Labour Force, Australia methodology

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Reference period
March 2024
Released
18/04/2024

Introduction

The monthly Labour Force Survey (LFS) provides information about the labour market activity of Australia's resident civilian population aged 15 years and over. The LFS is designed to primarily provide estimates of employment and unemployment for the whole of Australia and, secondarily, for each state and territory. The ABS has been conducting the Labour Force Survey since 1960, initially as a quarterly survey. In February 1978, the frequency of the survey was changed from quarterly to monthly.

Statistics from the monthly Labour Force Survey are released in two stages:

  • The initial release is Labour Force, Australia, which includes headline estimates of employment, unemployment, underemployment, participation and hours worked for Australia, and the states and territories.
  • The second release is Labour Force, Australia, Detailed, which includes more detailed monthly and quarterly data.

The conceptual framework used in Australia’s Labour Force Survey aligns closely with the standards and guidelines set out in Resolutions of International Conferences of Labour Statisticians. Descriptions of the underlying concepts and structure of Australia's labour force statistics, and the sources and methods used in compiling the estimates, are presented in Labour Statistics: Concepts, Sources and Methods.

Scope and coverage

The scope of the LFS is the civilian population aged 15 years and over, excluding:

  • Members of the permanent defence forces
  • Certain diplomatic personnel of overseas governments
  • Overseas residents in Australia
  • Members of non-Australian defence forces (and their dependants) stationed in Australia

Coverage rules are applied to ensure that each person is associated with only one dwelling, and has only one chance of selection. The coverage rules are necessarily a balance between theoretical and operational considerations. The chance of a person being counted at two separate dwellings is considered to be insignificant.

Collection method

The LFS is based on a multi-stage area sample of:

  • private dwellings;
  • discrete Aboriginal and Torres Strait Islander communities; and
  • non-private dwellings (i.e. hotels, motels, hospitals, retirement villages, etc.).

Households within selected dwellings are interviewed each month for eight months, with one-eighth of the sample being replaced each month. Information is obtained either by trained interviewers or through self-completion online. Generally, the first interview is completed face-to-face and subsequent interviews conducted by phone. All respondents in the sample are also offered the option of completing the survey online.

The interviews are generally conducted during the two weeks beginning on the Sunday between the 5th and 11th of each month. The information obtained relates to the week before the interview (i.e. the reference week). Occasionally, circumstances that present significant operational difficulties for survey collection can result in a change to the normal pattern for the start of interviewing.

Each year, to deal with the operational difficulties involved with collecting and processing the Labour Force Survey around the Christmas and New Year holiday period, interviews for December start four weeks after November interviews start (i.e. between the 3rd and 9th December), and January interviews start five weeks after December interviews start. As a result, January interviewing may commence as early as the 7th or as late as the 13th, depending on the year.

The questionnaire used in the LFS for face-to-face or phone interviews is below. An online version of this questionnaire is also used for respondents self-completing the survey on the ABS website.

Labour Force Survey questionnaire

Changes to the LFS questionnaire were implemented in July 2022. For details of the changes, please refer to History of changes in this page.

The retired LFS questionnaire (July 2014 – June 2022) is accessible via the methodology page in the June 2022 release.

Previous versions of the LFS questionnaire can be found in Questionnaires used in the Labour Force Survey.

Other survey forms may be used in special circumstances. A paper self-completion form may be used where it is not possible for an interview to take place — for instance, where contact cannot be made with the occupants of selected dwellings or when a respondent refuses to be interviewed but will complete a form.

A customised form is also used for Aboriginal and Torres Strait Islander peoples living in sparsely settled areas and Aboriginal and Torres Strait Islander communities when interviewers encounter significant cultural and language difficulties, or when other operational difficulties occur such as the availability of suitably trained and skilled interviewers.

Method for modelling SA4 level regional estimates

Modelled SA4 estimates are produced using a Rao-Yu time-series model. This model uses a real-world relationship between the administrative data and the survey estimates that is observed across SA4s. The model also makes use of the correlation of labour force status within SA4s and over time. The administrative data sources used include de-identified Single Touch Payroll data from the Australian Taxation Office and Youth Allowance and JobSeeker data from the Department of Social Services.

Detailed methodology on the model is available in the Methodology Advisory Committee paper A Rao-Yu model for small area estimation of labour force statistics. Advice on using regional estimates, including the modelled labour force survey estimates, is available in the Regional labour market data guide.

Sample design

Sample size

The sample size of the LFS is approximately 24,000 dwellings resulting in a sample of approximately 50,000 people.

Sample frame and selection

The ABS Address Register is used as the sampling frame for unit selection, and state sampling fractions for selection probabilities within each state and territory. 

Use of the Address Register as the sampling frame forms a three stage selection process where field officers do not have to visit base frame units to compile dwelling lists – enhancing the efficiency of data collection and effectiveness of sample selected.

The sample frame for the Labour Force Survey (LFS) is refreshed at regular intervals to ensure it accurately reflects the location of Australian residences.

A refreshed sample will be phased in between September 2023 and April 2024, with each incoming rotation group selected from the Address Register. This replaces the previous sample frame from July 2018.

Use of the ABS Address Register

State sampling fractions

Sample rotation

The sample can be thought of as comprising eight sub-samples (or rotation groups), with each sub-sample remaining in the survey for eight months. A new rotation group is introduced each month to replace an outgoing rotation group. This replacement sample generally comes from the same geographic area as the outgoing one.

Sample rotation enables reliable measures of monthly change in labour force statistics to be compiled, as seven-eighths of the sample from any month is retained for the following month. At the same time, the sample rotation procedure ensures that no household is retained in the sample for more than eight months, and that the sample reflects changes over time in the household population (such as construction of new households).

Sample design changes in response to COVID-19

Response rates

The LFS receives a high level of co-operation from individuals in selected dwellings. For the duration of the COVID-19 pandemic, due to the suspension of face to face interviews in late April 2020, the ABS had moved to a level target of response. The target response was 24,183 fully responding households. This level was achieved in March 2024.

Weighting and estimation

Population benchmarks

The LFS estimates are calculated so they add to independent estimates of the civilian population aged 15 years and over (population benchmarks) based on the most recently released estimates of final, revised and preliminary quarterly Estimated Resident Population (ERP). For information on the methodology used to produce the ERP, see National, State and Territory Population.

Since the most recently released ERP estimates lag the labour force estimates by nine months, the labour force population benchmarks are created by projecting forward three quarters past the most recently released quarterly ERP estimates. The projection is based on the historical pattern of each population component - births, deaths, interstate migration and net overseas migration (NOM). Estimates of NOM are supplemented with other data sources to better reflect short-term population changes. These estimates draw on information provided by the Department of Home Affairs.

As the population benchmarks are revised on a quarterly basis this results in revisions to hours worked estimates with the updated population benchmarks.

Every July, post June publication, an additional Hours Worked rebenchmarking updates the annual hours worked benchmark for the past financial year. Seasonal factors of hours worked estimates are also reviewed and updated.

Revisions to population benchmarks and rebenchmarking of LFS

Estimation method

The LFS uses a composite estimation method. Composite estimation combines the data collected in the previous six months with the current month's data to produce the current month's estimates. This takes advantage of the high correlation between overlapping samples across months in the survey. After composite estimation methods have been applied, the seven months of data are weighted to align with the current month population benchmarks. For details see Information Paper: Forthcoming Changes to Labour Force Statistics, 2007.

Seasonal adjustment and trend estimation

The key estimates from the Labour Force Survey are available as original, seasonally adjusted and trend series.

Any original time series can be thought of as a combination of three broad and distinctly different types of behaviour, each representing the impact of certain types of real world events on the information being collected:

  • systematic calendar related events;
  • short-term irregular fluctuations; and
  • long-term cyclical behaviour.

Seasonal adjustment is a statistical technique that attempts to measure and remove the effects of systematic calendar related patterns (i.e. which happen at the same time every year) including seasonal variation to reveal how a series changes from period to period, so other influences on the series can be more clearly recognised. Seasonal adjustment does not aim to remove the short-term or irregular influences which may be present. Influences that are volatile or unsystematic can still make it difficult to interpret the movement of the series even after adjustment for seasonal variation, and therefore month-to-month movements of seasonally adjusted estimates may not be reliable indicators of trend behaviour.

Seasonally adjusted estimates can be smoothed to reduce the impact of irregular or non-seasonal influences. Smoothed seasonally adjusted series are called trend estimates. The ABS considers that trend estimates provide a more reliable guide to the underlying direction of the data, and are more suitable than either the seasonally adjusted or original estimates for most business decisions and policy advice.

For more information about time series analysis see Time Series Analysis FAQ.

Impacts of COVID-19

ABS suspended the publication of Labour Force Trend estimates in April 2020, due to the large changes in the labour market during the COVID-19 period, particularly during the first two years of the pandemic (April 2020 to March 2022).

As suggested in A Guide to Interpreting Time Series, trend estimates are generally a better guide to the substantive movements in the series, and are considered the best indicator of the underlying behaviour in the labour market.

Given this, following extensive analysis of the time series, in September 2022 the ABS reinstated Labour Force Trend estimates and reverted back to using the concurrent seasonal adjustment method (rather than using forward factors).

The ABS has also included the trend during the COVID period in the spreadsheets from the Labour Force, Australia, October 2022 release onwards. However, given the large month-to-month changes during the first two years of the COVID-19 pandemic, resulting in multiple trend breaks, the ABS recommends caution when using trend estimates during this period.

The ABS further reviewed the trend breaks identified during the COVID-19 period as part of the 2023 Annual Seasonal Review.  As a result, some series have had trend breaks added or removed. The list of trend breaks included in this release has been updated to reflect these changes.

With the temporary suspension of trend during the pandemic, seasonally adjusted estimates have been published in Labour Force, Australia for the Northern Territory and the Australian Capital Territory (tables 10a, 11a, 12a, 19a and 23a). Caution should continue to be exercised when using seasonally adjusted estimates for the two territories. The ABS expects to cease publishing these temporary tables in 2024.

A list of all trend breaks between April 2020 and March 2022 can be found in 'Trend breaks by publication table, April 2020 to March 2022’.

Trend breaks by publication table, April 2020 to March 2022

Seasonal adjustment techniques

Survey output

Release strategy and frequency

Statistics from the monthly Labour Force Survey are released in two stages:

  • The initial release is Labour Force, Australia, which includes headline estimates of employment, unemployment, underemployment, participation and hours worked for Australia, and the states and territories. This is usually published 39 days after the beginning of interviews for that month, which is usually the third Thursday of the month following the reference month (e.g. estimates for June are published on the third Thursday in July). The exception is December, where estimates are published 46 days after.
  • The second release is Labour Force, Australia, Detailed, which includes more detailed monthly and quarterly data. The quarterly detailed data was previously published separately, in Labour Force, Australia, Detailed, Quarterly. The second release occurs 7 days after the first release (i.e. usually the fourth Thursday of the month).

Detailed longitudinal LFS microdata are also available in Microdata: Longitudinal Labour Force, Australia accessed via the ABS DataLab. This longitudinal file contains data from each monthly Labour Force Survey, along with data collected from labour supplementary surveys and multipurpose household surveys from October 1982 onwards. It includes a range of data to enable users to better understand the dynamics of the labour market and transitions between employment, unemployment and not in the labour force, by enabling analysis of how the labour force status and other characteristics of respondents changes for each of the 8 months they are in the LFS.

In addition:

Survey content

The LFS includes monthly information on:

  • Labour force status - Employed, Unemployed, Not in the labour force;
  • For people in the labour force - Unemployment rate, Underemployment rate, Participation rate, flows into and out of employment (Gross flows);
  • For employed people - Status in employment, full-time or part-time status, hours actually worked, hours usually worked, total monthly hours worked, duration of employment, expectations of future employment, underemployment, reason for working fewer hours than usual in the reference week;
  • For unemployed people - Whether looked for full-time and/or part-time work, duration of job search, and whether active steps taken to find work;
  • For people not in the labour force - Reason not in the labour force, whether looking for work;
  • Socio-demographic information - Sex, age, social marital status, relationship in household, family type, participation in school and tertiary education, highest year of school completed, level of highest educational attainment, birthplace and year of arrival in Australia; and
  • Geography/Region (of usual residence) - State or Territory, Capital City / Balance of State, and Labour Force Regions (Statistical Area Level 4 (SA4)). See Advice on reporting regional labour force data.

Quarterly information is available on:

  • For people in the labour force - Hours-based measures of underutilisation, and retrenchments in the previous quarter;
  • For employed people - occupation, industry, sector (public/private), and whether casual (i.e. employee without paid leave entitlements);
  • For unemployed people - Whether looked for full-time and/or part-time work, reason for ceasing last job, and industry and occupation of last job;
  • For people not in the labour force - Retrenchments in the previous quarter.

Seasonally adjusted and trend data are available for selected series, including labour force status, unemployment, participation rate, industry, and long term unemployed.

For information on the concepts and data items available from the LFS, see Labour Force Survey Standard Products and Data Item Guide.

Reliability of estimates

Two types of error are possible in an estimate based on a sample survey: sampling error and non-sampling error.

Non-sampling error arises from inaccuracies in collecting, recording and processing the data. Every effort is made to minimise reporting error by the careful design of questionnaires, intensive training and supervision of interviewers, and efficient data processing procedures. Non-sampling error also arises because information cannot be obtained from all persons selected in the survey.

Sampling error occurs because a sample, rather than the entire population, is surveyed. The most commonly used measure of the likely difference resulting from not including all households in the survey is given by the standard error. There are about two chances in three that a sample estimate will differ by less than one standard error from the figure that would have been obtained if all dwellings had been included in the survey, and about nineteen chances in twenty that the difference will be less than two standard errors.

Table 1 shows the movements in seasonally adjusted series, and the corresponding confidence intervals for these movements.

Table 1: Confidence intervals for seasonally adjusted movements between February 2024 and March 2024
Monthly change95% Confidence interval
Total Employment-6,600-71,600 to 58,400
Total Unemployment20,600-13,600 to 54,800
Unemployment rate0.1 pts-0.1 pts to 0.3 pts
Participation rate-0.1 pts-0.3 pts to 0.1 pts

Standard errors

Data files

How to interpret standard errors on levels and movements

 

The standard errors for all labour force estimates and movements can be calculated using the following spreadsheet.

Estimating standard errors of Labour Force data

Standards and classifications

The labour force characteristics of the population are measured and described through a group of variables. The core labour force variables are:

  • Labour force status
  • Status in employment
  • Hours worked
  • Full-time/part-time status
  • Duration of job search

The standards for these variables, including the concept(s), definition(s), classification, coding structure, questionnaire modules and output, are in Standards for Labour Force Statistics.

Other standards and classifications used in the LFS are outlined in Labour Statistics: Concepts, Sources and Methods.

Labour Force statistics insights from the 2021 ANZSCO update

Glossary

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History of changes

The ABS has been conducting the Labour Force Survey since 1960, initially as a quarterly survey. In February 1978, the frequency of the survey was changed from quarterly to monthly. While seeking to provide a high degree of consistency and comparability over time by minimising changes to the survey, sound survey practice requires careful and continuing maintenance and development to maintain the integrity of the data and the efficiency of the collection.

The changes which have been made to the LFS have included changes in sampling methods, estimation methods, concepts, data item definitions, classifications, and time series analysis techniques. In introducing these changes the ABS has generally revised previous estimates to ensure consistency and coherence with current estimates.

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