5206.0.55.004 - Information Paper: Quarterly Current Price Gross Value Added by Industry , 2016  
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 12/05/2016  First Issue
   Page tools: Print Print Page Print all pages in this productPrint All


On the production side, the ABS currently compiles quarterly GVA by industry for chain volume measures (CVM) only. These estimates are compiled by distributing the annual chain volume measures of GVA by industry into quarters using the “Output Indicator Method”. This method assumes that the ratio between output and intermediate usage does not vary drastically from quarter to quarter. Based on this assumption, indicators of output, such as sales and turnover, are used to obtain the quarterly CVM GVA estimates.

On the income side, the components of GDP(I) are compiled in current prices, with no industry dimension. GDP(I) at current prices is deflated using the Implicit Price Deflator (IPD) from the expenditure measure of GDP to obtain a chain volume estimate.

A current price estimate of GVA can be compiled from the income measure of GDP under the conceptual relationship that GVA can be distributed as either factor incomes or as flows to Government. This relationship is represented as follows:

Current Price GVA =

Compensation of employees (COE)

+ Gross operating surplus (GOS) and Gross mixed income (GMI)

+ Other taxes on production

- Other subsidies on production

Using this approach, industry level estimates can be developed providing an industry dimension to the income estimates on a quarterly basis.

The development of a current price (CP) measure of GVA provides another confrontational tool for the compilation of GDP through the derivation of a GVA IPD. Although conceptually value added cannot be priced as it is the representation of the difference between output and intermediate usage, an IPD developed from GVA can be used as a tool to measure the coherence of the income and production measures.

IPDs are obtained by dividing a current price measure by its corresponding chain volume measure. IPDs are derived measures (hence the term 'implicit') and are not normally direct measures of price change by which current price estimates are converted to estimates at constant prices.

When calculated from the major national accounting aggregates, such as GDP, IPDs relate to a broader range of goods and services in the economy than that represented by any of the individual consumer and producer price indexes published by the ABS. These IPDs provide an estimate of both changes in price and changes in the composition of the aggregates represented.

A limitation of the GVA IPD is the possibility for changes in the composition of the relevant aggregate to produce an increase in the IPD between two non-base periods when all component prices have decreased or, conversely, a decrease in the deflator when all component prices have increased. While these may be extreme cases, from time to time significant aberrations do occur in practice. These limitations mean that the movement in an individual GVA IPD between two quarters should not be taken as a measure of price change in isolation from other relevant information that may be available.

Chain volume measure and CP GVA, and the resulting IPDs, are produced at an industry level allowing for more detailed confrontation and the source of any discrepancy to be identified to a particular industry. For example, the movements in the IPD for Mining can be compared to movements in commodity prices such as iron ore and coal by taking into account potential compositional effects. Variations observed between them can lead to further analysis of the source data to determine the source of the discrepancy.

There are some limitations to using this framework as a confrontation tool. One of these is the difficulty in finding comparable price indicators for some service industries such as Financial and insurance services, Professional, scientific and technical services, and Administration and support services. However, they still provide a good basis to analyse the quality of the estimates.