Monthly Household Spending Indicator methodology

The experimental Monthly Household Spending Indicator is derived using banks transactions, supermarket transactions and VFACTS data. As this data is not designed for statistical purposes, its scope varies from Australian National Accounts concept of household final consumption expenditure (HFCE) and the Retail Trade turnover estimates for retail businesses. Coverage adjustments are subsequently made to align the MHSI with the HFCE concept.

The indicator should be considered experimental at this stage, as further enhancement to the transformation processes and methodology are expected in the future.

HFCE is the goods and services paid for by Australian resident households within the Australian domestic territory or by Australian resident households abroad, for own non-commercial use. It is referenced to the period where the value of the good/service is consumed, rather than when it was paid for, in cases where these differ.

The MHSI consumption concept therefore aligns almost exactly with the National Accounts' HFCE concept.

The bank transactions data is provided to the ABS by participating banks for statistical production purposes. The data is provided to the ABS following the end of each calendar month. Once all data is received it is validated and collated.

The data is received in different formats and classifications from the participating banks. Some banks provide data at a low level of categorisation e.g., at a bank allocated merchant category level, and others provide categorised data at the Australia and New Zealand Standard Industry Classification (ANZSIC) or retail or non-retail level.

Data is received at different frequencies e.g. daily, weekly or monthly. All participating banks provide data at an identifiable state and territory level.

The aggregated bank transaction data does not contain information about individuals or households. Banks transactions data is only accessed by ABS staff required to produce relevant statistics, including the indicator. The ABS is committed to upholding the privacy, confidentiality and security of the information it collects.

The ABS receives weekly transactions data aggregates from selected supermarket chains. Transactions (Scanner) data captures point-of-sale purchases from retailers and contains detailed information about transactions, dates, quantities, product descriptions, and values of products sold.

The data is received in different formats and classifications from the participating supermarkets and is standardised before being processed for MHSI estimation. Each supermarket provides item-level sales data by week, at varying levels of geography. 

The weekly aggregates received do not contain information about individuals purchasing the products, and are a business-side view of total product sales.

The ABS receives monthly vehicle sales data from FCAI via the VFACTS datasets. These datasets capture total sales from FCAI-associated dealers within the reference month and contains detailed information about the make, class and engine type of the vehicles. Sales aggregates are delivered at the state and part-of-state level of geography (e.g. Victoria metro or Victoria rural).

The monthly aggregates received do not contain information about individuals purchasing the products, and are a business-side view of total product sales.

The indicator is derived from aggregated, de-identified bank card transactions data for resident households, as well as supermarket and VFACTS car sale data. The data is provided to the ABS from participating banks, selected supermarkets and the FCAI respectively. 

The source data does not cover the whole population and in the case of bank data, does not include all payment types. While cash payments, direct transfers outside the banks, cryptocurrency and BPAY transactions are all forms of household spending, these are not currently included due to lack of available data sources or ability to identify such transactions in the current data set.

Estimation methods are used to adjust for under coverage of the population, under coverage within each payment type and over coverage of institutional sectors. For more information see Estimation.

Furthermore, the following assumptions have been used in producing the indicator:

1. All transactions represent final consumption expenditure for own non-commercial use. The data includes household transactions that may feed into the production process (e.g., a household purchase of seeds to grow vegetables at home). As it is not possible to identify or adjust for these transactions, it is assumed any ‘intermediate consumption’ transactions in the data have an immaterial impact on the final estimates.
2. Non-resident transactions (net expenditure overseas) captured within the bank transaction data have an immaterial impact on the estimates. Lacking any means to identify and adjust non-resident transactions, it is assumed that expenditure patterns between resident and non-residents exhibit similar trends on consumption goods and services.

Outputs are produced for nine out of the thirteen major Classification of Individual Consumption According to Purpose (COICOP) Divisions. Outputs are produced at the Australia, and state and territory level. For more information see Outputs.

In addition to normal micro and macro editing procedures, a number of data transformation steps and adjustments are made to derive the Monthly Household Spending Indicator. These include:

• Classification and concordance mapping
• Apportioning industry sales totals to individual consumer products
• Estimation, including coverage adjustments and benchmarking
• Seasonal adjustment and Calendar adjusted estimates

The bank data has varying classifications. To produce aggregate COICOP outputs, a concordance structure was developed to map the transactions data from each participating bank. This maps bank data, by merchant category or ANZSIC class, to the COICOP Division classification and creates a consistent data set for further transformation. 

For retail industry categories, bank data is mapped to the COICOP output classification using a "industry-product matrix" derived from the 2012/13 Retail and Wholesale Industries (RISWIS) survey. This matrix allows industry sales to be apportioned to individual products by the use of survey-derived weights. 

As VFACTS and supermarket transactions data already contains product data, no separate industry-product mapping is required to produce COICOP outputs.

There are potential areas of both under and over coverage. For example, not all Australian resident households are represented within the supplied bank data resulting in under coverage of the population. Additionally, not all payment types are captured in the bank data, such as cash payments. There is also potential over coverage as individuals may use their personal bank cards for business-related purchases. Instances of over or under coverage can introduce bias and variance in the estimates. 

To rectify coverage issues, data-driven adjustments are made to the estimates. An adjustment is made to correct for under-coverage of people who are not customers of data participating banks, using published RBA statistics totalling all card spending across all financial institutions as a "control level". An additional adjustment is made to correct cash spending under-coverage, by combining ATM withdrawal data with RBA survey insights into household payment behaviour from different types of retailers. 

An additional layer of quality assurance includes benchmarking to annual state-level HFCE, which is done for the primary reasons of consistency with published national accounts HFCE figures and to ensure quality by using the annual HFCE as a quality control total. MHSI estimates are currently benchmarked up to 2021/22 HFCE.

When the next annual benchmark becomes available, the growth rates will be adjusted to meet the benchmark series. This will result in revisions. Revisions from the initial to the benchmarked growth rates can be used to provide an indication of the accuracy of the initial estimates of the MHSI in terms of size (variance) and direction (bias).

The indicator exhibits systematic seasonal and calendar related effects. Producing seasonally adjusted series improves the quality of the output in these ways:

• Interpretability – predictable seasonal effects will be removed to better identify short-term and long-term behavioural trends
• Relevance – increased suite of statistics available for users
• Coherence – comparability with existing outputs including retail trade and HFCE

MHSI produces seasonally adjusted series for national total, total goods, total services, total discretionary and total non-discretionary consumption. Individual COICOPs and state level series are at this point not seasonally adjusted, but these will be added in the future and replace the calendar adjusted series.

Monthly and quarterly series are produced for total household spending and nine of the major COICOP Divisions:

• Food
• Alcoholic beverages and tobacco
• Clothing and footwear
• Furnishing and household equipment
• Health
• Transport
• Recreation and culture
• Hotels, cafes and restaurants
• Miscellaneous goods and services (excluding Insurance and Other Financial Services)

Published outputs also include analytical series such as total consumption of goods/services, and discretionary/non-discretionary products. The table below shows how the COICOP categories are mapped to these particular groups

Current price estimates presented in this publication reflect both price and volume changes. However, the quarterly chain volume estimates measure changes in value after the direct effects of price changes have been eliminated and hence only reflect volume changes. The chain volume measures of household spending in this publication are annually reweighted chain Laspeyres indexes referenced to current price values in a chosen reference year. The indexes are linked using the one-quarter overlap method, and the reference year is currently 2021-22. Each year's data in the MHSI chain volume series are based on the prices of the previous year, except for the quarters of the 2023-24 financial year which will initially be based upon price data for the 2021-22 financial year. Comparability with previous years is achieved by linking (or chaining) the series together to form a continuous time series. 

Chain volume measures are not generally additive. In other words, component chain volume measures do not, in general, sum to a total in the way original current price components do. This means, for example, that the chain volume estimates for COICOP Divisions will not add to the total for Australia. Further information on the nature and concepts of chain volume measures is contained in the ABS publication Information Paper: Introduction of Chain Volume Measures in the Australian National Accounts (cat. no. 5248.0).

Legislative requirements to ensure privacy and secrecy of this data have been adhered to. In accordance with the Census and Statistics Act 1905, results have been confidentialised to ensure that they are not likely to enable identification of a particular person or organisation.

All personal information is handled in accordance with the Australia Privacy Principles contained in the Privacy Act 1988. For more information, see ABS privacy.

The data provided by the participating banks does not include all domestic resident households nor does it capture all household spending across the COICOP Divisions. Card and bank transactions are an appropriate and preferred mode of payment for most of the published COICOP Divisions, however, it does not represent all spending due to the absence of cash-based spending and other payment modes. Coverage adjustments are made to improve coverage and fill data gaps arising transactions from non-participating financial institutions, and cash spending.

Due to the varying payment modes, high concentration of non-card or bank transaction payments for some COICOP Divisions, and lack of available monthly data sources, a household spending indicator could not be produced for all major COICOP Divisions.

The appropriateness of using available data sources to measure household spending across each COICOP Division was assessed with selected Divisions excluded from the Monthly Household Spending Indicator.

COICOPs that are currently excluded from the indicator are:

• Rent and other dwelling services
• Electricity, gas and other fuels
• Communication Services
• Education Services
• Insurance and other financial services

Revisions are a change in the values of published data and may arise due to a variety of reasons.

Revisions may be applied to the Monthly Household Spending Indicator due to:

• Revisions to the source data
• Refinements to decisions made around the treatment of data anomalies in the series
• Implementation of methodological and process improvements
• Application of the annual benchmark
• Revisions as a standard feature of seasonal adjustment and trend estimation
• Application of a new chain volume reference year

The methods and data sources used will be subject to ongoing review to improve outputs and maintain the relevance of this indicator.

Indicator estimates are produced in current price and chain volume original terms, and for selected series, current price seasonally adjusted terms. Calendar adjusted estimates account for trading day impacts and length of month, and seasonal adjustment accounts for time-of-year related regular variation in consumption, so that movements represent meaningful deviations from expected patterns.

Published dollar levels are converted to millions and rounded to one decimal place. Published percentage changes are calculated on the underlying dollar levels and rounded to one decimal place. Any discrepancies between percentage changes published and percentage changes derived from published dollar levels are due to rounding.