Sources and methods - Annual

The periodic Retail and Wholesale Industry Surveys (RIS/WIS) provides the primary benchmark estimates for this series.

The value of self-supplied food is included and is based on estimates of the amount of food produced for home consumption from the ABS publication, Home Production of Selected Foodstuffs, Australia.

The following scope and coverage adjustments are made:

• sales of food prepared off premises, sourced from irregular ABS publications:  Accommodation Services, Australia; Clubs, Pubs, Taverns and Bars, Australia; Cafes, Restaurants and Catering Services, Australia; Casinos, Australia; Gambling Services, Australia; Performing Arts, Australia; and Sports and Physical Recreation Services, Australia.
• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing units selling directly to households; and
  • goods purchased on ships and aircraft, flea market sales and sales by NPISH units.
• an estimate for cooked meals by food stores prepared on the premises for consumption off-the-premises is subtracted;
• an estimate for food withdrawn from sale is also removed (this is considered to be an intermediate use of food); and
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The periodic Retail and Wholesale Industry Surveys (RIS/WIS) provides the primary benchmarks for this series.

The value of home-made alcohol is included and is based on estimates of the amount of alcohol produced for home consumption from the ABS publication, Home Production of Selected Foodstuffs, Australia.

The following scope and coverage adjustments are made:

• sales of alcoholic beverages from service industries sourced from irregular ABS publications:  Accommodation Services, Australia; Clubs, Pubs, Taverns and Bars, Australia; Cafes, Restaurants and Catering Services, Australia; Casinos, Australia; Gambling Services, Australia; Performing Arts, Australia; and Sports and Physical Recreation Services, Australia.
• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing units selling directly to households; and
  • goods purchased on ships and aircraft.
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The value of tobacco products consumed by households is estimated using the formula:

Domestic production

                     + imports

                     –  exports

                     –  re-exports

                     + taxes on products

                     + margin estimate

                     = Total consumption.

The value of domestic production is estimated using the estimates of income for sale of goods from the Economic Activity Survey. Exports and re-exports data are obtained from trade data as sourced from the ABS Balance of Payments. Taxes on products are sourced from Government Finance Statistics. Margins data are obtained from the RIS/WIS.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing units selling directly to households; and
  • flea market sales.

• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Census of Population and Housing is the benchmark data source for the number of owner-occupied and rented dwellings and information about rents paid for rented dwellings.

The imputed rent for owner-occupied dwellings is calculated by multiplying average rents (adjusted to exclude rents at less than market value) reported in the census for privately rented dwellings in various categories.

Estimates of imputed rent of owner occupiers for intercensal and post-census periods are obtained by multiplying an estimate of the stock of dwellings by an estimate of the average rent of rented dwellings.

The stock of dwellings is estimated by extrapolating the benchmark estimate. The benchmark stock of dwellings includes all occupied private dwellings and a proportion of unoccupied private dwellings but excludes short-term caravans in caravan parks.

Private dwellings include separate houses, duplexes, town houses, flats including those which are part of a building that is used for commercial purposes (e.g. a retail shop) and caravans used for long-term accommodation. Additions to the stock are calculated from the number of dwelling completions sourced from the ABS publication, Building Activity, Australia. This is then modified by a factor to take into account other changes to the stock of dwellings (demolitions, net conversions from commercial uses and dwelling completions not in the scope of the survey).

For intercensal periods, this factor is calculated by dividing the change in the stock between the census benchmarks by the total number of dwelling completions in the period. For the post-census period, the factor is assumed to be the same as for the latest intercensal period.

After the latest applied benchmarks from the Census of Population and Housing, the total and owner occupied rent prices have been obtained from a combination of the Survey of Income and Housing (SIH), the CPI and real estate bulletins (Australian Property Monitors and Real Estate Institute of Australia).

These estimates are produced using the same sources as for the estimates of imputed rentals for housing.

The benchmark calculation gives a direct measure of the dwelling rent paid by households to the owners of dwellings.

Data is sourced from the ABS publication, Household Expenditure Survey, Australia: Summary of Results. HES provides the benchmark estimates for this series which includes water and sewerage and waste services.

The following scope and coverage adjustments are made:

• household expenses on water and sewerage service charges for rental and investment properties, which are out of scope of HES - based on HFCE estimates of actual rent for housing and imputed rent for owner occupiers;
• coverage for remote and non-private dwellings which are not in scope of the HES; and
• to capture final consumption expenditure of NPISH units using waste collection and disposal services, based on current grants information sourced from the Government Finance Statistics.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Volume estimates for water and sewerage services are based on the sum of the quarterly volumes.

Annual current price estimates in relation to waste collection and disposal services are re-valued using relevant price deflators from the Consumer Price Index to derive the annual volume estimates.

The Household Expenditure Survey provides the benchmark estimates for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing units selling directly to households;
  • dealers’ margins associated with second-hand goods; and
  • flea market sales and sales by NPISH units.

• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of furnishings and floor coverings in Australia are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • flea market sales and sales by NPISH units.
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of household textiles in Australia are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing and wholesaling units selling directly to households;
  • electricity, gas and water industry units selling directly to households;
  • dealers’ margins associated with second-hand goods; and
  • flea market sales and sales by NPISH units.
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore. adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of household appliances in Australia are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • flea market sales.
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of glassware, tableware and household utensils in Australia are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • flea market sales.
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of tools and equipment for house and garden in Australia are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing and wholesaling units selling directly to households; and
  • flea market sales.
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of non-durable household goods in Australia are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture current grants from government to NPISH units providing ambulatory health care sourced from annual time series data from the Government Finance Statistics;
• to capture current grants and donations from corporations and households to NPISH units providing ambulatory health care as extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Accounts;
• household claims from private health insurance funds sourced from the Private Health Insurance Administration Council (PHIAC);
• an estimate of 15 per cent of household claims associated with the health service component of workers’ compensation and motor vehicle and third party insurance sourced from the Australian Prudential Regulation Authority (APRA). This was derived from workers’ compensation and other insurance estimates associated with health services for ANZSIC Subdivision 85 Medical and other health care services, published in Health Care Services; and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey (HES) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture current grants from government to NPISH units providing ambulatory health care sourced from annual time series data from the Government Finance Statistics;
• to capture current grants and donations from corporations and households to NPISH units providing ambulatory health care as extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Accounts;
• household claims from private health insurance funds sourced from the Private Health Insurance Administration Council (PHIAC); and
• an estimate of 15 per cent of household claims associated with the health service component of workers’ compensation and motor vehicle and third party insurance sourced from the Australian Prudential Regulation Authority (APRA). This estimate was derived from workers’ compensation and other insurance estimates associated with health services for ANZSIC Subdivision 85 Medical and other health care services published in Health Care Services;
• an estimate of household expenses associated with nursing home fees. As nursing homes are not in scope of the HES, direct expenditure on these services is estimated using services income associated with Aged care residential services from the Economic Activity Survey; and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Annual volume estimates for healthcare HFCE are estimated in conjunction with volume estimates for health output based on the direct volume index approach and output volume method, as described in Chapter 9, Table 9.30.

Hospital services are provided to both admitted and non-admitted patients, as well as through different settings such as emergency departments. The number of hospital separations, emergency presentations and non-admitted events are used as quantity indicators; direct volume indexes are constructed for admitted patient care, emergency departments and non-admitted patient care services using average costs for weights.

Weights for aggregation are sourced from the Australian Institute of Health and Welfare (AIHW), Government Finance Statistics and Economic Activity Survey. They are used to construct volume indexes for private, public and total hospitals. Other data are sourced from AIHW and the Independent Health and Aged Care Pricing Authority (IHACPA).

Non-hospital services are based on the number of non-hospital services provided, stratified at various levels of procedure type, and weighted together by their respective current price value of expenditures. Data are sourced from Medicare, the Private Health Insurance Administration Council and the Productivity Commission Report on Government Services.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• purchase of vehicles that are out of scope of the survey;
• dealers’ margins on used vehicles traded between households;
• the value of private imports of used vehicles are estimated using data supplied from Customs documentation and an average price for used cars sourced from Vehicle Sales from the Federal Chamber of Automotive Industries (FCAI) publication, Vehicle Facts (VFACTs), or Glass' Automotive Business Intelligence (Glass' Guide); and
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Annual household expenditure on automotive petroleum and coal products are based on the ABS publication, Survey of Motor Vehicle Use, Australia (SMVU).

The SMVU includes information on the fuel consumption of all motor vehicles by motor vehicle type and the private use of all vehicles by type of vehicle. Using this information and the national average retail price per litre of petrol and diesel sourced from the Australian Institute of Petroleum and the Automotive Petroleum Association, respectively, supplemented by Energy Accounts data, annual estimates of household expenditure for automotive petroleum and coal products are estimated.

The Household Expenditure Survey provides the primary benchmarks for the series relating to pneumatic tyres and tubes for motor cars and motor cycles, motor vehicle engines, chassis and panels; transport equipment not elsewhere classified, motor vehicle repair and maintenance expenditure and miscellaneous motoring expenditure.

The proportion of household claims associated with Motor Vehicle Comprehensive and third party insurance that captures estimates for the repair of accident damage to insured motor vehicles owned by the household sector is also included in compilation of Automotive repair and maintenance services.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES; and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture the final consumption expenditure of NPISH units using railway passenger transport services based on current grants information as sourced from the Government Finance Statistics;
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES; 
• to capture the final consumption expenditure of NPISH units using road passenger transport services based on current grants information as sourced from the Government Finance Statistics;
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture the final consumption expenditure of NPISH units using passenger transport by sea and inland waterway services based on current grants information as sourced from the Government Finance Statistics;
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of expenditure on postal services are re-valued using relevant price deflators from the CPI.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture the final consumption expenditure of NPISH units using telecommunication services based on current grants information sourced from the Government Finance Statistics;
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price annual estimates of expenditure on telephone and facsimile services are re-valued using relevant price deflators from the Consumer Price Index.

Volume estimates for internet services are based on the sum of the quarterly volumes.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales of recreation and culture sourced from irregular ABS publications:  Accommodation Services, Australia; Clubs, Pubs, Taverns and Bars, Australia; Cafes, Restaurants and Catering Services, Australia; Casinos, Australia; Gambling Services, Australia; Performing Arts, Australia; and Sports and Physical Recreation Services, Australia.
• sales that are out of scope of the RIS/WIS survey, which are:
  • flea market sales and sales by NPISH units.
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing units selling directly to the public;
  • a proportion of caravans used as residences is excluded,
  • dealers’ margins for sales of second-hand boats and caravans, excluding transactions between households; and
  • flea market sales.
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of other major durables for recreation and culture are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing units selling directly to the public;
  • sales of ‘backyard’ pure bred pets based on a historical value extrapolated using a growth rate for retail sales of pets and live animals over the last seven years from RIS/WIS;
  • sales of toys and other goods provided by NPISH units; and
  • flea market sales.
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price annual estimates of purchases of other recreational items and equipment are re-valued using relevant price deflators from the Consumer Price Index.

Household expenditure for sporting and recreational services not elsewhere classified is based on historical estimates which are rolled forward by multiplying movements associated with the estimated resident population and the CPI for the sports participation series.

The Household Expenditure Survey provides the primary benchmarks for this series relating to the cost of hiring entertainment equipment and facilities and sporting and educational services.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES; and
• net expenditure overseas.

Current expenditure of NPISHs providing sporting and recreational services is sourced from current grants to NPISH units providing sporting and recreational services. These data are sourced from Government Finance Statistics and current grants and donations from corporations and households to NPISHs units extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Account.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of expenditures on sporting and recreational services are re-valued using relevant price deflators from the Consumer Price Index.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture the final consumption expenditure of NPISH units providing cultural and entertainment services based on current grants information as sourced from the Government Finance Statistics and donations and sponsorship from households and corporations to NPISH units for providing these services extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Account; and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates on Net losses from gambling are sourced from the Australian Gambling Statistics publication (published by the Queensland government). This publication provides comprehensive annual data on gambling in Australia.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• sales of newspapers, books and stationery sourced from irregular ABS publications: Accommodation Services, Australia; Clubs, Pubs, Taverns and Bars, Australia; Cafes, Restaurants and Catering Services, Australia; Casinos, Australia; Gambling Services, Australia; Performing Arts, Australia; and Sports and Physical Recreation Services, Australia.
• sales that are out of scope of the RIS/WIS survey, which are:
  • manufacturing units selling directly to households;
  • sales of books and other goods provided by NPISH units; and
  • flea market sales.
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture current grants from government to NPISH units providing education services sourced from annual time series data from Government Finance Statistics;
• to capture current grants and donations from corporations and households to NPISH units providing education services extrapolated from benchmark data in the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Accounts; and
• net expenditure overseas.

The household expenditure associated with the tertiary education services Higher Education Loan Program (HELP) was derived from time series data on HELP provided by the Department of Education.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Annual volume estimates for education are estimated in conjunction with direct volume estimates for education output, as described in Chapter 9, Table 9.29.

The sources used are total numbers of students at both private and government schools, student load of universities, course hours for TAFE and other vocational education providers stratified at various levels of education and weighted together by their respective current price value of expenditures.

Student numbers are sourced from the ABS publication, Schools; annual reports from the departments of Education and Employment and Workplace Relations for school and university students; and data from the National Centre for Vocational Education Research (NCVER) for vocational students.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture current grants from government to NPISH units providing catering services as sourced from annual time series data from Government Finance Statistics, and
• to capture current grants and donations from corporations and households to NPISH units providing catering services as extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Accounts; and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

The Household Expenditure Survey provides the primary benchmarks for this series.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture current grants from government to NPISH units providing accommodation services as sourced from annual time series data from Government Finance Statistics, and
• to capture current grants and donations from corporations and households to NPISH units providing accommodation services as extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Accounts; and
• net expenditure overseas.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Expenditures on accommodation services by Australian residents are re-valued using relevant price deflators from the Consumer Price Index.

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for the series relating to personal outlays on personal care products such as perfume, cosmetics and soap.

The Household Expenditure Survey (HES) provides the benchmarks for miscellaneous services including hair dressing and beauty salon services.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • sales on aircraft and ships; and
  • flea market sales.
• coverage for remote and non-private dwellings which are not in scope of the HES;
• current grants from government to NPISH (sourced from annual Government Finance Statistics); and
• net expenditure overseas.

For the years where RIS/WIS and HES data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS and HES benchmarks become available a linear interpolation technique is used to align the current estimates to best fit the linear model between the benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Expenditures on personal care by Australian residents are re-valued using relevant price deflators from the Consumer Price Index.

Personal effects

The periodic Retail and Wholesale Industry Survey (RIS/WIS) provides the primary benchmarks for this series relating to personal outlays on jewellery and watches etc.

The following scope and coverage adjustments are made:

• sales that are out of scope of the RIS/WIS survey, which are:
  • sales on aircraft and ships, and
  • flea market sales.
• current grants from government to NPISH (sourced from annual Government Finance Statistics), and
• net expenditure overseas.

For the years where RIS/WIS data are not available the annual estimate is the sum of the four quarters.

When the next RIS/WIS benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Expenditures on personal effects by Australian residents are re-valued using relevant price deflators from the Consumer Price Index.

This is the service charge for insuring householders' furniture and effects, generally called home contents insurance. Insurance of the dwelling itself is excluded from household final consumption expenditure as it is considered to be part of the intermediate consumption of the industry, Ownership of dwellings.

Premiums and claims for Homeowner and Household Insurance are obtained from Quarterly General Insurance Performance Statistics; General Insurance Supplementary Statistical Tables; half-yearly General Insurance Bulletin and Selected Statistics on the General Insurance Industry, published by the Australian Prudential Regulatory Authority (APRA) in quarterly, half-yearly and annual bulletins.

Expected claims are derived by using a centred five-year moving average of claims incurred.

Premium supplements are calculated using the proportion of Homeowner and Household premiums to total general insurance premiums multiplied by total investments earnings on general insurance technical reserves.

Premium supplements are added together with personal premiums to give the total value of premiums.

Personal premiums paid plus premium supplements less expected personal claims incurred gives the value of the service charge which is included in household final consumption expenditure.

Taxes on products are added to derive a purchases price value. Taxes on products are allocated to this product using a number of methods. These include the proportion of GST from net of premiums less claims and the supply proportion of Government taxes on insurance n.e.c. for other taxes on products.

Motor vehicle insurance service charges cover both compulsory third party (personal injury) insurance, and comprehensive and third party property insurance on motor vehicles.

Premiums and claims for motor vehicle property and compulsory third party (personal injury) insurance are obtained from Quarterly General Insurance Performance Statistics; General Insurance Supplementary Statistical Tables; half-yearly General Insurance Bulletin and Selected Statistics on the General Insurance Industry, published by the APRA in quarterly, half-yearly and annual bulletins.

APRA data are classified in a consistent manner to national accounts requirements. Domestic comprehensive motor vehicle insurance is applicable directly to household final consumption expenditure, commercial comprehensive motor vehicle insurance is categorised to business and government. Compulsory third party motor vehicle insurance for householders is obtained by multiplying total compulsory third party motor vehicle insurance by the proportion of personal vehicles to business and government vehicles from the ABS Survey of Motor Vehicle Use, Australia.

Expected claims are derived by using a centred five-year moving average of claims incurred.

Premium supplements are added together with personal premiums to give the total value of premiums for both motor vehicle property and compulsory third party (personal injury) insurance. Premium supplements for each type of motor vehicle insurance are calculated using the proportion of motor vehicle insurance premiums to total general insurance premiums multiplied by total investment earnings on general insurance technical reserves.

Personal premiums paid plus premium supplements less expected personal claims incurred gives the value of the service charge which is included in household final consumption expenditure.

Taxes on products are added to derive a purchases price value. Taxes on products are allocated to this product using a number of methods. These include the proportion of GST from net of premiums less claims and the direct amount of government third party insurance taxes for other taxes on products.

The insurance service charge for health insurance is calculated in the same way as for general insurance of householders' effects.

Information about premiums paid and claims incurred by households from health insurers is sourced from the Private Health Insurance Administration Council publication, Operations of the Registered Health Benefits Organisations.

Expected claims are derived by using a centred five-year moving average of claims incurred.

Personal premiums paid plus premium supplements less expected personal claims incurred gives the value of the service charge which is included in household final consumption expenditure.

 Premium supplements are added together with personal premiums to give the total value of premiums. Premium supplements are calculated by dividing health insurance premiums by total general insurance premiums multiplied by investment earnings on general insurance technical reserves.

The Medicare levy paid by individuals is considered to be an element of income tax levied by the Commonwealth Government. As such, it is not included in household final consumption expenditure.

This is the service charge for various classes of insurance which are taken out by households, but which have not been explicitly discussed above. Included are travel, consumer credit, marine hull, and sickness and accident.

Premiums and claims for the relevant classes of insurance business are obtained from Quarterly General Insurance Performance Statistics; General Insurance Supplementary Statistical Tables; half-yearly General Insurance Bulletin and Selected Statistics on the General Insurance Industry, published by the Australian Prudential Regulation Authority in quarterly, half-yearly and annual bulletins.

The households' share of both premiums and claims for each class of business are estimated using available information and subjective judgement.

Expected claims are derived by using a centred five-year moving average of claims incurred.

Premium supplements are added together with personal premiums to give the total value of premiums.

Premium supplements are calculated using the proportion of households' premiums for the relevant classes of business to total general insurance premiums, multiplied by total investment earnings on general insurance technical reserves.

Personal premiums paid plus premium supplements less expected personal claims incurred gives the value of the service charge which is included in household final consumption expenditure.

Taxes on products are added to derive a purchases price value. Taxes on products are allocated to this product using a number of methods. These include the proportion of GST from net of premiums less claims and supply proportions of government taxes on insurance n.e.c. for other taxes on products.

Premiums and contributions paid by policyholders to life insurance corporations and superannuation are considered to include an insurance service charge element. A proportion of life insurance and superannuation premiums/contributions is actually paid by employers on behalf of their employees. However, for national accounts purposes these premiums are included in employers' social contributions, which is a component of compensation of employees. The employee pays the insurance service charge (a component of household final consumption expenditure) and invests in life insurance and superannuation funds recorded in the household financial account.

For life insurance corporations and friendly societies, the insurance service charge is equal to the cost of running the business plus a profit margin. The service charge is compiled from data on life insurance statutory funds available from Quarterly Life Insurance Performance Statistics; half-yearly Life Insurance Bulletin and the Annual Friendly Society Bulletin, published by the Australian Prudential Regulatory Authority. The profit margin is calculated by estimating a proxy return on equity (where the return on equity is defined as gross operating surplus over shareholders' funds).

For pension funds the insurance service charge is equal to cost of running the fund, included are administrative and investment expenses. The service charge is compiled from data on pension funds available from the ABS publications, Managed Funds, Australia  and Australian National Accounts: Finance and Wealth; and the APRA publications, Superannuation Performance Statistics and the Annual Superannuation Bulletin.

Taxes on products are added to derive a purchases price value. Other taxes on products are allocated to this product using supply proportions of government taxes on insurance n.e.c.

The insurance service charge for workers’ compensation insurance paid by employers is included in household final consumption expenditure. The insurance service charge measures the value of services provided by the insurance enterprises in arranging payments for claims in exchange for the receipts of premiums.

Premiums and claims for the relevant classes of insurance business are obtained from, quarterly General Insurance Performance Statistics; General Insurance Supplementary Statistical Tables; half-yearly General Insurance Bulletin and Selected Statistics on the General Insurance Industry, published by the Australian Prudential Regulation Authority in quarterly, half-yearly and annual bulletins.

Premium supplements are added together with personal premiums to give the total value of premiums. Premium supplements are calculated using the proportion of workers’ compensation insurance premiums to total general insurance premiums, multiplied by total investment earnings on general insurance technical reserves. Personal premiums paid plus premium supplements less expected personal claims incurred gives the value of the service charge which is included in household final consumption expenditure.

Taxes on products are added to derive a purchases price value. Taxes on products are allocated to this product using a number of methods. These include the proportion of GST from net of premiums less claims and supply proportion of government taxes on insurance n.e.c. for other taxes on products.

The initial data is compiled at the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

The SUPC level data are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of insurance services are re-valued using relevant price deflators from the CPI.

The scope of this item is household expenditure, both actual and imputed, on services provided by financial institutions other than insurers. Three broad categories of expenditure are covered.

The first relates to the charges that households pay explicitly to financial institutions for services rendered. Examples are account-keeping fees; commission on money orders, travellers' cheques and overseas drafts; brokerage on share trading; and financial advisers' charges.

The second covers taxes on production and imports levied by general government on financial transactions undertaken by households. Examples are financial institutions duty and stamp duty incurred by trading in financial instruments. The stamp duty payable on the transfer of titles to residential property is treated as part of the transfer costs of ownership of dwellings (which are included in gross fixed capital formation) and as such is not part of household final consumption expenditure.

The last component is the indirectly charged service charges of banks and other similar financial intermediaries. In the national accounts an imputation is made for the value of the services provided by financial intermediaries; that is, Financial Intermediation Services Indirectly Measured (FISIM). It is estimated by reference to the difference in interest rates offered to borrowers and depositors and the average levels of outstanding loans and deposits. The payment for financial services is implicit in both the higher interest paid by borrowers and the lower interest received by depositors. That part of this service which relates to personal loans to households to finance household consumption and household deposits held by financial intermediaries is regarded as being paid by persons and included in household final consumption expenditure. FISIM relating to mortgages on dwellings owned by persons is not included in household final consumption expenditure, but is treated as a component of intermediate consumption in the calculation of gross operating surplus for dwellings owned by persons.

The total value of explicit charges (e.g. account-keeping fees; commission on money orders; travellers' cheques and overseas drafts; brokerage on share trading; and financial advisers' charges) paid by households is calculated using data from the following sources:

• Banks', Credit Unions' and Building Societies' performance statistics published quarterly by the Australian Prudential Regulatory Authority (APRA);
• the Reserve Bank of Australia's Statistical Bulletin;
• suite of APRA forms – quarterly Bank Statement of Financial Performance and quarterly Registered Financial Corporations Statement of Financial Performance; and
• Economic Activity Survey

Taxes on products are added to derive a purchases price value. Taxes and subsidies on products are allocated to specific products using a number of methods. These include household final consumption expenditure proportions in the case of the Goods and Services Tax and supply proportions for other taxes on products.

FISIM is estimated as the difference between the interest rates on loans and deposits and a pure or reference rate of interest, multiplied by the level of loans and deposits, respectively. The total value of FISIM paid by households is calculated using data from the following sources:

• Balance sheets:
  • ABS, Australian National Accounts: Finance and Wealth;
  • Australian Prudential Regulatory Authority (APRA) Monthly Bank Statement of Financial Position– detail breakdown for bank loans and deposits;
  • ABS, Assets and Liabilities of Australian Securitisers; and
  • Reserve Bank of Australia’s (RBA) Statistical Bulletin.
• Income and expenditure:
  • RBA: Annual Report; Financial Stability Report (6 monthly); Statement of Monetary Policy (quarterly);
  • ABS publications: Balance of Payments and International Investment Position; Statistics of Financial Institutions  (note: Statistics of Financial Institutions has ceased but for completeness it is included as the data in this publication still underpins the estimates);
  • ABS collections – Economic Activity Survey, quarterly Survey of Financial Information, Government Finance Statistics;
  • suite of APRA forms – quarterly Bank Statement of Financial Performance and quarterly Registered Financial Corporations Statement of Financial Performance;
  • APRA publications:  quarterly Banks, Building Societies and Credit Unions Performance Statistics; and
  • ad hoc reports: annual reports for small subsectors such as listed investment companies, bank annual reports and private consultant banking reports.
• Interest rates:
  • RBA Statistical Bulletin.

To compile household final consumption expenditure FISIM estimates for banks, other depository corporations and securitisers, the total interest receivable and payable estimates by financial instruments (i.e. deposits, bills of exchange, one-name paper, bonds and loans) and counterparty sector and subsector flows for the following five sectors and subsectors are compiled:

• Rest of the world;
• Reserve Bank of Australia;
• Banks;
• Other depository corporations;
• Securitisers.

Three datasets are required to compile the interest flows, namely:

1. total interest payable and receivable;
2. interest rates for relevant financial instruments for various sectors and subsectors; and
3. balance sheets for the five sectors and subsectors.

The next step is to calculate FISIM for loans and deposits (banks and other depository corporations) and for loans (securitisers). That is:

• For banks and other depository corporations, FISIM is derived as the sum of the counterparty sector and subsector stock levels of loans and deposits; that is:

[(counterparty loan rate – reference rate) * counterparty stock of loans] + [(reference rate – counterparty deposit rate) * counterparty stock of deposits]

where the reference rate is the mid-point between the average interest rate on loans and the average interest rate on deposits.

• For securitisers, FISIM is derived as the sum of the counterparty sector and subsector stock levels of loans; that is:

[(counterparty loan rate – reference rate) * counterparty stock of loan]

where the reference rate is the weighted average bond yield.

The above calculations are undertaken in separate loan and deposit FISIM tables for each of the three FISIM generating institutions. Each table captures the counterparty sector and subsector loan and deposit balances, their respective interest flows and interest margins and the subsequent FISIM estimates.

The FISIM tables mentioned above for loans and deposits enable the allocation of FISIM by final use (i.e. household final consumption expenditure), exports and intermediate use directly.

The initial data is compiled at the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

The SUPC level data are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results. For more information on the product flow method refer to Chapter 7.

Current price estimates of purchases of direct financial services by Australian residents are re-valued using relevant price deflators from the CPI.

The detailed information from the current price FISIM loan and deposit tables for the four financial intermediaries (i.e. banks, other depository corporations, central borrowing authorities and securitisers) are used to construct chain volume measures.

Chain volume FISIM measures are produced for the total, household final consumption expenditure, intermediate use of ownership of dwellings, intermediate use by general government, total intermediate use, exports and imports:

Laspeyres chain volume estimates of balances (loans and deposits) by counterparty sectors and subsectors are calculated by deflating the current price estimates using the All groups CPI.

The deflated loans and deposits are multiplied by the associated interest margin for the previous year to produce estimates of FISIM in prices of the previous year.

The estimates in the previous step are summed across the four financial intermediaries to produce Laspeyres chain volume estimates of total FISIM, final use (i.e. household final consumption expenditure), exports, imports, total intermediate use and dwellings and general government intermediate use.

The Household Expenditure Survey provides the primary benchmarks for miscellaneous services including personal outlays on dry cleaning, photographic services, laundering, removalist services, funeral services and professional services (other than health care services) such as legal and accounting services.

The following scope and coverage adjustments are made:

• coverage for remote and non-private dwellings which are not in scope of the HES;
• to capture current expenditure of NPISH units providing professional services such as other social assistance services not elsewhere classified (including elderly, disabled, marriage and adoption services), legal services as compiled based on current grants from government to NPISH units as sourced from annual time series data from Government Finance Statistics;
• to capture current grants and donations from corporations and households to NPISH units providing childcare services, interest groups not elsewhere classified (including welfare fundraising services) as extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Accounts, and
• net expenditure overseas.

Current expenditure on NPISHs such as religious services are sourced from current grants and donations from corporations and households to NPISH units providing religious services extrapolated from the ABS publication, Australian National Accounts: Non-Profit Institutions Satellite Accounts.

For the years where HES data are not available, the annual estimate is the sum of the four quarters.

When the next HES benchmark becomes available a linear interpolation technique is used to align the current estimates to best fit the linear model between the two benchmarks.

The initial data is compiled according to the COICOP classification. This is mapped to the Input-Output Product Classification (IOPC) level. The IOPC level is then aggregated to the Supply-Use Product Classification (SUPC) level.

Supply and Use balancing process

The HFCE estimates at the SUPC level are inserted into the Use table which is balanced with the Supply table at the product level using the product flow method. Therefore, adjustments are likely to be applied to the initial HFCE estimate to obtain a balance between supply and use. The adjustments are determined by confronting the supply and use data with industry association data, annual reports of significant units within the industry, as well as other relevant ABS survey results.

For more information on the product flow method refer to Chapter 7.

Current price estimates on household expenditures on other goods and services by Australian residents are re-valued using relevant price deflators from the Consumer Price Index.