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The publication Labour Force, Australia (cat. no. 6202.0) contains information about survey design, sample redesign, scope, coverage and population benchmarks relevant to the monthly LFS, which also apply to supplementary surveys such as the SEW. It also contains definitions of demographic and labour force characteristics.
Concepts, sources, and methods
The conceptual framework used in Australia's LFS aligns closely with the standards and guidelines set out in Resolutions of the International Conference of Labour Statisticians. Descriptions of the underlying concepts and structure of Australia's labour force statistics, and the sources and methods used in compiling these estimates, are presented in Labour Statistics: Concepts, Sources and Methods, Feb 2018 (cat. no. 6102.0.55.001).
In July 2014, the LFS survey questionnaire underwent a number of developments. For further information see Information Paper: Questionnaire Used in the Labour Force Survey, July 2014.
The scope of the SEW is restricted to people aged 15-74 years who were usual residents of private dwellings and non-institutionalised special dwellings excluding:
Boarding school pupils have been excluded from the scope of the SEW since 2005, but were included in earlier collections.
Since 2009, SEW has included people living in 'very remote' areas who are not in Indigenous Communities. Prior to SEW 2009, all people living in 'very remote' parts of Australia were excluded. Nationally, less than 1% of people in scope of SEW live in 'very remote' areas that are not Indigenous Communities. In the Northern Territory, this proportion is higher, at around 8%.
In 2013, the scope of SEW was extended to include all people aged 65-74 years for the first time. From 2009 to 2012, people aged 65-74 years who were in the labour force, or were marginally attached to the labour force were included.
Persons who are permanently unable to work were included in the scope of SEW for the first time in 2013. There were an estimated 456,733 people who reported being permanently unable to work in May 2019.
In the LFS, coverage rules are applied which aim to ensure that each person is associated with only one dwelling and has only one chance of selection in the survey. See Labour Force, Australia (cat. no. 6202.0) for more details.
Data from the SEW is available by State, Greater Capital City Statistical Area, Section of State, Remoteness area and Statistical Area Level 4, subject to confidentiality constraints. Geography has been classified according to the
Australian Statistical Geography Standard (ASGS), July 2016. For a list of these publications see the ABS Geography Publications page.
How the data is collected
Information was collected from respondents over a two week period in May 2019. The data were collected through interviews, conducted either face-to-face or over the telephone, or respondents were able to provide their information over the internet via a self-completed form. All information in the SEW was obtained from any person in the household aged 15 years or over who was asked to respond on behalf of all people in the household in scope of the survey. If the responsible adult was unable to supply all of the details for another individual in the household, a personal interview was conducted with that particular individual.
Approximately 91% of the selected households were fully responding to the Monthly Population survey in May 2019, which resulted in 38,683 completed interviews.
Key Education concepts
Australian Standard Classification of Education (ASCED)
Education data are coded to the Australian Standard Classification of Education, 2001 (cat. no. 1272.0). The ASCED is a national standard classification which can be applied to all sectors of the Australian education system, including schools, vocational education and training, and higher education. It includes:
Level of Education of Current Study
Since 2014, people identified in the Labour Force Survey as currently studying a school level qualification have been asked in the Survey of Education and Work (SEW) whether they are currently studying for any non-school qualifications. If they are still attending school, their level of study is recorded as their current year of schooling, not their non-school qualification.
Level of Highest Education Attainment
Level of highest educational attainment identifies the highest achievement a person has attained in any area of formal study. It is derived from highest year of school completed and level of highest non-school qualification. The derivation process determines which of the 'school' or 'non-school' attainments will be regarded as the highest. Usually the higher ranking attainment is self-evident, but in some cases some secondary education is regarded, for the purposes of obtaining a single measure, as higher than some certificate level attainments.
There are two types of measures used in this publication to determine level of highest educational attainment: 'Non-School Priority' and 'Standard Education Priority'.
Decision table: Level of highest educational attainment
Cert = Certificate
L.n.d. = Level not determined
n.f.d. = not further defined
N.S. = Not Stated
Sec. = Secondary
For ease of interpretability, the layout of this table has been modified from Education Variables, June 2014 (cat. no. 1246.0), however the ranking of different levels of attainment has not changed.
Engagement in Employment and Education
The term 'engagement' is used when assessing a person's level of participation in employment and education. The following table shows the ways in which people can be 'Fully engaged', 'Partially engaged', or 'Not engaged'.
How the data is processed
Weighting is the process of adjusting results from a sample survey to estimate characteristics of the total population. To do this, a 'weight' is allocated to each enumerated person. The weight is a value which indicates how many people in the population are represented by the sample person.
The first step in calculating weights for each unit is to assign an initial weight, which is the inverse of the probability of the unit being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 300, then the person would have an initial weight of 300 (that is, they represent 300 people).
The initial weights are then calibrated to align with independent estimates of the population, referred to as benchmarks. The population included in the benchmarks is the survey scope. This calibration process ensures that the weighted data conform to the independently estimated distribution of the population described by the benchmarks rather than to the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories which may occur due to either the random nature of sampling or non-response.
The survey was benchmarked to the estimated resident population (ERP) aged 15-74 years living in private dwellings and non-institutionalised special dwellings in each state and territory. People living in Indigenous communities were excluded.
Survey estimates of counts of people are obtained by summing the weights of people with the characteristics of interest.
To minimise the risk of identifying individuals in aggregate statistics, a technique called perturbation is used to randomly adjust cell values. Perturbation involves small random adjustment of the statistics which have a negligible impact on the underlying pattern. This is considered the most satisfactory technique for avoiding the release of identifiable data while maximising the range of information that can be released. After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values in Data Cubes to derive a total may give a slightly different result to the published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as TableBuilder.
Reliability of estimates
All sample surveys are subject to error which can be broadly categorised as either sampling or non-sampling error. For more information refer to the Technical Note.
The estimates are based on information collected in May 2019, and due to seasonal factors (such as school terms, semesters, or intake periods for other qualifications), they may not be representative of other months of the year.
Comparability of time series
In addition to the changes in scope listed in the 'Scope' section, there are a number of other changes to be aware of with regard to how SEW has been collected and reported over time.
Size of the sample
Supplementary surveys are not always conducted on the full LFS sample. Since August 1994 the sample for supplementary surveys has been restricted to no more than seven-eighths of the LFS sample. Since it was introduced, this survey has been conducted on various proportional samples and therefore sampling errors associated with previous supplementary surveys may vary from the sampling error for this survey.
Since 2007, industry data in the SEW have been classified according to the Australian and New Zealand Standard Industrial Classification, 2006 (cat. no. 1292.0). Prior to this, they were classified according to the Australian and New Zealand Standard Industrial Classification, 1993 (cat. no. 1292.0) and are therefore not directly comparable to data for 2007 and subsequent years.
Since 2007, occupation data in the SEW have been classified according to the Australian and New Zealand Standard Classifications of Occupations, First Edition, Revision 1 (cat. no. 1220.0). Prior to this, they were classified according to the Australian Standard Classifications of Occupations, Second Edition, 1997 (cat. no. 1220.0) and are therefore not directly comparable to 2007 and subsequent years.
Prior to 2008, only people aged 15-54 years were included in the apprenticeship/traineeship survey questions. In 2008, the age scope was extended to include people aged 55-64 years and in 2009, the scope was further extended to include people aged 65-74 years for these questions. In 2008, the definition for apprentices and trainees changed from those employed as apprentices/trainees to include only those with a formal contract under the Australian Apprenticeships scheme. Therefore data on apprentices from previous years are not directly comparable to 2008 and subsequent data.
Other comparability issues
Comparability with other ABS surveys
Differences may also exist in the scope and/or coverage of the SEW compared to other surveys. Differences in estimates, when compared to the estimates of other surveys, may result from different reference periods reflecting seasonal variations, non-seasonal events that may have impacted on one period but not another, or because of underlying trends in the phenomena being measured.
Finally, differences can occur as a result of using different collection methodologies. This is often evident in comparisons of similar data items reported from different ABS collections where, after taking account of definition and scope differences and sampling error, residual differences remain. These differences are often the result of the mode of the collections, such as whether data are collected by an interviewer or self-enumerated by the respondent and whether the data are collected from the person themselves or from a proxy respondent. Differences may also result from the context in which questions are asked, i.e. where in the interview the questions are asked and the nature of preceding questions. The impacts on data of different collection methodologies are difficult to quantify. Every effort is made to minimise such differences.
How the data is released
A number of data cubes (spreadsheets) containing all tables produced for this publication are available from the Downloads tab of the publication. The data cubes present tables of estimates and proportions, and their associated measures of error.
For users who wish to undertake more detailed analysis of the data, the survey microdata will be released through the TableBuilder product (see Microdata: Education and Work, Australia (cat. no. 6227.0.30.001) for more detail). Microdata can be used by approved users to produce customised tables and analysis from the survey data. Microdata products are designed to ensure the integrity of the data whilst maintaining the confidentiality of the respondents to the survey. More information can be found at How to Apply for Microdata.
Detailed microdata may also be available on DataLab for users who want to undertake interactive (real time) complex analysis of microdata in the secure ABS environment. For more details, refer to About the DataLab.
Customised statistical tables to meet individual requirements can be produced on request. These are subject to confidentiality and sampling variability constraints which may limit what can be provided. Enquiries on the information available and the cost of these services should be made to the National Information and Referral Service on 1300 135 070.
History of changes
Results of similar surveys have been published in previous issues. These surveys were conducted annually from February 1964 to February 1974, in May 1975 and 1976, in August 1977 and 1978, and annually in May since 1979. Results of previous surveys were published in Transition from Education to Work, Australia (cat. no. 6227.0) from 1964 to 2000. Since May 2001, the results of the survey have been published in Education and Work, Australia (cat. no. 6227.0).
The ABS intends to conduct this survey again in May 2020.
Other ABS publications which may be of interest are shown under the ‘Related Information’ tab of this release.
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