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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A3.1 Quarterly time series such as those in national accounts publications are affected by three influences - calendar ( mostly seasonal), trend and irregular. When interpreting a quarterly series, it is often helpful to take account of the seasonal and other regular calendar-related influences. The seasonal adjustment process removes these influences, and the remaining (seasonally adjusted) series reflects the trend and irregular influences. The irregular component refers to changes attributable to irregular events such as industrial disputes or lumpy investments. A further statistical process (Henderson smoothing) removes the irregular influence to reveal the trend. This appendix summarises the methods used by the ABS to decompose quarterly national accounts series into their three components.
A3.2 Seasonal effects usually reflect the influence of the seasons themselves, either directly or through production series related to them (such as farm production), or social conventions (such as the incidence of holidays) or administrative practices (such as the timing of tax payments). Other types of calendar variation occur as a result of influences such as the number and composition of days in the calendar period (trading day), accounting or recording practices adopted by businesses, the effect of regular paydays on activity levels or the incidence of movable holidays (such as Easter).
A3.5 The ABS method of seasonal adjustment is the SEASABS (SEASonal analysis to ABS standards) package, a knowledge-based seasonal analysis and adjustment tool. The seasonal adjustment algorithm used by SEASABS is based on the X-11 ARIMA package from Statistics Canada. This in turn is based on the United States Bureau of the Census Method II Seasonal Adjustment Program, X-11 Variant. In the X-11 method, calendar effects, where measurable, are estimated using mainly filtering techniques, and occasionally regression procedures. In certain cases (such as the payment of pensions) additional information may be used to estimate appropriate prior adjustment factors. The estimated seasonal and calendar influences, together with certain prior adjustment factors, provide the combined adjustment factors by which the original series is seasonally adjusted.
A3.8 The SEASABS program allows for the original series to be decomposed into trend, seasonal and irregular components by using a multiplicative, additive or pseudo-additive model. The choice of which of these models to use depends on whether it is more appropriate to consider the amplitudes of the trend, seasonal and irregular components to be proportional to or largely independent of each other. Specifically, the multiplicative model treats all three components as dependent on each other, the additive model treats them independently, and the pseudo-additive model treats the seasonal and irregular components as independent of each other but dependent upon the level of the trend.
A3.10 It is possible to seasonally adjust an aggregate series either directly or by seasonally adjusting a number of its components and adding the results. The latter (aggregative) method has been employed for most of the major aggregates in the national accounts. Besides retaining, as far as possible, the essential accounting relationships, the aggregative approach is needed because many of the aggregates include components having different seasonal and trend characteristics, and sometimes require different methods of adjustment. Details of the methods of adjustment used for each of the quarterly national accounts aggregates are available on request.
A3.11 National accounts series are normally reanalysed annually using data consistent with the June quarter national accounts estimates. On occasions, however, particular components have been reanalysed before the normal time because of one or more of the following conditions:
A3.12 Significant revisions can occur as a result of the annual reanalysis, with the more recent periods likely to be most affected. It is particularly difficult to identify and estimate the trend and seasonal components at times of rapid or abrupt changes in these components.
Interpreting seasonally adjusted series
A3.13 The following points need to be taken into account when using seasonally adjusted statistics:
A3.14 For all these reasons, seasonally adjusted series should not be regarded as 'definitive' or necessarily indicative of underlying economic influences or trends. They must be treated with caution as being no more than useful indicators of movements. Without doubt they can be a useful aid to critical interpretation, but they are not a substitute for it.
The trend estimation process
A3.15 In cases where the removal of only the seasonal element from a seasonally adjusted series may not be sufficient to allow identification of changes in its trend, a statistical technique is used to damp the irregular element. This technique is known as smoothing, and the resulting smoothed series are known as trend series.
A3.18 For more information about ABS procedures for deriving trend estimates and an analysis of the advantage of using them over alternative techniques for monitoring trends, see A Guide to Interpreting Time Series - Monitoring Trends: an Overview (Cat. no. 1348.0).
This page first published 15 November 2000, last updated 29 June 2012
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