Barriers and Incentives to Labour Force Participation, Australia methodology

Latest release
Reference period
2022-23 financial year

Introduction

The Barriers and Incentives to Labour Force Participation (B&I) Survey was first conducted during the 2004-05 financial year, as a topic on the Multipurpose Household Survey (MPHS). The MPHS is conducted by the Australian Bureau of Statistics (ABS) as a supplement to the monthly Labour Force Survey (LFS) and is designed to collect statistics for a number of small, self-contained topics.

The Barriers and Incentives to Labour Force Participation survey was initially collected every second financial year from 2004-05 to 2022-23. The survey is now collected every financial year starting 2023-24 and provides a range of information about the people who are not participating, or not participating fully, in the labour force and the factors that influence them to join or leave the labour force.

Additional information about survey design, scope, coverage and population benchmarks relevant to the monthly LFS, which also applies to supplementary surveys, can be found in Labour Force, Australia, Methodology.

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.

Reference period

The reference period for the Barriers and Incentives to Labour Force Participation survey is the 2022-23 financial year.

Quarterly reference periods have also been produced by dividing the full financial year sample into four quarters - September quarter 2022, December quarter 2022, March quarter 2023 and June quarter 2023.

An additional reference period for September quarter 2023 has also been provided from the incomplete 2023-24 financial year survey. Finalised estimates from the 2023-24 financial year survey are scheduled for release on 11 December 2024. 

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.

The following additional exclusions apply to the MPHS:

  • People aged 15-17 years. The MPHS is collected via personal interview and restricted to persons aged 18 years and over. 
  • Very remote parts of Australia and Aboriginal and Torres Strait Islander communities.
  • People living in non-private households such as hotels, university residences, students at boarding schools, patients in hospitals, inmates of prisons and residents of other institutions (e.g. retirement homes, homes for people with disabilities).

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

Collection method

The Barriers and Incentives to Labour Force Participation topic is collected within the Multi-Purpose Household Survey (MPHS), a supplement to the monthly Labour Force Survey (LFS).

Each month, a sample of households are selected for the MPHS from the responding households who are in the last of their 8 months in the LFS. In these households, after the LFS had been fully completed for each person, a usual resident aged 18 years and over is selected at random to complete the questionnaire.

Data are collected via personal interviews by either telephone or in person at selected households.

For more details, see the MPHS chapter in Labour Statistics: Concepts, Sources and Methods.

Questionnaire

Sample Design

This survey is based on the new sample introduced into LFS in July 2018. The new sample design has adopted the use of the Address Register as the sampling frame for unit selection, and the sampling fractions for selection probabilities within each state have been updated to reflect the most recent population distribution based on results from the 2016 Census of Population and Housing. As with each regular sample design, the impacts on the data are expected to be minimal. For more information, see the Information Paper: Labour Force Survey Sample Design.

Sample Size

The sample is pooled from data collected each month across the whole financial year. In January 2023, the ABS increased the sample selections for the remaining 6 months of the year. The total sample size of the 2022-23 B&I survey (after taking into account the scope, coverage and sub-sampling exclusions) was approximately 18,000.

Weighting and estimation

Population benchmarks

Survey weights are calibrated against population benchmarks to ensure that the survey estimates conform to the independently estimated distribution of the population, rather than the distribution within the sample itself.

When calibrating the weights, the survey sample is grouped into categories based on the following characteristics:

  • State or territory.
  • Capital city or rest of state.
  • Sex.
  • Age.
  • Employed full-time, part-time, unemployed or not in the labour force.

The Labour Force Survey estimates are calculated in such a way as to sum to the independent estimates of the civilian population aged 15 years and over (population benchmarks). These population benchmarks are updated quarterly based on Estimated Resident Population (ERP) data. See Labour Force, Australia, Methodology for more information.

From August 2015, Labour Force estimates have been compiled using population benchmarks based on the most recently available release of ERP data, continually revised on a quarterly basis.

The B&I benchmarks were based on a 12-month average of the LFS estimates for the June to July financial year, as reported in the November 2023 issue of Labour Force, Australia. This approach is used to remove the seasonality from the employed, unemployed and not in the labour force benchmarks and to improve coherence between the two publications.

Estimates from previous surveys back to 2014-15 have also been revised using this method, with benchmarks based on the same population series (as at November 2023). These estimates were calibrated to population benchmarks based on the final rebasing of ERP that incorporated the results of the 2021 Census (introduced to LFS in the November 2023 issue).

Quarterly benchmarks

The benchmarks for quarterly estimation were based on the same method as for the full financial year sample, using the corresponding 3-month average of the LFS estimates for each quarter. This shorter time period does not account for seasonality in the same way as using a 12-month average, so it is expected that some seasonality remains in the estimates. 

The weights for the reduced quarterly sample were calibrated based on grouping the sample using broader characteristics than the full financial year sample, notably excluding State and territory from the calibration. This means that State and territory estimates are not available on a quarterly basis.

The LFS estimates used in benchmarking the quarterly estimates were also taken from the November 2023 issue of Labour Force, Australia.

Comparability with LFS

Due to differences in the scope and sample size of this MPHS and that of the monthly LFS, the estimates procedure may lead to some small variations between labour force estimates from this survey and those from the LFS.

Survey output

A number of spreadsheets are available from Data downloads. They present tables of estimates and their corresponding relative standard errors (RSEs).

For users who wish to undertake more detailed analysis, the underlying microdata is available in DataLab and TableBuilder. For more details, refer to Microdata and TableBuilder: Barriers and Incentives to Labour Force Participation.

Survey content

The survey is designed to provide a large range of statistics on labour market dynamics across the following conceptual groups:

  • Geography.
  • Demographics.
  • Cultural diversity.
  • Families and Children.
  • Education and Qualifications.
  • Health and Disability.
  • Unpaid work and care.
  • Participation and Underemployment.
  • Characteristics of employment.
  • Characteristics of main job.
  • Characteristics of last job.
  • Income and Housing.
  • Partner's participation and income.
  • Wanting to work or more hours.
  • Available for work or more hours.
  • Looking for work or more hours.
  • Difficulties finding work.
  • Barriers to participation.
  • Incentives to participate.
  • Populations of interest.

For more details, refer to the Data item list.

Data item list

Conceptual framework

To understand potential barriers to increased participation in the labour force, there are three groups who are of particular interest:

  • unemployed.
  • persons not in the labour force.
  • employed persons who usually worked less than 35 hours.

These groups can be further broken down into:

  • those who wanted a paid job or would prefer to work more hours.
  • those who were available (either in the previous week or within four weeks) to start a job or work more hours.
  • those who were looking (actively or passively) for a paid job or more hours. 

This conceptual framework is represented diagrammatically in the 2018-19 issue of Barriers and Incentives to Labour Force Participation.

In 2020-21, the conceptual framework was revised to include the concept of job attachment, where there is a group of people who are not classified as employed but have a job that they about to start or can return to when available. This is consistent with the approach used in Participation, Job Search and Mobility.

In general, people who have a job to start or return to are excluded from populations of interest:

  • The unemployed population of interest is now "Unemployed looking for work" where people who had already obtained a job and are waiting to start are excluded from the population (also known as future starters).
  • The persons not in the labour force population of interest now excludes people who had a job to start or return to. This includes people who had obtained a job and were waiting to start, and also people who were away from work without pay for four weeks or longer and were not classified as employed or unemployed. 

It is also worth noting that in cases where people who were reported as "permanently unable to work" in the LFS, but later indicated that they wanted a paid job during the personal interview of the MPHS, that these people are classified as potential supply in the population "PNILF who wanted a paid job." People who were permanently unable to work and who did not want a paid job are not classified as potential supply and are usually excluded from estimates (unless otherwise stated).

Another group that is usually excluded from estimates are those who are "permanently retired." From March 2023, this group is defined as anyone who is not in the labour force, did not want a paid job, and responded that they were "Permanently retired, will not work full-time again" when asked for "all reasons for not wanting to work". Prior to March 2023, only those who responded with that reason as their "main reason for not wanting to work" were defined as "permanently retired." This change in definition has been backcast to 2014-15. 

What is a barrier?

Barriers are any conditions or characteristics that may make employment difficult.  When out of work, barriers can make finding work difficult, and when employed, barriers can hinder the ability to increase participation by working more hours. Some examples of barriers to labour force participation include:

  • Caring for children.
  • Caring for people who were ill, with disability or were elderly
  • Long-term health conditions, disability or old age.
  • Low levels of education, training or experience.
  • Cultural background or language difficulties.

It is not necessary to want to work in order to be affected by a barrier to participation, as barriers can prevent or discourage people from wanting to work. It should also be noted that barriers can exist regardless of economic conditions, but may make some more or less challenging.

The ABS identifies certain barriers to participation by collating the different reasons why people are not working or not working more hours. These are based on the following questions asked in the survey:

  • Reasons why not wanting to work or work more hours.
  • Reasons why not available to work or work more hours.
  • Reasons why not looking for work or more hours.
  • Difficulties finding work or more hours.
  • Reasons why left or lost last job.

For example, when 'Caring for children' is reported as a barrier to participation, it could be because caring for children was given as a reason for not wanting to work, or as a reason why not available for work, or as a reason why not looking for work. All these responses are collated together to provide estimates for all of the people that are affected by this barrier. 

Using this approach, the results of the survey can be grouped to arrange the barriers thematically, around people’s common responses and shared experience, rather than the specific questions and the answers to those questions.

Furthermore, each question asked in the survey acts like a gateway to the next question. If someone responds that they do not want to work, they do not get asked questions about looking for work or difficulties finding work. Respondents are only asked questions that are relevant to them, so they aren't able to identify with barriers that are exclusive to questions later in the survey that are not relevant to them. For example, only people who are available and looking for work can identify "No jobs in locality, line of work or problems with access to transport” as a barrier. People who do not want to work are not asked about this barrier, even though it might be a factor in their response to not wanting to work. This tailoring of questions means that information on some barriers is limited to particular groups of people, based on their participation in the labour market, rather than covering the entire population.

Accuracy and quality

Reliability of estimates

As the estimates are based on information obtained from occupants of a sample of households, they are subject to sampling variability. That is, they may differ from those estimates that would have been produced if all households had been included in the survey or a different sample was selected. Two types of error are possible in an estimate based on a sample survey - sampling error and non-sampling error.

  • sampling error is the difference between the published estimate and the value that would have been produced if all dwellings had been included in the survey.
  • non-sampling errors are inaccuracies that occur because of imperfections in reporting by respondents and interviewers, and errors made in coding and processing data. These inaccuracies may occur in any enumeration, whether it be a full count or a sample. Every effort is made to reduce the non-sampling error to a minimum by careful design of questionnaires, intensive training and effective processing procedures.

Some of the estimates contained in the tables have a relative standard error (RSE) of 50 per cent or greater. These estimates are marked as unreliable for general use. Estimates with an RSE of between 25 and 50 per cent are also marked and should be used with caution.

More on reliability of estimates

Rounding

As estimates have been rounded, discrepancies may occur between sums of the component items and totals.

Glossary

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History of changes

December quarter 2023

  • Quarterly estimates published for December quarter 2023.
  • Financial year Table 12 estimates rebenchmarked to November 2023 Labour Force Survey. These revisions incorporate the final rebasing of ERP to the results of the 2021 Census.
  • An issue was detected in the 2023-24 collection which resulted in incomplete incentives data for people who did not want to work. This issue only relates to 2023-24 data and does not affect other data for this population group or data for other groups.  For the December quarter 2023, this issue has been addressed using imputation based on December quarter 2022 data. The ABS will review this imputation approach when December quarter 2024 data becomes available.
  • Microdata in DataLab was updated to include the revised estimates and the new data for the December quarter 2023. Refer to Microdata and TableBuilder: Barriers and Incentives to Labour Force Participation for more information.

September quarter 2023

  • Quarterly estimates published for September quarter 2023.
  • An issue was detected in the 2023-24 collection which resulted in incomplete incentives data for people who did not want to work. This issue only relates to 2023-24 data and does not affect other data for this population group or data for other groups.  For the September quarter 2023, this issue has been addressed using imputation based on September quarter 2022 data. The ABS will review this imputation approach when September quarter 2024 data becomes available.
  • Estimates rebenchmarked to November 2023 Labour Force Survey (both financial year and quarterly estimates). These revisions incorporate the final rebasing of ERP to the results of the 2021 Census.
  • Microdata in DataLab was updated to include the revised estimates and the new data for the September quarter 2023. Refer to Microdata and TableBuilder: Barriers and Incentives to Labour Force Participation for more information.
  • Tables have been updated to include the option to select Main reason or All reasons where applicable (for example, 'main reason not looking for work' or 'all reasons not looking for work').
  • Previously missing family relationship items 'Family composition of household', 'Social marital status' and 'Relationship in household' were re-instated for the 2014-15 and 2016-17 financial years. 
  • New populations of interest were added: 'People without children aged 0 - 14 years', 'People on any government pension or allowance', 'Areas of socio-economic disadvantage', and 'Part-time casual workers'.
  • References to the outdated term 'sickness' have been replaced with 'short-term illness' or 'long-term health condition'. 

Financial year 2022-23

June quarter 2023

  • Quarterly estimates published for June quarter 2023.
  • First release of data for 'People with disability'. Whether a person has disability has been derived from a subset of questions from the ABS Short Disability Module. These questions are not designed to estimate prevalence but rather allow for the broad comparison of the characteristics of people with and without disability. For more information, refer to the Glossary.
  • Quarterly estimates rebenchmarked to August 2023 Labour Force Survey estimates.
  • Updates to the financial year tables and microdata in DataLab are scheduled for 27 November 2023. 

March quarter 2023

  • Quarterly estimates published for March quarter 2023.
  • Revisions to estimates from 2014-15 onwards:
    • Rebenchmarking to April 2023 Labour Force Survey estimates.
    • Manual recoding of the text provided as "other reasons" for the items related to "Reasons not looking for work or more hours" and "Difficulties finding work or more hours."
    • Scope of "permanently retired" expanded to include all people not in the labour force who did not want a paid job and who provided the reason "Permanently retired, will not work full-time again" when asked why they did not want to work. Previously, only those who provided that reason as the main reason were defined as permanently retired.
  • New financial year tables in Data downloads, which contain the latest revised estimates and better consistency with the Quarterly measures tables. These new tables also include 'Populations of interest' in more tables, such as 'People with a long-term health condition.'
  • Minor changes to the Quarterly measures tables to improve consistency between the tables by using the same population scope - People aged 18-75 years, excluding:
    • permanently retired (new definition, as mentioned above),
    • permanently unable to work (who did not want a paid job), and
    • people who had a job to start or return to.
  • Table Q2 now has additional summary details related to caring for children and other barriers to participation.

December quarter 2022

  • Quarterly estimates published for the first time, from September quarter 2014 to December quarter 2022.
  • New Tables Q1 to Q7 in Data downloads with summary tables of quarterly measures.
  • Estimates were benchmarked to a 3-month average of population estimates from the Labour Force Survey (as at January 2023).

Financial year 2020-21

  • Improvements have been made to the way data is presented. Adjustments were made to the conceptual framework to include a separate category for people who had a job to start or return to, which is consistent with the approach used in Participation, Job Search and Mobility. Data have been revised back to 2014-15 to incorporate these changes.
  • The Excel spreadsheets in Data downloads have been redesigned to incorporate timeseries data back to 2014-15, with optional state and territory breakdowns.
  • Estimates were rebenchmarked to a 12-month average of population estimates from the Labour Force Survey (as at May 2020).

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