Australian Bureau of Statistics 

5216.0  Australian National Accounts: Concepts, Sources and Methods, 2000
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 15/11/2000 
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Introduction 13.1 This chapter discusses the methods used to derive annual benchmarks and quarterly estimates for relevant aggregates in the gross domestic product account in current price and chain volume terms. 13.2 The supply and use (SU) tables provide annual benchmarks for the major current price aggregates included in the gross domestic product account for all years from 199495 (except for the latest financial year, for which SU tables are not available). SU tables were first compiled in respect of 199495. As explained in Chapter 12, three versions of the SU tables are compiled in respect of each financial year. Consequently, the annual current price estimates are revised progressively for three years, as more complete information becomes available to construct the successive SU tables for a particular financial year. Quarterly estimation methods 13.7 Four general methods are used to compile quarterly current price national accounts estimates for Australia:
A brief description of each is provided below. Quarterly estimation methods  direct sources 13.8 The preferred method of compiling quarterly national accounts estimates is to use a high quality data source which provides data for the aggregate being measured according to the conceptual basis required for the national accounts. In such cases both the quarterly and annual estimates may be compiled from the same source, the annual estimates being obtained simply as the sum of the quarterly estimates. The new dwellings component of private gross fixed capital formation on dwellings is an example of where this method is applied. Quarterly estimation methods  indicators (pro rata) 13.9 In many cases the quarterly data sources used to compile the national accounts are less reliable, less detailed and/or less appropriate than those used for compiling the annual national accounts benchmarks for particular aggregates. Consequently, indicator series are used to allocate (on a pro rata basis) annual estimates for such aggregates to the quarters of each financial year, and to extrapolate forward for the quarters of the latest incomplete year. The quality of estimates compiled using this method will depend on how closely the indicator series relates to the required national accounts aggregate. If the indicator series is very closely related to the national accounts aggregate that it is being used to estimate, this method will provide good quality quarterly estimates. However, if the correlation between the indicator series and the national accounts aggregate is volatile, this method would provide relatively poor quarterly national accounts estimates. A particular problem that arises when using the indicators (pro rata) method is that the September quarter estimates can be adversely affected by what is known as the 'step problem'. A significant step problem will arise if the relationship between the annualised indicator series and the annual benchmark estimates varies significantly between any two consecutive financial years. In effect, the difference in the annual relationship between the benchmark and the indicator series is largely reflected in just the September quarter. This problem is reduced by using the 'benchmark' procedure discussed in the paragraph 13.10. Given the obvious advantage of using the 'benchmark' procedure, the pro rata method is generally only used in a limited number of cases where the step problem is not significant. Quarterly estimation methods  indicators (using 'benchmark') 13.10 This method of deriving quarterly estimates involves applying a mathematical technique that maintains the movements in the indicator series for all quarters as far as possible, but with the constraint that the sum of the quarterly estimates for each financial year must equal the corresponding annual benchmark estimate. In effect, instead of all the differences in the relationship between the annualised indicator series and the benchmark series being reflected in the September quarter, as would occur if the simple pro rata method was used, the differences are distributed across all quarters (see also paragraph 13.3 above). Quarterly estimation methods  trend interpolation with or without specific annual forecasts 13.11 Where there are no quarterly direct data sources or indicator series available it is necessary to generate a quarterly time series by adopting the most appropriate allocation procedure. One possible method would be to divide the annual estimate by four, but this would result in steps each September quarter and no change in the other three quarters. The method used in the ASNA is to apply a linear interpolation method to calculate quarterly time series from annual series. The procedure involves forecasting annual estimates for two extra years, using a weighted average of the movements in year t1 and year t. However, if information is available which provides a superior forecast for the annual estimates for those two years, such forecasts are used in preference to the standard projection produced by the interpolation procedure. A mathematical representation of the trend interpolation procedure is provided in Appendix 6. This method is particularly appropriate for series such as consumption of fixed capital, where only annual estimates are available and where it is reasonable to expect that movements in the quarterly series will be relatively smooth. 13.12 The annual SU tables are compiled in both current prices and in the prices of the previous year. The latter, which are compiled from 199596, are used to benchmark the quarterly chain volume estimates of the gross domestic product account in exactly the same way as their current price counterparts. Estimates for the latest financial year are obtained by aggregating the quarterly estimates which are derived by extrapolation from the latest annual benchmarks, in just the same way as the current price estimates.
This page first published 15 November 2000, last updated 29 June 2012
