas. Some were areas with a growing population but not necessarily commensurate employment opportunities, i.e. Clarence (excluding Coffs Harbour) in northern New South Wales, Hervey Bay City Part A in southern Queensland, and Mandurah in Western Australia. Others were areas affected by economic restructuring and which traditionally had a relatively high concentration of employment in industries experiencing job losses over the last decades of the 20th Century (i.e. Whyalla in South Australia, Burnie-Devonport in Tasmania, and La Trobe Valley in Victoria). On the other hand, the SSD with the lowest rate of unemployment in each state tended to be either a group of capital city suburbs, or a farming area with a high incidence of self employment among those employed. In New South Wales, the SSD of Northern Beaches (comprising the Sydney SLAs of Manly, Pittwater and Warringah) had the state's lowest unemployment rate (3.4%). In Victoria, the SSD with the lowest rate (West Mallee 3.3%) had a relatively high proportion of employed persons working as employers, own account workers or contributing family workers (41% compared with the national average of 18%). Similarly, in Queensland, South Australia and Western Australia, the rate of unemployment was lowest in rural SSDs with a relatively high propensity for self employment in agriculture. The reasons for low unemployment vary from one area to another. For example, in the territories, SSDs with the lowest rate had different demographic and labour market profiles to those with the lowest rate in each of the six states. In the Australian Capital Territory, the unemployment rate was lowest in Gungahlin-Hall (3.8%), with this SSD having the nation's highest labour force participation rate (80%). Gungahlin-Hall had a young population (median age of 29 years) and a higher proportion of children than the national average. The area also had comparatively high rents and housing loan repayments, and few public housing tenants. In the Northern Territory, the SSD with the lowest unemployment rate was East Arnhem. Unlike most other SSDs with a low rate of unemployment, East Arnhem had a comparatively small propensity for self-employment among employed persons (6%), and a relatively low labour force participation rate (54% compared with the national average of 63%). An above average proportion of employed people in East Arnhem were employed in the Mining industry (14% compared with less than 1% nationwide) and, reflecting East Arnhem's largely Indigenous population, a comparatively high proportion of employed people were employed under the Community Development Employment Program (CDEP) (25% compared with less than 1% nationally).
Characteristics of unemployed people In 2001, the average rate of unemployment in Major Cities was 7.1%. While higher overall outside these cities (8.0%), the rate varied across regional and remote Australia and generally eased with increasing remoteness. The rate was higher in Inner Regional areas (8.5%), lower in Outer Regional areas (7.9%), and decreased to 4.5% in Very Remote areas. In terms of absolute numbers of unemployed people, the vast majority were located in Major Cities (65%) or Inner Regional areas (22%), with 2% in Remote or Very Remote areas. This distribution across Remoteness Areas largely reflects the spread of the total population across these areas and partly mirrors the higher rate of unemployment in non-remote areas. The characteristics of unemployed people in each of the Remoteness Areas also tended to reflect the overall population characteristics of each area (see Australian Social Trends 2003, Population characteristics and remoteness). For example, more than one-third (35%) of all unemployed people in Major Cities were aged 15–24 years. In more remote areas, unemployed people were more likely to be older. SELECTED CHARACTERISTICS OF UNEMPLOYED PEOPLE(a) IN REMOTENESS AREAS - 2001
(b) Includes Migratory category. Source: ABS 2001 Census of Population and Housing. In each Remoteness Area, the unemployment rate among 15-24 year olds was higher than it was among older people. Yet this youth unemployment rate itself varied considerably between Remoteness Areas. In particular, the youth unemployment rate was much lower in Very Remote areas (7.5%) than in Inner Regional areas (16.4%); a difference that may partly reflect the outward migration of young people to areas with more employment opportunities.1 Men have slightly higher unemployment rates than women, with more unemployed men than women in each of the Remoteness Areas. The majority of unemployed people in Major Cities were men (59%), and this proportion increased with remoteness. In Remote and Very Remote areas, nearly two in three (64%) unemployed people were men. Unemployed people in Major Cities and regional areas were also more likely than unemployed people in more remote areas to be living as a member of a family with one or more dependent children. For example, 58% of unemployed people in Major Cities were in this living arrangement compared with 44% of unemployed people in Very Remote areas. Furthermore, unemployed people in Major Cities were more likely to have non-school qualifications than unemployed people in Very Remote areas (37% compared with 27%). At each degree of remoteness in 2001, labour force participants without a non-school qualification were twice as likely to be unemployed as those who did possess a non-school qualification. Nevertheless, the unemployment rate among people without a non-school qualification was lower for those in Very Remote areas (5.7%) than for those in Major Cities (9.6%) and Inner Regional areas (11.1%). This may partly reflect migration of job seekers between Remoteness Areas. The proportion of unemployed people who were Indigenous rose with increasing remoteness. In 2001, Indigenous peoples constituted a markedly greater proportion of unemployed people in Very Remote areas (42%) and Remote areas (21%) than in Outer Regional areas (9%), Inner Regional areas (4%) and Major Cities (2%). At each degree of remoteness, the Indigenous unemployment rate was around three times higher than the non-Indigenous rate. Yet the Indigenous unemployment rate itself varied widely between Remoteness Areas, being considerably lower in Very Remote areas (8.2%) than in Inner Regional areas (25.3%). This difference may partly reflect the higher proportion of CDEP employment among Indigenous labour force participants in Very Remote areas compared with Inner Regional areas. UNEMPLOYMENT RATE BY REMOTENESS AREA AND ENGLISH LANGUAGE PROFICIENCY(a) - 2001 (a) Non response has been excluded from percentage calculations presented in this graph. (b) For those who speak a language other than English at home. Source: ABS 2001 Census of Population and Housing. English language proficiency In Australia, level of skill in comprehending and expressing ideas in the English language can affect a person's chances of getting and holding a job. This communication skill is likely to be more important for some jobs than others. In 2001, the unemployment rate for people who spoke only English at home followed the same pattern across Remoteness Areas as the total population. The pattern also prevailed among people who spoke a language other than English at home but who nevertheless spoke English well or very well. However, at each degree of remoteness, the unemployment rate among the latter group of people who spoke a language other than English at home was a little higher than the unemployment rate among those who spoke only English at home. In Major Cities, for example, comparative rates of unemployment were 9.2% and 6.3% respectively. The story differed for people who spoke a language other than English at home but who did not speak English well. Among these people, those located in Major Cities had the highest unemployment rate (19.5%). Their rate was still high outside the Major Cities when compared with rates for those who spoke only English at home, and those who spoke another language at home yet spoke English well or very well. However, the difference in the unemployment rate between people with and without English language difficulty generally lessened as remoteness increased.
Endnotes 1 Haberkorn, G., Hugo, G., Fisher, M. and Aylward, R. 1999, Country Matters: Social atlas of rural and regional Australia, Bureau of Rural Sciences, Canberra. 2 Chapman, B. 1993, 'Long-term unemployment: The case for policy reform', reprinted in the Social Security Journal, June 1994, pp. 19–39, AGPS, Canberra.
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
