Qualifications and work methodology

Latest release
Reference period
2022-23 financial year

Overview

Scope

People aged 15 to 74 years who were usual residents of private dwellings.
Excludes:

  • Australian permanent defence force members and their dependants
  • non-Australian defence forces
  • residents of the Indigenous Community Strata.

Geography

Data available for:

  • Australia
  • Major cities
  • Inner regional
  • Outer regional
  • Remote/very remote.

Source

Multipurpose Household Survey

Collection method

Interviews were conducted by telephone with responses directly recorded in an electronic questionnaire.
Proxy interviews were permissible under certain circumstances.

Concepts, sources and methods

Education data are coded to the Australian Standard Classification of Education (ASCED), 2001.

History of changes

See Comparing the data.

Data collection

Overview

This release presents the results from the Qualifications and Work (Q&W) survey, a topic on the Multipurpose Household Survey (MPHS) conducted throughout Australia from July 2022 to June 2023. The MPHS, undertaken each financial year by the Australian Bureau of Statistics (ABS), is a supplement to the monthly Labour Force Survey (LFS) and is designed to collect statistics for a number of small, self-contained topics.

The Q&W survey collected information about the following:

  • level and field of up to five qualifications
  • year of their qualification completion
  • whether qualifications were attained in Australia
  • relevance of completed qualifications to people's current jobs
  • labour force characteristics
  • main language spoken at home
  • income
  • other demographics.

Scope

The scope of the survey was restricted to people aged 15-74 years who were usual residents of private dwellings and excludes:

  • members of the Australian permanent defence forces
  • certain diplomatic personnel of overseas governments, customarily excluded from Census and Estimated Resident Population (ERP) counts
  • overseas residents in Australia (intending to stay less than 12 months)
  • members of non-Australian defence forces (and their dependants)
  • persons living in non-private dwellings such as hotels, university residences, boarding schools, hospitals, nursing homes, homes for people with disabilities, and prisons
  • persons resident in the Indigenous Community Strata (ICS).

The scope for MPHS included households residing in urban, rural, remote and very remote parts of Australia, except the ICS.

Coverage

In the LFS, rules are applied which aim to ensure that each person in scope is associated with only one dwelling, and hence has only one chance of selection in the survey. See Labour Force, Australia for more detail. 

Data from the Q&W survey 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.

Sample size

Information was collected from 22,673 fully responding persons. This includes 511 proxy interviews for people aged 15 to 17 years, where permission was not given by a parent or guardian for a personal interview, and 1,465 proxy interviews for people aged 18-74 years who were not capable of answering for themselves due to illness, injury or language problems.

Collection method

Each month, one eighth of the dwellings in the LFS sample were rotated out of the survey and selected for the MPHS. After the LFS had been fully completed for each person in scope and coverage, a usual resident aged 15 years or over was selected at random (based on a computer algorithm) and asked the additional MPHS questions in a personal interview.

In the MPHS, if the randomly selected person was aged 15 to 17 years, permission was sought from a parent or guardian before conducting the interview. If permission was not given, the parent or guardian was asked the questions on behalf of the 15 to 17 year old (proxy interview). If the randomly selected person was aged 18 years and over but was not capable of answering for themselves, due to illness, injury or language problems, the person responsible for them could be asked the questions on their behalf (proxy interview).

Data were collected using Computer Assisted Interviewing, whereby responses were recorded directly onto an electronic questionnaire in a notebook computer, with interviews conducted over the telephone. 

Processing the data

Weighting

As only a sample of people were surveyed, their results needed to be converted into estimates for the whole population. This was done with a process called weighting.

  • Each person was given a number (known as a weight) to reflect how many people they represented in the whole population.
  • A person's initial weight was based on their probability of being selected in the sample. 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).

Benchmarks

After calculating the initial person weights, an adjustment was incorporated into the weighting for persons to account for all persons in the population.

The person weights were separately calibrated to independent estimates of the in-scope population, referred to as ‘benchmarks’. The benchmarks used additional information about the population to ensure that:

  • people in the sample represented people who were similar to them
  • the survey estimates reflected the distribution of the whole population, not the sample.

The survey was benchmarked to the Estimated Resident Population (ERP) aged 15-74 living in private dwellings in each state and territory at December 2022. People living in Indigenous communities were excluded. These benchmarks are based on the 2021 Census. 

While LFS benchmarks are revised every 5 years, to take into account the outcome of the 5-yearly rebasing of the ERP following the latest Census, the supplementary surveys and MPHS (from which the statistics in this publication are taken) are not. Small differences will therefore exist between the civilian population aged 15 years and over reflected in the LFS and other labour household surveys estimates, as well as over time. If comparisons are being made over time then proportions should be used rather than estimates of persons. 

    Estimation

    Survey estimates of counts of persons are obtained by summing the weights of persons with the characteristic of interest.

      Accuracy

      Show all

      Reliability of estimates

      Two types of error are possible in estimates based on a sample survey:

      • non-sampling error
      • sampling error

      ​​​​​​​Non-sampling error

      Non-sampling error is caused by factors other than those related to sample selection. It is any factor that results in the data values not accurately reflecting the true value of the population.

      It can occur at any stage throughout the survey process. Examples include:

      • selected people that do not respond (e.g. refusals, non-contact) 
      • questions being misunderstood
      • responses being incorrectly recorded
      • errors in coding or processing the survey data

      Sampling error

      Sampling error is the expected difference that can occur between the published estimates and the value that would have been produced if the whole population had been surveyed. Sampling error is the result of random variation and can be estimated using measures of variance in the data. 

      Standard error

      One measure of sampling error is the standard error (SE). There are about two chances in three that an estimate will differ by less than one SE from the figure that would have been obtained if the whole population had been included. There are about 19 chances in 20 that an estimate will differ by less than two SEs.

      ​​​​​​​Relative standard error

      The relative standard error (RSE) is a useful measure of sampling error. It is the SE expressed as a percentage of the estimate:

      \(R S E \%=\left(\frac{S E}{e s t i m a t e}\right) \times 100\)

      Only estimates with RSEs less than 25% are considered reliable for most purposes. Estimates with larger RSEs, between 25% and less than 50% have been included in the publication, but are flagged to indicate that they should be used with caution. Estimates with RSEs of 50% or more have also been flagged and are considered unreliable for most purposes. RSEs for these estimates are not published.

      Margin of error for proportions

      Another measure of sampling error is the Margin of Error (MOE). This describes the distance from the population value that the sample estimate is likely to be within and is particularly useful to understand the accuracy of proportion estimates.

      The MOE is specified at a given level of confidence. Confidence levels typically used are 90%, 95% and 99%. For example, at the 95% confidence level, the MOE indicates that there are about 19 chances in 20 that the estimate will differ by less than the specified MOE from the population value (the figure obtained if the whole population had been enumerated). The 95% MOE is calculated as 1.96 multiplied by the SE:
      \( M O E=S E \times 1.96\)

      The RSE can also be used to directly calculate a 95% MOE by: 

      \(\normalsize MOE(y) \approx \frac{R S E(y) \times y}{100} \times 1.96\)

      The MOEs in this publication are calculated at the 95% confidence level. This can easily be converted to a 90% confidence level by multiplying the MOE by:

       \( \Large\frac{1.615}{1.96}\)

      or to a 99% confidence level by multiplying the MOE by:

       \(\Large\frac{2.576}{1.96}\)

      Depending on how the estimate is to be used, a MOE of greater than 10% may be considered too large to inform decisions. For example, a proportion of 15% with a MOE of plus or minus 11% would mean the estimate could be anything from 4% to 26%. It is important to consider this range when using the estimates to make assertions about the population.

      ​​​​​​​Confidence Intervals

      The estimate combined with the MOE defines a range, known as a confidence interval. This range is likely to include the true population value with a given level of confidence. It is important to consider this range when using the estimates to make assertions about the population or to inform decisions. The 95% confidence interval can be calculated, as follows:

      \( 95 \% \text { Confidence Interval }=(\text {estimate}-M O E, \text { estimate }+M O E)\)

      Measures of error in this release

      The datacube reports the relative standard error (RSE) for estimates of counts ('000) and the margin of error (MOE) for estimates of proportions (%) (available in the Data downloads section of the main release).

      Estimates of proportions with a MOE greater than 10% are annotated to indicate they are subject to high sample variability and particular consideration should be given to the MOE when using these estimates. In addition, estimates with a corresponding standard 95% confidence interval that includes 0% or 100% are annotated to indicate they are usually considered unreliable for most purposes.

      Calculating measures of error

      Proportions or percentages formed from the ratio of two count estimates are also subject to sampling errors. The size of the error depends on the accuracy of both the numerator and the denominator. A formula to approximate the RSE of a proportion is given below. This formula is only valid when the numerator (x) is a subset of the denominator (y):

      \(\normalsize RSE\left(\frac{x}{y}\right) \approx \sqrt{[R S E(x)]^{2}-[R S E(y)]^{2}}\)

      When calculating measures of error, it may be useful to convert RSE or MOE to SE. This allows the use of standard formulas involving the SE. The SE can be obtained from RSE or MOE using the following formulas:

      \(S E(y)=\frac{R S E(y) \times y}{100}\)

      \(S E=\Large\frac{M O E}{1.96}\)

      Comparison of estimates

      The difference between two survey estimates (counts or percentages) can also be calculated from published estimates. Such an estimate is also subject to sampling error. The sampling error of the difference between two estimates depends on their SEs and the relationship (correlation) between them. An approximate SE of the difference between two estimates (x - y) may be calculated by the following formula:

      \(S E(x-y) \approx \sqrt{[S E(x)]^{2}+[S E(y)]^{2}}\)

      While this formula will only be exact for differences between separate and uncorrelated characteristics or sub populations, it provides a good approximation for the differences likely to be of interest in this publication.

      Significance testing

      When comparing estimates between surveys or between populations within a survey, it is useful to determine whether apparent differences are 'real' differences or simply the product of differences between the survey samples. 

      One way to examine this is to determine whether the difference between the estimates is statistically significant. This is done by calculating the standard error of the difference between two estimates (x and y) and using that to calculate the test statistic using the formula below:

      \(\large \frac{|x-y|}{S E(x-y)}\ \)

      where

      \(\normalsize SE(y)\approx\frac{R S E(y) \times y}{100}\)

      If the value of the statistic is greater than 1.96, we can say there is good evidence of a statistically significant difference at 95% confidence levels between the two populations with respect to that characteristic. Otherwise, it cannot be stated with confidence that there is a real difference between the populations.

      Comparing the data

      Comparability of Time Series

      When comparing data from different cycles of the survey, users should be aware of the following significant changes.

      In 2022-23:

      • the scope of the Q&W survey was reduced from people aged 15 years and over to people aged 15-74 years. 
      • the age scope of the tables in the datacube has increased from 15-64 years to 15-74 years. As a result, care should be taken when comparing proportions reported in equivalent tables. 
      • the scope of migrants in the datacube has been expanded to include all persons not born in Australia or the Australian external territories. Previously, this was limited to migrants who arrived in Australia aged 15 years and older (referred to as Adult Migrants).
      • qualifications of migrants who completed a non-school qualification in the same year as their arrival in Australia have been treated as being completed before arrival in Australia. 
      • caution should be taken in comparing qualifications of migrants before and after the COVID pandemic as certain key populations may have been affected due to changes in net overseas migration during 2020-22.

      In  previous years:

      • 2010-11 data for this topic was previously published as the 'Learning and work survey'. It had a smaller sample size (13,366 persons) as compared to the surveys collected after this iteration that are at least double in sample size.
      • in 2015 data was collected from January to December, where as in 2022-23, 2018-19 and 2010-11 the data was collected from July to June (e.g. July 2022 to June 2023).
      • in 2018-19, qualifications of migrants who completed a non-school qualification in the same year as their arrival in Australia were treated as being completed after arrival in Australia.

      Comparability to monthly LFS Statistics

      Since the survey is conducted as a supplement to the LFS, data items collected in the LFS are also available in this publication. However, there are some important differences between the two surveys. The scope of the Q&W and the LFS differ (refer to the 'Scope' section above). Due to the differences between the samples, data from this survey and the LFS are weighted separately. Differences may therefore be found in the estimates for those data items collected in the LFS and published as part of Q&W. 

      Comparability with other ABS surveys

      Estimates from the Q&W survey may differ from the estimates for the same or similar data items produced from other ABS collections for several reasons. For example, all sample surveys are subject to different sampling errors so users should take account of the relative standard error (RSE) and margin of error (MOE) on estimates where comparisons are made. Differences may also exist in scope and/or coverage, 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. 

      The survey of Education and Work, Australia (SEW) has some similarities with the Q&W survey. Conducted annually, SEW provides a range of indicators about educational participation and attainment, and data on people's transition between education and work. Comparison of SEW and Q&W data should be undertaken with caution due to different collection methodologies, scope and sample size. SEW is based on a household interview with any responsible adult who responds on behalf of all persons aged 15-74 years in the household. Whereas Q&W is conducted as a personal interview with one randomly selected person aged 15-74 years in the household and only in a few cases as a proxy interview. 

      Comparability with non-ABS sources

      For similar reasons outlined in the section 'Comparability with other ABS surveys', estimates from the Q&W may differ from estimates produced from non-ABS sources. For example, due to differences in collection objectives and definitions, student visa data are not comparable with Home Affairs data. For more information on the Migration Program and Home Affairs statistics, refer to the Department of Home Affairs website. 

      Data release

      Datacubes/spreadsheets 

      A datacube (spreadsheet) containing all tables produced for this publication is available from the Data downloads section of the main release.  The tables have estimates and proportions, and their associated measures of error. As tables names have changed and new tables have been added since the last release, a 'Concordance' spreadsheet is included along with the Data Item List. A copy of the questionnaire is available under the Data downloads section.

      TableBuilder

      For users who wish to undertake more detailed analysis of the data, the survey microdata will be released through the TableBuilder product (see Qualifications and work 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.

      Confidentiality

      The Census and Statistics Act 1905 authorises the ABS to collect statistical information, and requires that information is not published in a way that could identify a particular person or organisation. The ABS must make sure that information about individual respondents cannot be derived from published data.
      To minimise the risk of identifying individuals in aggregate statistics, a technique is used to randomly adjust cell values. This technique is called perturbation. Perturbation involves a small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. After perturbation, a given published cell value will be consistent across all tables. However, adding up cell values to derive a total will not necessarily give the same result as published totals. The introduction of perturbation in publications ensures that these statistics are consistent with statistics released via services such as TableBuilder. 

      Glossary

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      Australian Standard Classification of Education (ASCED)

      Education data are coded to the Australian Standard Classification of Education, 2001. 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' and 'Field of education'.  

      Capital city

      Refers to Greater Capital City Statistical Areas (GCCSA) as defined by the ASGS. The GCCSAs represent the socio-economic extent of each of the eight State and Territory capital cities. The whole of the Australian Capital Territory is included in the GCCSA. See Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2016.

      Completed a qualification

      A person having 'completed' a qualification means they have successfully passed all of the requirements for the qualification and excludes people who have stopped studying without gaining the qualification.

      Country of birth

      Country of birth has been classified according to the Standard Australian Classification of Countries (SACC), 2016. 'Born in Australia' refers to all persons born in Australia or any of its external territories. 'Born overseas' refers to all persons not 'born in Australia', including those born at sea and persons whose country of birth is unknown.  

      ​​​​​​​Currently working in field of qualification

      As reported by respondent when asked in survey if they are currently working in the field of their qualification.

      ​​​​​​​Educational institution

      Any institution whose primary role is education. Included are schools, higher education establishments, colleges of technical and further education and public and private colleges.

      Employed

      People who, during the reference week:

      • worked for one hour or more for pay, profit, commission or payment in kind in a job or business, or on a farm (comprising employees, employers and own account workers); or 
      • worked for one hour or more without pay in a family business or on a farm (i.e. contributing family workers); or 
      • were employees who had a job but were not at work and were: 
        • away from work for less than four weeks up to the end of the reference week; or 
        • away from work for more than four weeks up to the end of the reference week and received pay for some or all of the four week period to the end of the reference week; or 
        • away from work as a standard work or shift arrangement; or 
        • on strike or locked out; or 
        • on workers' compensation and expected to return to their job; or
      • were employers or own account workers who had a job, business or farm, but were not at work.

      Employed full-time

      Employed people who usually worked 35 hours or more a week (in all jobs) and those who, although usually working less than 35 hours a week, worked 35 hours or more during the reference week.

      Employed part-time

      Employed people who usually worked less than 35 hours a week (in all jobs) and either did so during the reference week, or were not at work in the reference week.

      Engagement

      The term engagement is used when assessing a persons level of participation in employment and education. People can be 'Fully engaged', 'Partially engaged', or 'Not engaged'.  

      Employment statusEducation Status
      Full-time studyPart-time studyNot studying
      Full-time employmentFully engagedFully engagedFully engaged
      Part-time employmentFully engagedFully engagedPartially engaged
      Unemployed looking for full-time workFully engagedPartially engagedNot engaged
      Unemployed looking for part-time workFully engagedPartially engagedNot engaged
      Not in the labour forceFully engagedPartially engagedNot engaged

      Equivalised household income

      Equivalised household income is total household income adjusted by the application of an equivalence scale to facilitate comparisons of income levels between households of differing size and composition. Equivalised total household income can be viewed as an indicator of the economic resources available to a standardised household. 

      For a lone person household it is equal to household income. For a household comprising more than one person, it is an indicator of the household income that would be needed by a lone person household to enjoy the same level of economic well-being.

      Field of education

      Refers to the subject matter of an educational activity. Fields of education are related to each other through the similarity of subject matter, through the broad purpose for which the education is undertaken, and through the theoretical content which underpins the subject matter. There are 12 broad fields, 71 narrow fields and 356 detailed fields of education. Where a qualification covered multiple fields (e.g. a double degree) the 'Main Field of Education ' is the field considered the most important for the survey respondent.

      First qualification

      In this survey, the first qualification was based on the earliest year the non-school qualification was completed. Where two or more non-school qualifications were completed in the same year, then the lowest qualification level is considered to be the first qualification. If they were all completed in the same year and at the same level, then the qualification reported last is the first qualification.

      Great capital city

      Refers to Greater Capital City Statistical Areas (GCCSA) as defined by the Australian Statistical Geography Standard (ASGS). The GCCSAs represent the socio-economic extent of each of the eight State and Territory capital cities. The whole of the Australian Capital Territory is included in the GCCSA. See Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2016.

      Income

      Income consists of all current receipts, that are received by the household or by individual members of the household, and which are available for, or intended to support, current consumption.

      • wages and salaries and other receipts from employment (whether from an employer or own incorporated enterprise), including income provided as part of salary sacrificed and/or salary package arrangements 
      • profit/loss from own unincorporated business (including partnerships)
      • net investment income (interest, rent, dividends, royalties) 
      • government pensions and allowances 
      • private transfers (e.g. superannuation, workers' compensation, income from annuities, child support, and financial support received from family members not living in the same household)

      Gross income is the sum of the income from all these sources before income tax, the Medicare levy and the Medicare levy surcharge are deducted. 

      Incomplete qualification

      Refers to a non-school qualification that was started and partially undertaken but never completed. Incomplete qualifications excludes qualifications that are currently being studied. 

      Industry

      International Standard Classification of Education (ISCED)

      The ISCED was developed by the United Nations Educational Scientific and Cultural Organisation (UNESCO) to facilitate comparisons of education statistics and indicators within and between countries. In 2011, the second major revision of this classification was officially adopted by the UNESCO General Conference and takes into account significant changes in education systems worldwide since the previous ISCED revision in 1997. Education data were categorised from ASCED 2001 to ISCED 2011 using a concordance method. For more information, see 'International Standard Classification of Education 2011 (ISCED) 2011 to Australian Standard Classification of Education (ASCED) Concordance (tcisupport.gov.au)', Tertiary Collection of Student Information.

      Level of highest educational attainment

      Level of highest educational attainment identifies the highest achievement a person has attained in any area of formal study. It is not a measurement of the relative importance of different fields of study, but a ranking of qualifications and other educational attainments regardless of the particular area of study or the type of institution in which the study was undertaken. 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 to determine level of highest educational attainment: 'Non-School Priority' and 'Standard Education Priority'. 

      • 'Non-School Priority' is where all non-school qualifications are considered of higher ranking than secondary education. For example, a person whose highest year of school completed was Year 12, and whose level of highest non-school qualification was a Certificate I, would have their level of highest education attainment output as Certificate I. 
      • 'Standard Education Priority' is where some school qualifications are ranked higher than some non-school qualifications. For example, years 10, 11 and 12 are ranked higher than Certificates I, II and n.f.d. The Standard Education Priority is based on the decision table below and was designed for the purpose of obtaining a single value for level of highest educational attainment and is not intended to convey any other hierarchy.

      The following decision table shows which responses to 'highest year of school completed' and 'level of highest non-school qualification' are regarded as the highest. For example, a person's level of highest educational attainment if they completed Year 12 and a Certificate III would be 'Certificate III'. However, if the same person answered 'certificate' to the highest non-school qualification question, their level of highest educational attainment would be output as 'Level not determined'. In addition, for persons who never attended school and do not have a non-school qualification the output is 'No educational attainment'.

      Decision table - Level of Highest Educational Attainment
      Highest year of school completedCert IVCert IIICert III & IV n.f.d.Cert IICert ICert I & II n.f.d.Cert n.f.d.Inadequately described L.n.dNot Stated
      Year 12Cert IVCert IIICert III & IV n.f.d.Year 12Year 12Year 12L.n.d.L.n.d.N.S.
      Year 11Cert IVCert IIICert III & IV n.f.d.Year 11Year 11Year 11L.n.d.L.n.d.N.S.
      Senior Sec. Education n.f.dCert IVCert IIICert III & IV n.f.d.Senior Sec. n.f.d.Senior Sec. n.f.d.Senior Sec. n.f.d.L.n.d.L.n.d.N.S.
      Year 10Cert IVCert IIICert III & IV n.f.d.Year 10Year 10Year 10L.n.d.L.n.d.N.S.
      Year 9 and belowCert IVCert IIICert III & IV n.f.d.Cert IICert ICert I & II n.f.d.Cert n.f.d.L.n.d.N.S.
      Sec. Education n.f.dCert IVCert IIICert III & IV n.f.d.L.n.d.L.n.d.L.n.d.L.n.d.L.n.d.N.S.
      Junior Sec. Education n.f.dCert IVCert IIICert III & IV n.f.d.L.n.d.L.n.d.L.n.d.L.n.d.L.n.d.N.S.
      Not statedCert IVCert IIICert III & IV n.f.d.N.S.N.S.N.S.N.S.N.S.N.S.
      Never attended schoolCert IVCert IIICert III & IV n.f.d.Cert IICert ICert I & II n.f.d.Cert n.f.d.L.n.d.N.S.

      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, however the ranking of different levels of attainment has not changed.

      Level of highest non-school qualification

      A person's level of highest non-school qualification is the highest qualification a person has attained in any area of formal study other than school study. It is categorised according to the Australian Standard Classification of Education (ASCED), 2001 Level of education classification.

      In this survey, a respondent's non-school qualifications (up to five qualifications) were ranked by their Level of education ASCED code to determine which was their highest non-school qualification. Where a respondent had more than one non-school qualification at the same level, then the qualification reported first was ranked higher. 
      Note: Not further defined levels were ranked lower than the defined levels eg. Certificate n.f.d. was ranked lower than the defined Certificate levels I-IV. Responses that did not provide sufficient information to be coded to any level, or there was no level information provided were ranked last.

      Migrant

      Migrant refers to any person not born within Australia or the Australian external territories.

      ​​​​​​​Most recent qualification

      In this survey, the most recent qualification was based on the most recent year that the non-school qualification was completed. Where two or more non-school qualifications were completed in the same year, then the higher qualification level is considered to be the most recent. If they were all completed in the same year and were at the same level, then the qualification reported first is considered to be the most recent qualification.

      ​​​​​​​Non-school institution

      Non-school institutions are those which may still provide school level programs but primarily deliver higher education courses, e.g. universities, colleges, institutes of advanced/tertiary/higher education, agricultural colleges and some institutes of technology.

      ​​​​​​​Non-school qualification

      Non-school qualifications are awarded for educational attainments other than those of pre-primary, primary or secondary education. They include qualifications at the Postgraduate Degree level, Master Degree level, Graduate Diploma and Graduate Certificate level, Bachelor Degree level, Advanced Diploma and Diploma level, and Certificates I, II, III and IV levels. School level qualifications obtained through institutions other than primary and secondary schools (such as TAFE) are not included. Non-school qualifications may be attained concurrently with school study. 

      Not in labour force

      People who were not in the categories ‘employed’ or ‘unemployed’. 

      Number of qualifications

      Refers to number of non-school qualifications completed. Detailed information was collected on only up to five of the highest non-school qualifications.

      Occupation

      An occupation is a collection of jobs that are sufficiently similar in their title and tasks, skill level and skill specialisation. Occupation data is classified according to the Australian and New Zealand Standard Classification of Occupations (ANZSCO), 2013, Version 1.2

      Proficiency in spoken English

      Spoken English proficiency as reported by respondent who speaks a language other than English at home.

      Qualification

      Formal certification, issued by a relevant approved body, in recognition that a person has achieved an appropriate level of learning outcomes or competencies relevant to identified individual, professional, industry or community needs. Statements of attainment awarded for partial completion of a course of study at a particular level are excluded.

      Qualification(s) completed before and/or after arrival

      Qualification(s) completed by a migrant before and/or after arrival in Australia are based on the five highest completed qualifications reported. These may have been completed before arrival, after arrival or a combination of both. 

      Qualification(s) completed after arrival

      Out of the five highest qualifications reported, the highest qualification(s) completed by a migrant in any year after their year of arrival in Australia.

      Qualification(s) completed before arrival

      Out of the five highest qualifications reported, the highest qualification(s) completed by a migrant in the same year or any year prior to their year of their arrival in Australia.

      Relevance of qualification to current job

      A qualification was 'relevant' to an employed person's current job or business if they reported: 

      • working in the field of the qualification, or 
      • the qualification was highly relevant, relevant or somewhat relevant to current job or business.
      Most relevant qualification to current job 

      If a person had only one relevant qualification, then that was the 'most relevant'. Where a person had more than one relevant qualification, the most relevant was identified by the respondent from a list of their relevant qualifications.

      Remoteness

      The Australian Statistical Geography Standard (ASGS) was used to define remoteness. The Remoteness Structure is described in detail in the Australian Statistical Geography Standard (ASGS): Volume 5 - Remoteness Structure, July 2016.

      Rest of state/territory

      Skill level

      A function of the range and complexity of the set of tasks involved in an occupation. The greater the range and complexity of the set of tasks, the greater the skill level of the occupation. For more information, see the Occupation Standard, 2018.

      Socio-Economic Indexes for Areas (SEIFA)

      Socio-Economic Indexes for Areas (SEIFA) is an ABS product that ranks areas in Australia according to relative socio-economic advantage and disadvantage. The indexes are based on information from the five-yearly Census of Population and Housing.  The SEIFA indexes used in this publication were created from Census 2016 data. Each index is a summary of a different subset of Census variables and focuses on a different aspect of socio-economic advantage and disadvantage. Each index ranks geographic areas across Australia in terms of their relative socio-economic advantage and disadvantage. It is therefore likely that the same area will have different ranking on each index. 
      The four indexes in SEIFA 2016 are: 

      • Index of Education and Occupation (IEO)
      • Index of Relative Socio-economic Advantage and Disadvantage (IRSAD)
      • Index of Economic Resources (IER)
      • Index of Relative Socio-economic Disadvantage (IRSD)
      • For more information, refer to Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016. 

      For more information, refer to Census of Population and Housing: Socio-Economic Indexes for Areas (SEIFA), Australia, 2016. 

      Underemployed

      Employed people aged 15 years and over who want, and are available for, more hours of work than they currently have. They comprise:

      • people employed part-time who want to work more hours and are available to start work with more hours, either in the reference week or in the four weeks subsequent to the survey; or
      • people employed full-time who worked part-time hours in the reference week for economic reasons (such as being stood down or insufficient work being available). It is assumed that these people wanted to work full-time in the reference week and would have been available to do so.

      Unemployed

      People aged 15 years and over who were not employed during the reference week, and:

      • had actively looked for full-time or part-time work at any time in the four weeks up to the end of the reference week and were available for work in the reference week; or 
      • were waiting to start a new job within four weeks from the end of the reference week and could have started in the reference week if the job had been available then.

      Year 12 or equivalent

      'Year 12 or equivalent' includes overseas qualifications comparable to the Australian Year 12 level of schooling as well as other terms used to describe the final year of schooling in Australia, for example, 'Year 13', '6th Form', 'high school certificate' and 'matriculation'.

      Abbreviations

      Show all

      ABSAustralian Bureau of Statistics
      ANZSCOAustralian and New Zealand Standard Classification of Occupations
      ANZSICAustralian and New Zealand Standard Industrial Classification
      ASCEDAustralian Standard Classification of Education
      ASGSAustralian Statistical Geography Standard
      ASCLAustralian Standard Classification of Languages
      ERPEstimated Resident Population
      GCCSAGreater Capital City Statistical Areas
      ICSindigenous Community Strata
      IEOIndex of Education and Occupation
      IERIndex of Economic Resources
      IRSADIndex of Relative Socio-Economic Advantage and Disadvantage
      IRSDIndex of Relative Socio-Economic Disadvantage
      ISCEDInternational Standard Classification of Education
      LFSLabour Force Survey
      MOEMargin of Error
      MPHSMonthly Population Survey
      n.f.d.not further defined
      NSQnon-school qualification
      Q&WQualifications and Work
      RSERelative Standard Error
      SACCStandard Australian Classification of Countries
      SA1Statistical Area Level 1
      SA4Statistical Area Level 4
      SEStandard Error
      SEIFASocio-economic Indexes for Areas
      SEWSurvey of Education and Work
      TAFETechnical and Further Education
      UNESCOUnited Nations Educational Scientific and Cultural Organisation
      VETVocational Education and Training
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