Sources and methods - Quarterly
9.91 Gross value added in chain volume measures are derived by interpolating and extrapolating annual benchmarks using quarterly indicator series. Both the annual benchmarks and the quarterly indicators are calculated as chain volume measures.
9.92 Quarterly chain volume indicators of gross value added in the ASNA are derived using three different methods:
- the output indicator method;
- double deflation; and
- the input indicator method.
9.93 The method selected to obtain chain volume measures for a particular industry depends on the data available in respect of that industry. The most commonly used method is the output indicator method. However, Agriculture uses the double deflation method. The input indicator method involves extrapolation using a measure of labour input such as hours worked and is used to obtain estimates for the Public administration and safety industry.
9.94 The use of output or input indicator methods is based on the implicit assumption that movements in output and intermediate use are consistent with each other. Whilst this is almost certainly not the case in practice, the assumption is made owing to limitations of quarterly source data as well as the time available for compilation and editing. Double deflation is applied to Agriculture as prices and volumes for both agricultural inputs and outputs can be highly volatile. This level of volatility does not exist for other industries and, while it is arguable that quarterly double deflation would improve the estimates of GDP(P) for other selected industries, it is not clear the improvement would be significant.
9.95 The output indicator method is the most commonly used by the ABS. It involves extrapolating reference year estimates of current price gross value-added using movements in a volume indicator of output. It assumes that the ratio of gross output volumes to intermediate input volumes remains constant over time. In a few cases the output indicator is just a single statistic, but in most cases, it is a combination of several statistics. In no cases do these output statistics precisely meet the national accounts definition of output, but in most cases, they approximate the national accounts definition reasonably closely. In some cases, the output statistics are merely highly correlated with the national accounts definition of output, as when turnover data are used as the output indicator for wholesale and retail trade. The principal output of these industries is their margin on the goods they sell (the margin is the difference between the price at which goods are sold and the price at which those goods are bought by the wholesaler or retailer). When a margin volume is estimated using a turnover volume as the indicator, the underlying assumption is that the ratio of the margin to the turnover volume is fixed over time.
9.96 Most industries produce many different commodities, and the ratio of output to value added can differ appreciably between industries and over time. Hence, in constructing a composite output indicator to be used as an indicator of growth in real value added, it is best for the constituent output statistics to be weighted together using current price value added data, and for re-weighting to occur as frequently as possible. The availability of current price value added data varies considerably between industries.
9.97 The volume estimates of gross value added for each industry are derived in the prices of the previous year. Chaining takes place after aggregation.
9.98 Quarterly current price sales data reported by survey respondents are aligned to concepts embedded in the Australian equivalents to International Financial Reporting Standards (AIFRS), net of the Goods and Services Tax (GST), and net of any discounts provided. In addition to income from sales of physical goods, sales estimates include sales of services, including consulting services, income from exports, income from leasing and hiring, income from contracts and commissions, sponsorship income, management fees and charges, income from operating leases, delivery charges, income from royalties pertaining to original artistic works, and billed progress payments from long-term contractual arrangements. They exclude items such as interest income, sales of assets, income from finance leases, payments under hire purchase arrangements, and royalties received in respect of natural resource ownership.
9.99 Inventories are also recorded according to AIFRS, and are closing book values, exclusive of GST, measured before deduction of provisions for losses. These also cover domestic activity only, and are collected according to three categories:
- Inventories of raw materials – this includes materials and fuels designed to be consumed in productive activities, non-capitalised spare parts designated for use in fixed assets, and containers and packaging materials. Inventories of fuels for sale are excluded (these are classified as inventories of finished goods).
- Inventories of work-in-progress – this includes partially processed or fabricated goods which will be further processed prior to sale, and general work-in-progress less payments billed. Prepayments are excluded.
- Inventories of finished goods – this includes goods manufactured or processed which are ready for sale, goods purchased from other businesses which are ready for resale without further processing, and fuels for sale. Hired goods, inventories of land, and rented or leased buildings are excluded.
9.100 For many industries, quarterly industry gross value added is estimated in the latest year by making two assumptions: firstly, that sales growth is a proxy for output growth (in the case of manufacturing, growth in sales plus change in inventories (excluding raw materials) is a proxy for output growth), and that, if we assume movements in output and intermediate consumption are consistent with each other, that output growth is a proxy for growth in gross value added. This is the essence of the output indicator method.
9.101 Ideally, output growth would be better approximated by sales growth plus change in inventories (excluding raw materials) for all industries relying on QBIS data. However, change in inventories is only included for the derivation of estimates for manufacturing. See Table 9.44 for the rationale.
9.102 The tables below outline the data sources and methods used in the extrapolation of quarterly gross value added chain volume estimates by industry from the balanced annual supply and use data, as well as the quarterly distribution of annual supply and use estimates.
| Item | Comment | ||
|---|---|---|---|
| General | |||
Updating of source data: Annual data from the ABARES publication, Agricultural Commodities are revised during the March quarter with the release of the ABS publication, Value of Agricultural Commodities Produced, Australia. During this process, the new farm forecast for the current year provided by the Australian Bureau of Agricultural and Resource Economics and Sciences is incorporated into the time series. Quarterly apportionment of annual data: Annual data are split across the four quarters using weights that reflect the estimated production of that commodity throughout the year; for example, wheat is harvested in December and March quarters, not in June or September quarters. For some commodities quarterly data sources are available, including: sheep, lambs, cattle, calves, pigs, poultry, goats, milk, and wool. | |||
| Gross Output | |||
| Livestock | |||
| Sheep, lambs, cattle & calves | |||
| Gross value of production for sheep, lambs, cattle and calves is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities publication, and quarterly data from the ABS publication, Livestock Products, Australia. | |||
| Pigs, deer, poultry for slaughtering and egg laying hens | |||
| Gross value of production for pigs, deer, poultry for slaughtering and egg laying hens is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities and quarterly data from the ABS publication, Livestock Products, Australia. | |||
| Pets and live animals n.e.c. | |||
| Gross value of production for pets and live animals n.e.c. is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities, and quarterly data from the ABS publication, Livestock Products, Australia. | |||
| Milk, eggs and honey | |||
| Milk | |||
| Gross value of production for milk is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities and monthly quantity data from Dairy Australia, Milk Production Reports. | |||
| Eggs and honey | |||
| Gross value of production for eggs is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. Data for honey is no longer available in ABS cited above; ABARES estimates are used instead. | |||
| Grains | |||
| Wheat | |||
| Gross value of production for wheat is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | |||
| Barley, oats, rice, sorghum & cereal grains n.e.c. | |||
| Gross value of production for barley, oats, rice, sorghum and cereal grains n.e.c. is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | |||
| Other grains n.e.c. | |||
| Gross value of production for other grains n.e.c. is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | |||
| Total other crops | |||
| Fodder & grass | |||
| Gross value of production for fodder and grass is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | |||
| Plants & flowers | |||
| Gross value of production for plants and flowers is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | |||
| Fruit, nuts & vegetables | |||
| Gross value of production for fruits, nuts and vegetables is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | |||
| Sugar cane | |||
Gross value of production for sugar cane is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | |||
| Other agriculture (includes cotton, wine grapes, hops and tobacco output (Note: tobacco production ceased in Australia in 2006-07)) | |||
| Gross value of production for other agriculture is estimated using price and quantity data from the ABS publication, Value of Agricultural Commodities Produced, Australia, supplemented by annual data from the ABARES publication, Agricultural Commodities. | ||
| Miscellaneous agriculture | |||
| Sheep & beef cattle agistment services | |||
Gross value of production for sheep and beef cattle agistment services is derived using the gross value of production of sheep, lambs, cattle and calves. | |||
| Livestock products n.e.c., horse agistment services | |||
Gross value of production for livestock products n.e.c. and horse agistment services is estimated using price and quantity data published in the ABARES publication, Agricultural Commodities. | |||
| Non-agricultural products (production which is secondary to agriculture) | |||
| Gross value of Agriculture industry production for non-agricultural products (e.g. maintenance of farm infrastructure such as barns and fences, on-farm meat processing, road freight transport etc.) is derived from the growth in the value of total agricultural production. | |||
| Intermediate use | |||
| Marketing costs | |||
| Wheat | |||
| Marketing costs are derived from the ABS publication, Value of Agricultural Commodities Produced, Australia supplemented by annual data from ABARES publication, Agricultural Commodities. They are calculated by taking the local value of production of wheat from the gross value of production. | |||
| All other | |||
Marketing costs are derived from the ABS publication, Value of Agricultural Commodities Produced, Australia supplemented by annual data from ABARES publication, Agricultural Commodities. They are calculated by taking the local value of production for a commodity from the gross value of production. | |||
| Seed & fodder | |||
| Seed costs are derived using data from ABARES publication, Agricultural Commodities, for area sown multiplied by corresponding seeding rates multiplied by the price per tonne. Fodder costs are derived as a residual after deducting the value of exports and non-fodder uses for these products from the gross value of production. | |||
| Other input costs | |||
| Historical data for farm costs such as chemicals, electricity, fuel and maintenance are moved forward using data from the ABARES publication, Agricultural Commodities. These data were originally collected in the ABS Agricultural Finance Survey (AFS), but this collection ceased in 2001. | |||
| Item | Comment | |
|---|---|---|
| Gross value added | ||
| The double deflation method is used. Prior to chaining, volume measures of output and intermediate use in the prices of the previous year are derived, as described below, with the difference between the two components being the gross value-added volume. | ||
| Gross output | ||
| Volume measures of output in the prices of the previous year for most commodities are derived by quantity revaluation. Volume measures of output in the prices of the previous year for the remaining commodities are derived by deflation using implicit price deflators obtained for similar commodities. | ||
| Intermediate use | ||
| The sum of marketing costs, fodder, seed, fertiliser and other intermediate inputs (fuel, maintenance of plant and structures, chemicals, insurance, etc.), as described below. | ||
| Marketing costs | ||
| Volume estimates in the prices of the previous year are derived for 13 commodity groups by using chain volume measures of the output of each group to extrapolate the previous year's current price value and then summing the results. | ||
| Fodder & seed | ||
| Components are re-valued using price indexes derived from unit price data which have been adjusted in some cases to allow for timing differences between production of the commodities and their use as fodder or seed. | ||
| Other intermediate inputs | ||
| Fertiliser volume estimates in the prices of the previous year are derived by quantity revaluation. For other components, current price estimates are re-valued using the relevant component indexes from Index of Prices Paid by Farmers in the ABARES publication, Agricultural Commodities. | ||
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by linear trend interpolation of annual estimates. Annual volume estimates are obtained by quantity revaluation of the major commodities using quantity data from Agricultural Commodities published by the Australian Bureau of Agricultural and Resource Economics and Sciences. Note that commercial fishing activities reflect only part of ANZSIC Subdivision 04. There is no quarterly data source to reflect the remainder of this ANZSIC subdivision; that is, hunting and trapping. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by linear trend interpolation of annual estimates. Annual volume estimates in the prices of the previous year are derived by quantity revaluation using current price gross value of production and production quantities for total softwood and hardwood logs as published in ABARE's Agricultural Commodities. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by price deflation of current price values for cotton ginning, shearing and other services. Shearing current price values are estimated using quarterly estimates of the value of shorn wool production. Cotton ginning and other services are estimated using annual production values for cotton and total farm production, respectively, from the ABARES publication, Agricultural Commodities. These are then averaged across the four quarters of the year to derive the quarterly current price values. Cotton ginning and shearing price indexes are based on the hourly wage rates while the other services price deflator is the All groups CPI. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. A quarterly output indicator is production tonnage collected on the ABS Supplementary Survey of Mining Inventories and Production Volumes. Prior to September quarter 2019, coal volume measures were estimated using production values from the Department of Industry, Science, Energy and Resources. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. The primary data source is monthly production volumes of oil and gas, published by the Department of Industry, Science, Energy and Resources. in the publication, Australian Petroleum Statistics. The specific output indicators used are (a) total crude oil and condensate, in megalitres; (b) ethane, in millions of cubic metres; and (c) natural gas, in millions of cubic metres. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. The Department of Industry, Science, Energy and Resources provides quarterly production estimates of copper (kilotonnes), nickel (kilotonnes), zinc (kilotonnes) and gold (tonnes) produced. These estimates are preliminary and unpublished at the time the quarterly national accounts are compiled, but are subsequently published by the department in Resources and Energy Statistics. Revisions to the published data are subsequently incorporated into the quarterly national accounts. The Department of Industry, Science, Energy and Resources publication, Resources and Energy Statistics provides the output indicator data for other commodities such as bauxite, alumina, tin, silver, uranium and manganese, as well as mineral sands such as ilmenite, rutile and zircon. Data relating to these commodities are generally not available for the most recent quarter. A preliminary estimate for the current quarter is generated for each of these commodities using a simple average of production for the same quarter in the recent past. These preliminary estimates are then replaced by data published by the department in the subsequent quarter. Revisions in the published data are also incorporated. Weights applied to each commodity within this industry are derived from the ABS publication, Australian Industry. ANZSIC classes not covered by an output indicator as described above are assumed to have the same quarterly growth rate as the classes that are measured. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. A quarterly output indicator is production tonnage collected on the ABS Supplementary Survey of Mining Inventories and Production Volumes. Prior to September quarter 2019, iron ore volume measures were estimated using production values from the Department of Industry, Science, Energy and Resources. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy for output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales plus change in inventories (work-in-progress and finished goods) from Business Indicators: Australia and applying the same level of growth. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. The inclusion of change in inventories generates a more conceptually correct measure of output growth than just growth in sales. Change in inventories is only included in the quarterly output indicator for manufacturing because, for all other industries relying on Business Indicators: Australia, change in inventories is small when compared with sales volumes (and for most service industries, inventories of work-in-progress and finished goods are so insignificant they are not measured). | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Volume measures, in the prices of the previous year, are obtained by revaluing quantity data for a range of petroleum and coal products, published by Department of Industry, Science, Energy and Resources in Australian Petroleum Statistics. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Electricity produced in New South Wales, Victoria, Queensland, Tasmania, South Australia and Western Australia is obtained from the Australian Energy Market Operator (AEMO). Electricity produced in the ACT and NT is excluded from the indicator series, and therefore not reflected in the quarterly growth rates. These two jurisdictions comprise less than one per cent of national output, so that the extra effort to incorporate them would not result in materially improved statistical output. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from the Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy for output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. The current price indicator series is quarterly sales revenue data for public authorities classified to the water services industry, sourced from the Government Finance Statistics collection. The indicator series is not published in its own right. The volume data are derived by deflating this current price data with the same deflator applied to Business Indicators: Australia sales for water services which is then chained. The reason QBIS data is not used to measure water services on a quarterly basis is that most water services units are classified to the public sector, and are therefore out of scope of Business Indicators: Australia. The choice to use Government Finance Statistics instead of Business Indicators: Australia means that any privately-owned water services units, such as regional irrigators, are not reflected in the quarterly growth rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy for output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Volume measures of the value of work done for non-residential building construction and heavy and civil engineering construction are compiled using volume indicators sourced from ABS publications, Building Activity, Australia and Engineering Construction Activity, Australia, whereas residential building construction volume measures are compiled using volume indicators derived from private gross fixed capital formation. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy for output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia and applying the same level of growth. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. Measuring gross value added for the wholesale trade industry is problematic on a quarterly basis. Conceptually, output for the wholesale trade industry is equal to the margin between the value at which goods are acquired and at which goods are on-sold, after allowing for inventory valuation adjustments. However, there are no appropriate data sources for measuring wholesale trade margins on a quarterly basis. Additionally, to derive volumes of margins, price indexes which are directly applicable to measurement of change in margins would be required, but these also do not exist. In using Business Indicators: Australia, sales chain volume growth rates as an indicator of growth in gross value added, the additional assumption is made that margins volumes move in line with sales volumes. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Estimates of growth in gross value added for motor vehicle retailing and fuel retailing are based on growth in current price expenditure data for purchase of vehicles, and operation of vehicles, by households. These are deflated and chained to create a chain volume indicator series. This assumes that growth in these household expenditure categories is a reliable proxy for output growth, and that growth in output and intermediate consumption occur at identical rates. Measuring gross value added for the Retail trade industry is problematic on a quarterly basis. Conceptually, output for the Retail trade industry is equal to the margin between the value at which goods are acquired and at which goods are on-sold, after allowing for inventory valuation adjustments. However, there are no appropriate data sources for measuring retail trade margins on a quarterly basis. Additionally, to derive volumes of margins, price indexes which are directly applicable to measurement of change in margins would be required, but these also do not exist. In using the household expenditure chain volume growth rates as an indicator of growth in gross value added for retail trade in motor vehicles, the additional assumption is made that margins volumes move in line with expenditure volumes. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Estimates of growth in gross value added for these ANZSIC subdivisions are based on quarterly volume turnover growth rates published quarterly in the ABS publication, Retail Trade, Australia. This assumes that growth in these retail turnover categories is a reliable proxy for output growth, and that growth in output and intermediate consumption occur at identical rates. Measuring gross value added for the Retail trade industry is problematic on a quarterly basis. Conceptually, output for the Retail trade industry is equal to the margin between the value at which goods are acquired and at which goods are on-sold, after allowing for inventory valuation adjustments. However, there are no appropriate data sources for measuring retail trade margins on a quarterly basis. Additionally, to derive volumes of margins, price indexes which are directly applicable to measurement of change in margins would be required, but these also do not exist. In using the Retail Trade chain volume turnover growth rates as an indicator of growth in gross value added, the additional assumption is made that margins volumes move in line with turnover volumes. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Private sector activity is measured using sales data, in current and constant prices, from the Quarterly Business Indicators Survey. Public sector activity is measured using expenditure on rail fares as reflected in household final consumption expenditure, in current and constant prices. The current and constant price values for public and private are aggregated to form total current and constant price values for rail transport. These are then chained to form the indicator for the whole ANZSIC subdivision. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. A quarterly output indicator is compiled in-house, based on data from a survey of revenue passenger kilometres and freight tonne kilometres from the major domestic and Australian-based international airlines. The term revenue passenger kilometres is a measure of traffic and is derived by multiplying the number of revenue-paying passengers by distances travelled. Calculations are made by the providers. Revenue passenger kilometres is considered to be a more accurate volume estimator for output given it is a combined measure of distances travelled as well as passengers carried. The same measurement principle applies for deriving freight tonne kilometres. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Private sector activity (reflecting private courier services, etc.) is measured using the sales data from Business Indicators: Australia, in current and constant prices. Public sector activity is measured using a variety of indicator data from providers on sales revenue in current prices, as well as quantities of letters and parcels carried. The current and constant price values for public and private are aggregated to form total current and constant price values for this ANZSIC subdivision. These are then chained to form the indicator for the whole subdivision. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. Telecommunications Services also includes quarterly sales revenue data from Government Finance Statistics. The volume data are derived by deflating the sales revenue data using price deflators. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Chain volume measures for quarterly bank financial intermediation services indirectly measured (FISIM) are compiled using bank balance sheets; detailed breakdown for bank loans and deposits (Australian Prudential Regulatory Authority (APRA) Monthly Banking Statistics); income and expenditure (Suite of APRA forms - Quarterly Bank Performance Statistics); and indicator interest rates (RBA Statistical Bulletin). The methodology is the same as described for the annual benchmarks for FISIM. Chain volume estimates of bank FISIM are the quarterly indicator series for gross value added. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Current price estimates of the Insurance service charge (ISC) are compiled as follows:
A weighted sum of the three components is derived to produce a quarterly current price indicator of the ISC. This is deflated using the All groups CPI index and chained to produce a chain volume series. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia, and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the input indicator method. The sales data from Business Indicators: Australia are not appropriate for measuring gross value added for division O because of the large proportion of non-market activity in this division. Aggregate hours worked in Division O, is the main data source. Defence is out of scope of the LFS so additional hours worked estimates for Defence are added to the LFS estimates to obtain total hours worked. | |
| Item | Comment |
|---|---|
| Gross value added | |
| No appropriate quarterly indicator currently exists. Quarterly growth is estimated via linear trend interpolation of the annual estimates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Private sector activity is expenditure by households on private health services, excluding pharmaceuticals, sourced from the household final consumption expenditure dataset, re-expressed as a volume index. Public sector activity is captured through data received from Medicare Australia, which reflects health services classified by broad type of service. The number of the various services provided are weighted together to produce a total volume index. Public and private outputs are expressed as volume indexes because the units of measurement in the original source data are not consistent. The public sector data are derived from numbers of services performed whereas the private sector data uses dollar values of household expenditures as the starting point. These resulting volume indexes are re-weighted (approximately two-thirds public, one-third private) to derive a weighted volume index for the industry. This is then chained to create output in chain volume terms for the whole industry. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. Private sector activity is measured via the sales data from Business Indicators: Australia, in current and constant prices. Annual current price estimates for public sector expenditure on recreation and culture are obtained from Government Finance Statistics and re-valued by the implicit price deflator for non-defence government final consumption expenditure. Quarterly estimates are obtained by linear trend interpolation of the annual estimates. An adjustment was made for the one-off impact of the Sydney Olympic Games in 2000. Current and constant price estimates for the public and private sectors and for the Sydney Olympic Games are summed to form total current and constant price values for this division. These are then chained, with the resulting chain volume being the indicator for the whole industry. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. This involves extrapolating the quarterly series by taking a chain volume measure of sales growth from Business Indicators: Australia and applying the same level of growth to industry gross value added. This assumes that sales growth is a reliable proxy of output growth, and that growth in output and intermediate consumption occur at identical rates. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. The chain volume of the 'Rent and other dwelling services' component of household final consumption expenditure is the output indicator for Ownership of dwellings. | |
| Item | Comment |
|---|---|
| Gross value added | |
Quarterly volume measures are derived by the output indicator method. A range of individual taxes and subsidies on products is used to extrapolate supply and use benchmarks for taxes on products and subsidies on products. Taxes include the Goods and Services Tax (GST), gambling taxes, insurance taxes, excises on petroleum, import duties and tobacco and alcohol taxes. Subsidies include those payable under the Fuel Tax Credits scheme, as well as subsidies payable to bus, tram and rail operators. Current price estimates are sourced from the annual Government Finance Statistics dataset and are smoothed evenly across the four quarters of the year to which they relate. Constant price estimates are obtained from the quarterly household final consumption expenditure dataset, with the exception of import duties, which are mainly sourced from the International Trade in Goods and Services dataset. When calculating GST in constant prices, consumption categories which are exempt from GST (e.g. raw food) are excluded from the calculation. GST relating to the purchase of dwellings is included. Each individual type of tax and subsidy is quantity re-valued. The constant price measures for each tax and subsidy are aggregated allowing the creation of separate chain volume measures of taxes and subsidies. The constant price value for net taxes is derived by subtracting the constant price measure of subsidies from the constant price measure of taxes, and the result is chained to create the chained volume indicator series. | |
9.103 Backcast quarterly gross value added chain volume estimates – prior to the period covered by annual S-U benchmarks (i.e. June quarter 1994 and earlier) on an ANZSIC06 basis – are compiled by backcasting growth from the most applicable series under the previous ANZSIC93 industry classification.