Weekly Payroll Jobs and Wages estimates reinstated
This release sees the return of estimates following a two month pause while the ABS and ATO implemented changes to the processes supporting the use of STP data for statistical purposes. These changes have resulted in revisions to all payroll jobs and wages indexes and are concentrated in the second half of 2022. The ABS recommends that analyses of previously published estimates be refreshed with the data from this release.
Within this release, additional sections have been included at the end of the national, state and territory and industry sections presenting estimates for the reference periods of the weeks ending 10 December 2022 and 14 January 2023. For more information on the impact of the update, see the Update to STP processes section of the Methodology.
At year-end, payroll jobs and wages estimates usually see larger seasonal changes and can be affected by a higher degree of reporting variability. In this release, wages estimates across year-end have seen additional variability due to an increased incidence of one-off payments during December 2022 and January 2023.
Factors affecting interpretation
These estimates are not seasonally adjusted. Seasonality can affect the interpretation of change in payroll jobs and wages, 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 in payroll jobs and wages between any two periods, interpretation can be complicated by variations in their 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.
Wages can be more heavily influenced by week-to-week change in composition, as the wages index reflects movements in aggregate wages and salaries paid (unlike the ABS Wage Price Index which presents changes in the price of labour unaffected by compositional shifts in the labour force, hours worked or employee characteristics). Variability in wages indexes in this release in any given week may be due to:
- changes in hours worked,
- the inclusion of cyclical payments such as bonuses, commissions or lump sum payment of leave loading,
- payment of penalty rates for public holidays (which may not fall on the same date each year), or
- the inclusion of irregular payments such as overtime, ad hoc or one-off payments relating to employee recognition or enterprise agreement sign-on.
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 and wages estimates presented. These comparisons will likely reduce the impact of seasonal factors and compositional change, making trends easier to identify.
To learn more about the different labour measures available, their purpose and how to use them, see our Earnings guide.
This release sees higher than usual revisions in October 2022, 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.
With the inclusion of additional reference periods in this release, the dates of all change periods are noted within each reference period section.