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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.
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:. TableBuilder is an online tool for creating tables and graphs. Before applying for access, users should read and familiarise themselves with the information contained in the Table Builder, User Guide.
Compare access options to see what's right for you or Apply for access. Further information about these products, and other information to assist users in understanding and accessing microdata in general, is available from the Microdata Entry Page. Further information about the survey and the microdata can be found in the various pages associated with this product, including:. For further support in the use of this product, please contact Microdata Access Strategies via email at microdata.
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. Many improvements have been made to the 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 in TableBuilder has been changed to better reflect different conceptual groupings rather than populations and data items. These concepts groups are to assist with understanding the data and using the dataset. Data items are now listed under one of 17 conceptual groups:. In previous TableBuilder releases, there were occasions where two separate data items were measuring the same concept but were specific to different sub-populations.
For example, "availability to start work last week" was presented as a separate output variable for people not in the labour force and for people who were underemployed. 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 unit group level 4 digit. TableBuilder may suppress this level if a requested table is too finely detailed. Occupation data can be aggregated to minor, sub-major and major group levels 3, 2 and 1 digit levels to avoid table suppression.
Hours worked, hours preferred and duration data items have been aligned so they all provide data to the same level of detail. There is now consistency in the lowest available level usually single hours or single weeks , and the way that these items are aggregated into higher level groupings are now consistent.
More of these items are now also included as parameters in the "Summation Options. 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. The data for to have been revised to incorporate the population benchmarks that were used to produce estimates published in the April Labour Force, Australia.
To reduce the impact of seasonal effects on total employment, underemployment and unemployment, the benchmarks have been adjusted by factors based on seasonally adjusted Labour Force Survey estimates as published in April For example, February estimates have a typical seasonal pattern of higher unemployment.
The factors applied reduce the number of unemployed, to align with seasonally adjusted LFS estimates. Seasonally adjusted factors will be used until trend series are reinstated in Labour Force statistics. From February , statistics from the Participation, Job Search and Mobility survey are now published across three topic-based releases:.
This release of statistics from the PJSM survey includes a simpler approach for presenting statistics on unused labour supply. The new " Potential workers " release of PJSM data presents statistics for all people who are not employed i. Historically, PJSM content has been presented using the marginal attachment framework and the characteristics of people "not participating in the labour force", based on the criteria used to derive unemployment i.
While the new approach to presenting statistics for potential workers differs slightly from the traditional marginal attachment framework, and presents some population groups that do not entirely overlap with some of the marginally attached groups, there is still a strong alignment between them. Also statistics within the traditional marginal attachment framework are still available. As a result, estimates have been revised for the period to New sub-categories have also been introduced to separate this group into those who were available to start last week, those who could start within weeks, and those who were available in over 4 weeks.
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. 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 accessed from the Data downloads section. 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.
By default this field will be present in any new table as per the image below:. 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:.
However, at least one category reference year of the mandatory field must be present in a table for TableBuilder to retrieve data. 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. Hours usually worked in main job is not applicable for unemployed persons or persons not in the labour force.
From , The "Not applicable" categories in each item now have a descriptive label to describe which populations are not included for the data item. 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. 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. For general information relating to the TableBuilder or instructions on how to use features of the TableBuilder product, please refer to the TableBuilder, User Guide cat. 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.
In accordance with the Census and Statistics Act , 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. 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. 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. 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.
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. 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. 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.
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.
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. 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. When a multi—response data item is tabulated, a person is counted against each response they have provided e.
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.
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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. 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:. TableBuilder is an online tool for creating tables and graphs. Before applying for access, users should read and familiarise themselves with the information contained in the Table Builder, User Guide. Compare access options to see what's right for you or Apply for access. Further information about these products, and other information to assist users in understanding and accessing microdata in general, is available from the Microdata Entry Page. Further information about the survey and the microdata can be found in the various pages associated with this product, including:.
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