Barriers and Incentives to Labour Force Participation, Australia methodology

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Reference period
2020-21 financial year
Released
4/11/2022

Introduction

The two-yearly Barriers and Incentives to Labour Force Participation (B&I) Survey was first conducted in 2004-05, 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 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 2020-21 financial year.

Quarterly reference periods have also been produced by dividing the full financial year sample into four quarters - September quarter 2020, December quarter 2020, March quarter 2021 and June quarter 2021.

Additional reference periods for September quarter 2022, December quarter 2022, March quarter 2023, and June quarter 2023 have also been provided from the 2022-23 financial year survey. Finalised estimates from the 2022-23 financial year survey are scheduled for release on 27 November 2023. 

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. The sample size of the 2020-21 B&I survey (after taking into account the scope, coverage and sub-sampling exclusions) was approximately 13,000.

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 April 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 April 2023). These estimates were calibrated to population benchmarks based on revisions to ERP that incorporated the results of the 2021 Census (introduced to LFS in the November 2022 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 August 2023 issue of Labour Force, Australia.

Microdata in DataLab

The financial year and quarterly weights (and replicate weights used for calculating relative standard errors) provided on the most recent B&I microdata file in ABS DataLab have both been based on benchmarks using the 12-month and 3-month averages of the LFS estimates as reported in the April 2023 issue of Labour Force, Australia. Both sets of weights back to the 2014-15 financial year and September 2014 quarter have been aligned to include the revisions to ERP that incorporate the results of the 2021 Census.

Microdata for June quarter 2023 and the complete 2022-23 financial year are not yet available in the B&I microdata file in ABS DataLab and are scheduled for release on 27 November 2023. 

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."

Another group that is often excluded from populations of interest 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. 

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

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.
  • Microdata in DataLab was updated to include the revised estimates and the new data for reference period March quarter 2023. Refer to Microdata and TableBuilder: Barriers and Incentives to Labour Force Participation for more information.

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).
  • Microdata in DataLab was updated to include new quarterly weights and new data for reference periods September quarter 2022 and December quarter 2022. Refer to Microdata and TableBuilder: Barriers and Incentives to Labour Force Participation for more information.

Financial year 2020-21

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