Microdata and TableBuilder: Participation, Job Search and Mobility, Australia

Enables detailed analysis of labour market participation

PJSM microdata in DataLab

Participation, Job Search and Mobility (PJSM) microdata is now available in ABS DataLab, released as a supplementary file for the Longitudinal Labour Force (LLFS) microdata. All existing users of the LLFS microdata will automatically get access to the PJSM file and new users can apply for access to both files. 

On May 27 2022, an updated file of PJSM microdata with annual data for the years ending February 2015 to February 2022 will be released into DataLab. This will replace the first release of PJSM microdata released on May 6 2022, which featured annual data up to the year ending February 2021.

A detailed data item list for the PJSM microdata is available in Data downloads.

PJSM microdata in TableBuilder

The release of February 2022 PJSM microdata into TableBuilder has been delayed until later in the year in order to prepare for the release of 2021 Census data in TableBuilder. The previous release with data for the years ending February 2015 to February 2021 will remain available during this time. 

Introduction

This product provides a range of information about the release of microdata relating to people looking for work, finding work, losing jobs, changing jobs, or the reasons why people are not working or looking for work.

Microdata are the most detailed information available from a survey and are generally the responses to individual questions on the questionnaire or data derived from two or more questions.

Participation, Job Search and Mobility, 2015 to 2022

The Participation, Job Search and Mobility survey (PJSM) is conducted in February throughout Australia and is designed to provide statistics on labour market dynamics across the following 17 concepts:

  • Available for work or more hours
  • Away from work
  • Barriers to participation
  • Changes in current job over last 12 months
  • Characteristics of current main job
  • Characteristics of employment
  • Characteristics of job 12 months ago
  • Characteristics of last job
  • Demographic
  • Difficulties in finding work
  • Education
  • Families and children
  • Job offers
  • Looking for work or more hours
  • Participation and Underemployment
  • Retrenchment and lost jobs
  • Wanting to work or more hours

Microdata from the PJSM survey is released in both TableBuilder and DataLab.

TableBuilder is an online tool for creating tables and graphs from underlying microdata. Refer to TableBuilder for more information.

DataLab is the analysis solution for high-end users who want to undertake real time complex analysis of detailed microdata in a secure environment. Refer to DataLab for more information.

Accessing the data

You can use this data in:

  • TableBuilder - online tool for creating tables and graphs.
  • DataLab - analyse detailed microdata

Compare data services to see what's right for you. Information on how to apply for access can be found in TableBuilder and DataLab.

Further information about these products, and other information to assist users in understanding and accessing microdata in general, is available from the Microdata and TableBuilder Entry Page.

Further information

Further information about the survey and the microdata can be found in the various pages associated with this product, including:

Support

For further support in the use of this product, please contact Microdata Access Strategies via email at microdata.access@abs.gov.au.

Data available on request

Data collected in the survey but not included in TableBuilder or DataLab may be available from the ABS, on request, as statistics in tabulated form.

Subject to confidentiality and sampling variability constraints, special tabulations can be produced incorporating data items, populations and geographic areas selected to meet individual requirements. These are available, on request, on a fee for service basis. For more information, contact the ABS by visiting www.abs.gov.au/about/contact-us or email the Labour Statistics Branch at labour.statistics@abs.gov.au.

Privacy

The ABS Privacy Policy outlines how the ABS handles any personal information that you provide to us.

Data and file structure

Survey methodology

General information about the Participation, Job Search and Mobility (PJSM) survey, including summary results, are available in the following publications 

Detailed information about the survey including scope and coverage, survey design, data collection methodology, weighting, estimation and benchmarking, estimate reliability and a glossary can be accessed from the Methodology page of the publication.

Data items

The data items included in the PJSM TableBuilder are grouped under broad headings and subheadings as shown in the image below. A complete data items list can be found in Data downloads.

Data items

File structure

The underlying format of the PJSM TableBuilder file is structured at a single person level. This person level contains general demographic information such as age, sex and country of birth as well details about underemployed workers, persons not in the labour force, unemployed persons and educational qualifications.

When tabulating data from TableBuilder, person weights are automatically applied to the underlying sample counts to provide the survey's population estimates.

Reference year

The PJSM TableBuilder contains a mandatory field called Reference year to allow for historical analysis. By default this field will be present in any new table as per the image below:

Reference years

Individual years can be removed from the table using the data item panel by selecting the required year and removing it from the table as per the image below:

Data item panel

However, at least one category (reference year) of the mandatory field must be present in a table for TableBuilder to retrieve data.

Not applicable categories

Most data items included in the TableBuilder file include a 'Not applicable' category. This category generally represents the number of people who were not asked a particular question or the number of people excluded from the population for a data item when that data were derived (e.g. Hours usually worked in main job is not applicable for unemployed persons or persons not in the labour force).

From 2021, The "Not applicable" categories in each item now have a descriptive label to describe which populations are not included for the data item. For example, in the data item “Main difficulty in finding work,” the “Not applicable” category has been labelled as “Did not look for work” to indicate that only people who looked for work were asked about any difficulties in finding work.

Table populations

The population relevant to each data item should be kept in mind when extracting and analysing data. The actual population count for each data item is equal to the total cumulative frequency minus the 'Not applicable' category.

Generally, some populations can be 'filtered' using other relevant data items. For example, if the population of interest is 'Employed', any data item with that population (excluding the 'Not applicable' category) could be used.

Zero value cells

Tables generated from sample surveys will sometimes contain cells with zero values because no respondents that satisfied the parameters of a particular cell in a table were in the survey. This is despite there being people in the general population with those characteristics. This is an example of sampling variability which occurs with all sample surveys. Relative standard errors cannot be generated for zero cells.

Using TableBuilder

For general information relating to the TableBuilder or instructions on how to use features of the TableBuilder product, please refer to TableBuilder and the TableBuilder, User Guide.

More specific information applicable to the Participation, Job Search and Mobility (PJSM) survey TableBuilder, which should enable users to understand, interpret and tabulate the data, is outlined below.

Confidentiality features in TableBuilder

In accordance with the Census and Statistics Act 1905, all the data in TableBuilder are subjected to a confidentiality process before release. This confidentiality process is undertaken to avoid releasing information that may allow the identification of particular individuals, families, households, dwellings or businesses.

Processes used in TableBuilder to confidentialise records include the following: 

  • perturbation of data; and
  • table suppression

Perturbation effects

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 small random adjustments 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.

The introduction of these random adjustments result in tables not adding up. As a result, randomly adjusted individual cells will be consistent across tables, but the totals in any table will not be the sum of the individual cell values. The size of the difference between summed cells and the relevant total will generally be very small.

Please be aware that the effects of perturbing the data may result in components being larger than their totals. This includes determining proportions.

Table suppression

Some tables generated within TableBuilder may contain a substantial proportion of very low counts within cells (excluding cells that have counts of zero). When this occurs, all values within the table are suppressed in order to preserve confidentiality. The following error message below is displayed (in red) at the bottom of the table when table suppression has occurred.

ERROR: The table has been suppressed as it is too sparse
ERROR: table cell values have been suppressed

Counting units and weights

Weighting is the process of adjusting results from a sample survey to infer results for the total population. To do this, a 'weight' is allocated to each record. The weight is the value that indicates how many population units are represented by each sample unit.

To produce estimates for the in-scope population you must use a weight field in your tables. In TableBuilder they can be found under the Summation Options category in the left hand pane under the applicable level. If you do not select a weight field, TableBuilder will apply 'Person weight' by default. This will give you estimates of the number of persons.

If you are estimating the number of persons with certain characteristics (e.g. 'Number of non–school qualifications completed') the weight listed under the category heading 'Person level weighting' must be used.

When creating a table a default Summation Item will need to be the Reference year as this item will provide data for the relevant year. This item will then be used for time-series purposes as future data becomes available.

Selecting data items for cross-tabulation

The Person level contains a range of data items detailing the characteristics of respondents including demographic, education, labour force, participation, job search, mobility and population variables.

Populations and data items

When adding a data item to a table, it should be noted that not all respondents to the survey may be associated with than data item. For example, the data item “Main difficulty in finding work” only applies to people who looked for work. The “Not applicable” category for this item has been labelled as “Did not look for work” to indicate that only people who looked for work were asked about any difficulties in finding work.

Similarly, if users want to add multiple data items to a table they should ensure that these data items are applicable to the same population group.

For more information about data items, users should refer to the PJSM TableBuilder Data Items List available from Data downloads.

Cross-tabulating data items on the same level

Cross-tabulating data from the Person Level with other data items from the same level will produce data about people. For example, cross-tabulating the geographic variable 'State or territory of usual residence' by the 'Hours usually worked in main job' produces a table showing the number of people in each region by the hours that they usually work each week in their main job.

Multi-response data items

A number of the survey's data items allow respondents to report more than one response. These are referred to as 'multi–response data items'. An example of such a data item is pictured below. For this data item respondents can report all the difficulties they had in finding work.

Data items

When a multi–response data item is tabulated, a person is counted against each response they have provided (e.g. a person who responds 'Studying or returning to studies' and 'Caring for ill or elderly person/family member' and 'Problems with access to transport' will be counted once in each of these three categories).

As a result, each person in the appropriate population is counted at least once, and some people are counted multiple times. Therefore, the total for a multi–response data item will be less than or equal to the sum of its components.

For more information on definitions and concepts that apply to the data items in this file, please refer to Participation, Job Search and Mobility and Labour Force.

Using DataLab

DataLab allows real time access to detailed microdata files through a portal to a secure ABS environment. Using detailed microdata in DataLab allows users to run advanced statistical analyses using recent analytical software.

For information about the data items available on the detailed microdata files, see the Data Item Lists in Data downloads.

About DataLab

Detailed microdata files in DataLab can be accessed on-site at ABS offices or in a secure virtual environment from your own computer. All unit record data remains in DataLab, and any analysis results or tables are checked by the ABS before being provided to users.

Refer to DataLab for more information, including prerequisites for DataLab access.

PJSM microdata in DataLab, 2015-2022

Participation, Job Search and Mobility (PJSM) microdata is now available in ABS DataLab, released as a supplementary file for the Longitudinal Labour Force (LLFS) microdata. All existing users of the LLFS microdata will automatically get access to the PJSM file and new users can apply for access to both files. 

On May 27 2022, an updated file of PJSM microdata with annual data for the years ending February 2015 to February 2022 will be released into DataLab. This will replace the first release of PJSM microdata released on May 6 2022, which featured annual data up to the year ending February 2021.

Record identifiers

The record identifiers used in the PJSM and LLFS microdata are consistent across both files. This is to facilitate data linkage between the two files and enable further analysis. The PJSM survey is collected from private dwellings in 7/8th of the Labour Force Survey (LFS) sample, so not all records in February on the LLFS will have a corresponding PJSM record. There are also 334 records for February 2019 in the PJSM microdata that are imputed records due to floods in Townsville and cannot be linked to the LLFS microdata.

More details on these records and the formatting of record identifiers can be found in the Data Item List in Data downloads.

Weights

Person level weights (and replicate weights for calculating standard errors) are provided on the PJSM file. These differ from the weights provided on the LLFS file, as the weights are recalibrated for PJSM due to the reduced sample size compared to the LFS. Aggregate estimates from both sets of weights will align closely, as the PJSM survey data is benchmarked to match seasonally adjusted estimates from the LFS, but care should be taken when performing micro analysis.

PJSM weights are recommended for cross-sectional analysis of PJSM data items, but when linking PJSM and LLFS data for longitudinal analysis, new weights should be calculated based on the population benchmarks provided on the LLFS file. Care should be taken to account for attrition bias by adjusting the weights appropriately (increasing the weights for those more likely to leave the LFS). More information on using benchmarks and weights for longitudinal analysis is provided in Longitudinal Labour Force.

Historical microdata in DataLab, 1984-2012

Prior to 2014, microdata relating to labour mobility was released in a number of Confidentialised Unit Record Files (CURFs). These files are now available in ABS DataLab

For more information about these microdata releases, refer to the following archived publications:

Data downloads

Data files

History of changes

Show all

26/05/2022

This issue coincides with the release of data from the February 2022 Participation, Job Search and Mobility survey.

Details are provided on the second release of PJSM microdata in DataLab as a supplementary file for the Longitudinal Labour Force (LLFS) microdata. This file features annual data for the years ending Feb 2015 to Feb 2022 and replaces the first release of PJSM microdata released on May 6 2022, which featured annual data up to the year ending February 2021.

The release of PJSM data into TableBuilder has been delayed until later in the year in order to prepare for the release of 2021 Census data in TableBuilder.

06/05/2022

This issue provides details on the first release of PJSM microdata in DataLab as a supplementary file for the Longitudinal Labour Force (LLFS) microdata. This file features annual data for Feb 2015 to Feb 2021 and provides an indication of how the upcoming Feb 2022 PJSM microdata will be presented in DataLab for analysis.

06/09/2021

This issue provides information about the release of revised and additional data from the Participation, Job Search and Mobility Survey into TableBuilder, due for release on 8 Sep 2021: 

  • New parametric item - Duration of employment in current main job [months].
  • New parametric item - Duration of employment in last job [weeks].
  • Revisions to Population P05 - Part-time workers who would prefer full-time hours to correct an error in derivation that included workers who did not prefer more hours.
  • The following items were revised to better capture the population that was asked about Main reason child care is a barrier to participation:
    • Population P28 - PNILF who wanted work but were caring for children,
    • Whether caring for children affected participation in last 12 months,
    • Whether family considerations affected participation in last 12 months,
    • Whether pregnancy or child under 2 years affected participation in last 12 months.
  • Revisions to item Whether retrenched from last job to fix a minor error in derivation.
07/07/2021

This issue coincides with the release of data from the 2021 Participation, Job Search and Mobility Survey into TableBuilder. 

  • Many improvements have been made to the 2021 PJSM TableBuilder release to simplify the way data items are presented, increase the range of data items available and generally enhance the usability of the product.
    • The way that data items are arranged has been changed to better reflect different conceptual groupings (rather than populations and survey modules). Data items are now listed under one of 17 conceptual groups.
    • There were occasions where two separate data items were measuring the same concept but were specific to different sub-populations. These have now been combined and simplified into single output variables that can be applied across all populations.
    • Occupation data is now provided to the ANZSCO unit group level (4 digit).
    • Many new data items were added. Refer to the Data item list in Data downloads for the full range of items.
    • All parametric items (hours, weeks, etc.) are now available to the lowest available level (usually single hours or single weeks), and there is better consistency in how these items are grouped into higher levels. More of these items are now also included in the "Summation Options," so that means, medians, percentiles and custom ranges can now be calculated.
    • The "Not applicable" categories in each data item now have descriptive labels to describe which populations are not included for the data item.
    • Some data item labels have been revised or shortened to improve interpretability (note that the concepts remain the same).
  • Details and data item lists relating to historical labour mobility microdata have been added to the publication. These microdata files are available in ABS DataLab.
12/08/2020

This issue contains minor corrections to formatting. No data has been changed.

10/08/2020

First release of this publication to coincide with the release of data from the 2020 Participation, Job Search and Mobility Survey into TableBuilder

Previous catalogue number

This release previously used catalogue number 6226.0.00.001

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