Factors affecting interpretation
These estimates are not seasonally adjusted and seasonality can affect the interpretation of change, particularly between sub-annual periods. While annual comparisons can assist in understanding underlying change, they are less useful when events such as public holidays or pandemic lockdowns don't occur in the same week in both years.
In addition, when comparing the change between any two periods, interpretation can be complicated by variations in payroll jobs composition. Payroll job indexes are compiled from over 11 million jobs and variations in the types of jobs reported can result in compositional change (which is not quantified). For example, each payroll job in each week:
- is counted in the same way regardless of job status (full-time, part-time or casual), hence variations in demand for casual staff can influence week-on-week change.
- represents an individual in every paid job reported via STP, hence jobholders working multiple jobs are counted more than once. While multiple jobholders account for less than 10% of all payroll jobs, they can increase the rate of change seen week-to-week (in some industries) in circumstances where they are unable to work in any of their jobs (e.g. due to illness) and are not paid when absent.
Compositional change can also differ at the industry or state and territory level, particularly when there are localised labour market issues.
Alternative period comparisons
The combination of seasonal effects and differences in composition can increase the volatility of week-on-week or month-on-month changes in these estimates. For these reasons, the ABS recommends using comparisons of the current month to the same month in the previous year, or 3 months prior, to understand any trends in the payroll jobs estimates presented. These comparisons will likely reduce the impact of seasonal factors and compositional change, making trends easier to identify.
This release sees higher than usual revisions between early to mid-July 2023, as the 16 week imputation retention threshold passes through this period. These revisions mostly reflect the removal of previously imputed records, with the receipt of more complete data. Users should exercise caution when referring to estimates around this period.
This release presents percentage change between the weeks ending 14 October 2023 and:
- 30 September 2023, for fortnight
- 16 September 2023, for month
- 15 October 2022, for year
This differs for employment size estimates which are a month lagged.