Introducing the Consumer Price Indexes' new monthly time series

An introduction to the complete Monthly CPI data showcasing new monthly data for April 2024 - June 2025

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Released
18/11/2025
Release date and time
18/11/2025 11:30am AEDT

Introduction

Australia’s primary measure of headline inflation will transition from the quarterly CPI to a complete Monthly measure of the CPI on 26 November 2025 (for the October 2025 reference period). 

To support this transition, the Australian Bureau of Statistics (ABS) began collecting additional monthly data from April 2024. The ABS also implemented improved methods and acquired improved data sources for several indexes within the CPI. This means when publication of the Monthly CPI commences in November the ABS will include these series back to April 2024. 

This paper provides an overview of that monthly data from April 2024 – June 2025 that will be included in the October 2025 reference month publication. It includes insights into new trends that can be observed in the data collected to date for the indexes that are changing from quarterly to monthly. The paper also provides details of new data sources that will underpin some indexes and discusses how they differ to the sources they are replacing. 

Finally, the paper provides further information about the approach that ABS will take to seasonally adjust the short time series when the complete Monthly CPI goes live. (The ABS published details about seasonal adjustment for the complete Monthly CPI on 23 July 2025, see Seasonal adjustment for the new complete Monthly Consumer Price Index (CPI) | Australian Bureau of Statistics.)  

Attached to the paper are two downloadable data tables that include the percentage movements for each Expenditure Class, Sub-Group, Group and All Groups index up to June 2025¹. The percentage movements data match what will be included in the 26 November publication. Index numbers that will be published in the complete Monthly CPI are not, however, included in this paper because they will be re-referenced to a base period of September 2025=100.00 when they are published at the end of November. Rebasing the indexes does not impact the percentage movements of the indexes but will change the level of the index numbers.  

Executive summary

The complete Monthly CPI is a significant improvement from the previously published quarterly CPI and monthly CPI Indicator publications. It will provide comprehensive, monthly insights into economic conditions experienced by Australians.  The complete Monthly CPI will bring Australia’s economic data into line with other G20² countries who all publish their CPI data monthly making it easier to compare Australia’s inflation trends with those of other advanced economies and provide the community and governments with detailed inflation data every month. Importantly, it will also provide better information for monetary and fiscal policy decisions that have a direct impact on all Australians. 

The transition to the complete Monthly CPI is underpinned by a substantial increase in the amount of data collected monthly.  The quarterly CPI and monthly Indicator included a mix of monthly, quarterly, and annual price collection with around: 

  • 50% of the weight of the CPI basket being priced monthly;
  • 41% priced quarterly; and
  • 9% priced annually. 

In the complete Monthly CPI: 

  • 87% of the CPI by weight will be collected monthly;
  • 4% will be price quarterly including Other financial services (items such as stamp duty, real estate services and accounting services), as these prices do not tend to change frequently; and
  • 9% will continue to be priced annually as items such as school fees and private health insurance tend to only change price once a year. 

These changes are summarised in the following graphic. 

Change in frequency of data collection for the CPI by expenditure weight

Two bar graph comparing the frequency of data collection for each CPI Group by expenditure weight for the previous quarterly CPI and the new complete Monthly CPI.

Two bar graphs comparing the frequency of data collection for each CPI Group by expenditure weight for the previous quarterly CPI (bar graph on the left) and the new complete Monthly CPI (bar graph on the right). 

The frequency of data collection includes monthly, quarterly and annual. 

The increase in monthly data collection has been achieved through: 

  • more frequent data being provided by respondents and via websites; 
  • new data sources for child care and insurance; and 
  • a new model to underpin the calculation of changes in prices for apartments, which is included in the New dwelling purchase by owner-occupiers EC. 

The additional monthly data provides timelier insights into trends and turning points in inflation.  In particular, the monthly data shows: 

  • Most Goods indexes exhibit more variation on a monthly basis over the period than when they were collected quarterly. This is due to the monthly data more accurately capturing short term price changes such as Black Friday and End of Year sales. 
  • Most Services indexes are smooth when data is collected every month. The switch to monthly collection means that annual price reviews for services, for example at the start of a financial year, will appear earlier in the indexes. 
  • Much better alignment between the timing of price changes and the reporting of those changes in the Monthly CPI. 

Comparison between new Monthly CPI and previously published quarterly CPI

To understand the impact that these changes in data collection have had on the measurement of headline inflation in Australia, it is useful to compare the previously published quarterly CPI with the complete Monthly CPI.  As explained in Monthly and quarterly data series | Australian Bureau of Statistics,  the ABS will continue to produce quarterly CPI data series calculated as the average of the three relevant Monthly CPIs.  

Using this method to calculate quarterly indexes from the complete Monthly CPI data shows that the complete Monthly CPI aligns very closely with the previously published All Groups quarterly CPI. 

All groups CPI Index, June 2024 quarter = 100.0

Line graph comparing the previous quarterly All groups CPI indexes to quarterly indexes derived from the new complete Monthly All groups CPI indexes

Line graph comparing the previous quarterly All groups CPI indexes to quarterly indexes derived from the new complete Monthly All groups CPI indexes, between the June quarter 2024 and June quarter 2025. Indexes are re-based to June 2024 quarter, or June 2024 quarter = 100.0. 

Notes: (i) Complete Monthly CPI quarterly indexes have been calculated as the average of the three relevant Monthly CPIs. 

(ii) The underlying data for this graph can be found in the Data downloads. 

The following graph compares the quarterly movements as previously published, rounded to 1 decimal place, with those derived from the average of the Monthly CPI, also rounded to 1 decimal place.  Apart from the March quarter 2025, the differences between the two, when calculated using the underlying indexes, are less than 0.03 percentage points.   

In the case of March quarter 2025, the difference of 0.1 percentage point between the two is primarily due to several ECs in the Furnishings, household equipment and services Group and the Clothing and footwear Group changing from quarterly to monthly pricing.  In the quarterly CPI, prices for these ECs were collected in January and were treated as the price that applied for the whole quarter. In reality, prices for these products tended to be lower in January due to end of year and post-Christmas sales than they were in February and March when the discounting ended. The Monthly CPI captures the higher prices that applied in February and March for these products resulting in a higher movement for the All Groups CPI for the March 2025 quarter. 

Notes: (i) Complete Monthly CPI quarterly indexes have been calculated as the average of the three relevant Monthly CPIs. 

Comparison between new Monthly CPI and previously published monthly Indicator

Monthly data is inherently more variable and timelier than quarterly data. Comparing the complete Monthly CPI with the previously published monthly Indicator (Monthly Consumer Price Index Indicator, September 2025 | Australian Bureau of Statistics) therefore, more clearly highlights the additional insights that the Monthly CPI will deliver. In the monthly Indicator, prices that were collected once a quarter were ‘rolled forward’ between the months in which they were collected. Replacing these imputed prices with prices collected every month more clearly shows the impact of regular sales periods on inflation. It also shows changes such as the re-setting of the Medicare Benefits Schedule and Pharmaceutical Benefits Scheme safety nets in a much timelier manner. 

All groups CPI Index, April 2024 = 100.0

Line graph comparing the previous monthly Indicator All groups CPI indexes to the new complete Monthly All groups CPI indexes, between April 2024 and June 2025.

Line graph comparing the previous monthly Indicator All groups CPI indexes to the new complete Monthly All groups CPI indexes, between April 2024 and June 2025. Indexes are re-based to April 2024, or April 2024 = 100.0. 

The labels on the graph provide high level explanations for differences between the monthly indexes in certain time periods. 

Notes: (i) The underlying data for this graph can be found in the Data downloads. 

All groups CPI, monthly movement (%)

Column graph comparing the previous monthly Indicator All groups CPI monthly percentage movements to the new complete Monthly All groups CPI monthly percentage movements

Column graph comparing the previous monthly Indicator All groups CPI monthly percentage movements to the new complete Monthly All groups CPI monthly percentage movements, between May 2024 and June 2025. 

The labels on the graph provide high level explanations for differences between the monthly percentage movements in certain time periods. 

Notes: (i) The underlying data for this graph can be found in the Data downloads. 

Seasonally adjusting short time series

This paper will expand on the previously published paper (Seasonal adjustment for the new complete Monthly Consumer Price Index (CPI) | Australian Bureau of Statistics). In that paper, the ABS explained that 44 of the 87 ECs in the CPI will have time series that will be too short to apply standard seasonal adjustment methods in the short term. Of these, an estimated 18 ECs (10% of the basket) will have seasonal influences that will be managed by smoothing them out, to significantly reduce the impact of these seasonal influences on the seasonally adjusted and Trimmed mean series. This paper provides more detail on the steps that the ABS will take to determine whether an intervention is warranted and how the affected seasonally adjusted series will be smoothed. 

New monthly data time series - highlights

The attached tables include monthly indexes and monthly and annual movements for all Expenditure Classes (ECs) and above indexes for the period April 2024 to June 2025. The following summarises the main points of interest and changes that underpin those indexes. 

Highlight 1: More insights into price behaviour

Highlight 2: Improved alignment of changes in CPI with real-world price changes

Highlight 3: New and improved data sources

Highlight 4: New methods

Group level analysis

Another highlight of the change to a complete set of monthly indexes is that it will be possible to produce high quality aggregated indexes each month. This section provides insights into: 

  • How the transition to the complete Monthly CPI has changed how each of the eleven Group level indexes is measured;
  • What the indexes for each Group look like for the period April 2024 to June 2025; and
  • The main drivers of Group level movements in that period. 

Food and non-alcoholic beverages Group

Alcohol and tobacco Group

Clothing and footwear Group

Housing Group

Furnishings, household equipment and services Group

Health Group

Transport Group

Communications Group

Recreation and culture Group

Education Group

Insurance and financial services Group

Methods for seasonally adjusting short time series

At the time of first publication of the Monthly CPI, 44 of the 87 expenditure classes (ECs) will have data for 18 monthly movements. Standard seasonal adjustment methods require a minimum of 3 years of data. The ABS will apply a range of methods to manage seasonality for these short time series where appropriate and will transition to standard seasonal adjustment methods for those ECs when 3 years of data has been collected.  

Application of the methods described in the information paper Seasonal adjustment for the new complete Monthly Consumer Price Index (CPI) | Australian Bureau of Statistics will allow the ABS to produce seasonally adjusted and underlying measures of sufficient overall quality to improve interpretation of the month-to-month behaviour of the complete Monthly CPI and provide valuable information on underlying inflation. 

Of the 44 ECs with short time series, the ABS expects that around 18 ECs (10% of the weight of the CPI) will have seasonality that will be managed by smoothing these series to reduce the effect of large seasonal influences on monthly index movements. As explained in the previous information paper: 

ABS will smooth short time series ECs that cannot be seasonally adjusted where:  

  • information exists to confidently predict that strong price changes in some months of the year are largely being driven by seasonal effects, and
  • the data collected to date is consistent with these expectations. 

Unlike standard seasonal adjustment methods, the smoothing interventions target strong seasonal effects and aside from a small number of special cases, the adjustments will only be applied in selected months of the series. These treatments are designed to reduce residual seasonality of the headline CPI seasonally adjusted series and the trimmed mean series. Monthly seasonally adjusted and trimmed mean series incorporating all data available up to and including October 2025 will be included from the first publication of the complete Monthly CPI on 26 November. 

The series with the smoothing interventions will be produced until the time series have three years of data. The soundness of applying smoothing to these short time series has been supported by a recent review by Professor Rodney Strachan from the University of Queensland.  

Methods to smooth short time series

The smoothing method is applied when there is a high confidence that the price changes in specific months of a series are largely driven by seasonal influences. This method attempts to remove the bulk of the effect of these specific seasonal influences. The resulting smoothed series is therefore designed to better reflect what would have been observed, if these seasonal influences did not exist. 

The smoothing method applied to an EC varies according to the expected nature of seasonality affecting the series. Separate procedures are applied for three types of ECs: 

  1. ECs with strong seasonal discounting and no other strong expected seasonal effects
  2. ECs with seasonal price rises and falls throughout the year
  3. ECs which generally have sustained price increases, but a concentration of the increases occur in a small number of months of the year 

Most of the ECs which will have smoothing interventions belong to type A, and the procedure for these ECs is given in Section 1. Sections 2 and 3 describe the procedures for types B and C respectively. 

ABS practise when applying seasonal adjustment includes adjusting parameters and approaches depending on data features and methods performance. In a similar way, it may be necessary to adapt the parameters and thresholds used for this interim smoothing method over the next 18 months. The parameters and thresholds presented in this paper have been derived based on data to date, and these may be adjusted in response to features in the data observed in future months. 

Smoothing to manage strong seasonal discounting (Type A ECs) 

The flowchart below presents the procedure to produce a smoothed output series which treats the effects of short-term price discounting in expected months. These months are typically within two windows:  

  1. at the end of the financial year (June or July); and
  2. at the end of year and new year (November, December or January). 

Each month the procedure is applied to assess smoothing decisions for all observations in chronological order. The following points summarise the key aspects of the structure of the procedure in the flowchart below.  

  1. A smoothing intervention is introduced for a discounting window only if an observation in the window is sufficiently different from the level of the short-term trend at the previous month. The observation of interest is compared with the 5-term Henderson moving average (5-HMA)⁶ calculated for the previous month (using only data up to that prior month observation). A smoothing intervention is introduced if the observation of interest in the discounting window is at least 1.5% different from the 5-HMA value for the previous month.
  2. A smoothing intervention applied in the preceding month is extended to the current month if it is at least 1.5% different from the smoothed intervened value at its prior month.
  3. The smoothed value of an observation within an expected discounting period depends on whether there are observations beyond the discounting window which show a sustained drop in the series level. This dependency means the smoothed values can be revised when new data points are added to the series.

  4. The following procedure is used to set the smoothed value for observations satisfying the criteria in (1) and (2) and are within a discounting window.

    a. When there are no observations following the end of the seasonal discounting period, the previous value will be rolled forward. The exception to this is when the index level in the month prior to the discounting is assessed to be unusually high and so provides an unsuitable roll-forward value. If the pre-discounting month exceeds the 13-HMA value (calculated using data up to that month) by at least 1%, the smoothed value will be set to this 13-HMA value instead of a roll forward of the previous value.

    b. When there is an observation following the end of the discounting period, the smoothed value will typically be set as determined by (4a). The exception is when the data beyond the discounting window shows the seasonal discounting coincided with sustained drop in the series level. A sustained drop is deemed to have occurred when all observations between the commencement of discounting and the month following the discounting period are at least 1.5% below the 5-HMA level prior to commencement of the discounting. In this case, the smoothed series value is the value of the 5-HMA at that observation. 

For the ECs using the procedure to smooth for discounting effects, monthly data collected to date indicates only a small proportion of total variation in the series is associated with the medium-to-long-term variation. Using roll-forward values for smoothing these series in 4a has been assessed as fit for purpose and will prevent potentially large revisions in the smoothed output series which could arise if a series trend estimate were used to set the smoothed value. ABS will continue to monitor the performance of the smoothing method over the 18 months it will be used and may alter aspects depending on the features of the data observed, including the use of roll-forward values and all relevant thresholds used to determine whether to apply smoothing. 

Smoothing procedure for Expenditure Classes with seasonal discounting

Flowchart that breaks down the smoothing procedure for Expenditure Classes with seasonal discounting

Flowchart that breaks down the smoothing procedure for ECs with seasonal discounting. 

The flow chart shows the key requirements that lead to a decision to:
a) do not apply a smoothing intervention, and 
b) set smoothed valued to either the previous month value of the index or set smoothed value to the value of 5-term HMA. 

Appendix 4 provides an example of how this method will work in practice. 

Smoothing to manage seasonal price rises and falls throughout the year (Type B ECs) 

The monthly data collected since April 2024 for the three footwear ECs show higher prices in April and October and lower prices at the end of the year. Seasonal stock changes in April and October are expected to be the main cause of the increases in these months, and seasonal discounting is expected to be the main cause of lower prices in some other months. The smoothing process for these series needs to account for the overall uncertainty in the underlying level of the index given these price fluctuations throughout the year. 

The 9-term HMA calculated at each point in the series will provide the smoothed output series for the three footwear ECs. The graph below shows an example of this smoothing approach for the Women’s footwear EC. ABS will continue to monitor the performance of this approach and may adjust the application of the method and parameters used, such as the filter length. 

Series with price increases concentrated in a small number of months: services (Type C ECs) 

Services ECs typically increase over time and are unaffected by short-term falls. They display seasonality if price rises tend to be larger in particular months of the year (e.g. in July when award wage rates increase). Smoothing is considered for seasonally adjusting services ECs for which: 

  1. the original monthly series contains increases above 0.75% in that calendar month for two years, and
  2. there are expectations of seasonal price increases in the calendar months with large increases. 

Only the observations at or close to the month with the large increase are subject to smoothing. Smoothing is applied to observations in which the observed value differs from the 9-HMA by at least 0.4%. The smoothed value is set to the 9-HMA value in these months. The graph below illustrates the application of this method to the Sports Participation EC in May to August 2024. Note that as per criterion 1. above, whether this smoothing intervention will be retained in the smoothed output series will depend on whether a similar effect is observed in the May to August 2025 period. 

ABS will continue to monitor the performance of this method relative to features of the data and may alter these thresholds and filter lengths accordingly. 

The graph below illustrates the application of this method for the Sports Participation EC. 

Data downloads

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Time series spreadsheets

Data files

Appendices

Appendix 1: Pricing patterns for new monthly Goods EC

Table 1. Overview of pricing patterns in new monthly Goods ECs April 2024 – June 2025
 ECs
ECs that exhibit one or more periods of short-term discounting activity (e.g. EOFY, end of year, Black Friday)

Garments for men

Garments for women

Garments for infants and children

Footwear for men

Footwear for women

Footwear for infants and children

Accessories

Furniture

Carpets and other floor coverings

Household textiles

Major household appliances

Small electrical appliances

Glassware, tableware and household utensils

Therapeutic appliances and equipment

Motor vehicles

Spare parts and accessories

Audio, visual and computing equipment

Books

Newspapers, magazines and stationery

Equipment for sports, camping and open-air recreation

Games, toys and hobbies

Goods ECs with other pricing patterns

Takeaway and fast foods EC and Audio, visual and computing media and services EC which display smooth trends on a monthly basis similar to Services ECs (see below in Appendix 2).

Tools and equipment EC which displays discounting behaviour but with different timing to other Goods ECs (for example end of summer sales around February and Spring sales between August and November). 

Goods ECs with shifts in timing of pricing movements (see Highlight 2.)

Water and sewerage EC prices will now update in July each year, in line with annual price reviews. 

Pharmaceutical products EC includes out-of-pocket prices paid for medicines covered by the Pharmaceutical Benefits Scheme (PBS). This EC will more accurately reflect the timing of changes in PBS out-of-pocket prices, which are particularly noticeable in January when the safety net resets.

Appendix 2: Pricing patterns for new monthly Services EC

Table 2. Overview of pricing patterns in new monthly Services Expenditure Classes April 2024 - June 2025
 ECs
Services ECs with smooth monthly trends

Restaurant meals

Cleaning, repair and hire

Maintenance and repair of the dwelling

Hairdressing and personal grooming services

Other household services

Dental services

Maintenance and repair of motor vehicles

Veterinary and other services for pets

Services ECs with other pricing patterns

Medical and hospital services – typically shows large price increases in January and April each year related to the resetting of the Medicare Benefits Schedule (MBS) safety net and annual increases in Health insurance premiums.

Other services in respect of motor vehicles – more volatile price patterns than other Services ECs related to changes in State-based vehicle registration fees. 

Telecommunication equipment and services – more volatile price patterns related to EOFY sales and new models of phones/smart watches being released.

Other recreational, sporting and cultural services – price changes related to cinema discounting.

Sports participation – price increases at the start of the financial year

 

Appendix 3: Child care source data and methods changes details

As noted in the body of the paper, as part of the transition to a complete monthly CPI, Services Australia provided ABS with an anonymised census of child care payment and subsidy records.  In addition to improving the accuracy of the measurement of child care out-of-pocket costs in the CPI the change in data sources and methods has several notable implications, including: 

  • The new monthly index generated from actual payments data needs to be lagged by a month to enable time for the data to be submitted by child care providers to Services Australia and from there to the ABS. ABS has assessed that the significant improvement in the measurement of out-of-pocket child care costs outweighs the reduced timeliness – particularly given that a one-month delay will still be timelier than the current quarterly approach.
  • Generally, the monthly index is more volatile than the published quarterly index, in particular showing price falls in January. The graph below shows that the January drops in the final price index are caused by decreasing gross prices in these periods. One contributor to this decrease in gross prices is discounts being offered by some child care centres over school holiday periods.
  • An additional divergence compared to the published quarterly index is the large price increase in August (including the one-month lag). This can be partly explained by the gross price increases by child care centres, which often occur at the start of the financial year. Another contribution to the increase in August in the monthly Child care index relates to changing family income estimates. At the start of a financial year customers are asked to update their income estimate, and automatic indexation of incomes is applied by Services Australia if they do not⁷. Increasing income estimates leads to lower subsidy rates (and therefore higher out-of-pocket costs for households) compared with the previous financial year. 

At the end of the financial year there is a balancing process based on the actual financial year income for the family, known as reconciliation, to determine the correct subsidy entitlement they should have received for the financial year. Families may then be paid any additional subsidy owing to them or may need to repay excess subsidy back to Services Australia. The effect of this tax-time reconciliation of subsidies is not included in the child care index because it occurs after the end of each financial year and so cannot be measured in real time.  

The graph below shows some of the complex interrelationships between the different items that make up out-of-pocket costs for child care. For example, the graph shows that fees charged by child care providers ie gross fees (light blue line) increased in August 2024 (including the one-month lag).  At the same time the average estimate of family incomes used to determine subsidy entitlements increased (dark blue line). As a family’s estimated income goes up, the percentage of the child care gross fee covered by the child care subsidy falls⁸, resulting in an increase in out-of-pocket costs.  Child care subsidies are indexed in August (including the one-month lag) contributing to the increase in the total child care subsidy amount paid (red line), but the overall amount of subsidy has not increased by as much the gross fees, due to the increase in estimated family incomes. In addition to the increase in gross fees, this reduction in the proportion of fees covered by the subsidy results in higher out-of-pocket costs as measured by the CPI (orange line). 

In addition to the data provided to the ABS by Services Australia, ABS has been provided with data by the Department of Education back to 2020 that shows that these price increases at the start of the financial year, and price falls in holiday periods, have occurred regularly in recent years. The older data is not directly comparable to the data that will be published in the monthly CPI publication and so will not be used to extend the length of the time series that will be included in the monthly publication. It has, however, been useful in understanding seasonal patterns in the new administrative data that will underpin the child care index. This understanding of the historic price rises and falls has been used to derive a seasonally adjusted child care index which removes these regular effects to show the underlying changes in prices as shown in the following graph.  

Notes: (i) seasonally adjusted figures are routinely revised as new data points are added to the time series, so users should anticipate that the seasonally adjusted index presented here will change when published in November. 

Appendix 4: Worked illustration of seasonal adjustment for ECs with strong seasonal discounting and no other strong expected seasonal effects

The below provides a staged illustration of an example series for which seasonal discounting is expected to occur over November-December-January. 

When data is only available up to December 2024: 

  • the original November value is less than 1.5% different to the 5-HMA calculated on the October value, so no smoothing is applied and the original November value is retained in the smoothed output series
  • the December value is more than 1.5% different to the 5-HMA calculated on the November value, so the December observation would be smoothed. Because no January value is yet available, the smoothed value would be the November value, rolled-forward 

When data up to January 2025 is available: 

  • the January value in this example is more than 1.5% different to the smoothed value for December, so the November value would be rolled-forward again 

When data up to February 2025 is available: 

  • the February 2025 value in the example is outside the identified discount window so is not considered for smoothing, and
  • a sustained drop is identified. In this scenario, the December 2024 value is revised to be the 5-HMA at value for this month. The January 2025 observation is no longer smoothed because it is within 1.5% of the 5-HMA calculated up to December 2024 where the December 2024 value is the revised smoothed value. 

Footnotes

¹ Underpinning the change to the complete Monthly CPI was a complete system rebuild (Design, Sources and Methods | Australian Bureau of Statistics). Data for the September quarter 2025 months was not available for inclusion in this paper as it is being transformed and transferred from the old processing system to the new one.

² The make-up and role of the G20 is explained here: The G20 | Australian Government Department of Foreign Affairs and Trade.

³ Examples of how consumers’ purchases of grocery products change in response to sales activities can be found in the 'How do consumers react to the price of food and evidence from supermarket micro data' paper here: Underneath the headlines: understanding price change in the Australian economy | Australian Bureau of Statistics

⁴ Consumer Price Index, Australia, December Quarter 2024 | Australian Bureau of Statistics.

⁵ The model is an ARIMA(1,1,0) model with a constant term. The model specification will be periodically updated. 

⁶ Note that where Henderson moving averages are used, these will be symmetric wherever possible, or otherwise asymmetric to the extent that is necessary due to the available length of the time series.

⁷ Your family income estimate for family assistance payments - Child Care Subsidy - Services Australia.

⁸ More information about how the childcare subsidy is calculated is available here: Your income can affect Child Care Subsidy - Child Care Subsidy - Services Australia.