Australian Bureau of Statistics
5676.0 - Business Indicators, Australia, Mar 2012
Previous ISSUE Released at 11:30 AM (CANBERRA TIME) 04/06/2012
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8 In the Quarterly Business Indicators Survey the statistical unit used to represent businesses, and for which statistics are reported, is the Australian Business Number (ABN) unit, in most cases. The ABN unit is the business unit which has registered for an ABN, and thus appears on the ATO administered Australian Business Register. This unit is suitable for ABS statistical needs when the business is simple in structure.
9 For more significant and diverse businesses where the ABN unit is not suitable for ABS statistical needs, the statistical unit used is the Type of Activity Unit (TAU). A TAU is comprised of one or more business entities, sub-entities or branches of a business entity within an Enterprise Group that can report production and employment data for similar economic activities. When a minimum set of data items is available, a TAU is created which covers all the operations within an industry subdivision (and the TAU is classified to the relevant subdivision of the Australian and New Zealand Standard Industrial Classification (ANZSIC)). Where a business cannot supply adequate data for each industry, a TAU is formed which contains activity in more than one industry subdivision and the TAU is classified to the predominant ANZSIC subdivision. The businesses that contribute to the statistics in this publication are classified:
10 The Australian and New Zealand Standard Industrial Classification has been developed for use in both countries for the production and analysis of industry statistics. For more information, users are referred to Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 (cat. no. 1292.0).
11 In order to classify data by industry, each statistical unit (as defined above) is classified to the Australian and New Zealand Standard Industrial Classification industry in which it mainly operates.
12 The survey is conducted by mail on a quarterly basis. It is based on a random sample of approximately 16,000 units which is stratified by industry, state/territory and number of employees. All private sector units with over 300 employees, and other statistically significant units, such as joint venture partners, are included in the sample.
13 Respondents are asked to provide data on the same basis as their own management accounts. Where a selected unit does not respond in a given survey period, a value is estimated. If data are subsequently provided, the estimated value is replaced with the reported data. Aggregates are calculated from all data using the ‘number raised’ estimation technique. Data are edited at both individual unit level and aggregate level.
TIMING OF SURVEY CYCLE
14 Surveys are conducted in respect of each quarter and returns are completed during the eight or nine week period after the end of the quarter to which survey data relate e.g. December quarter survey returns are completed during January and February.
15 The survey frames and samples are revised each quarter to ensure that they remain representative of the survey population. The timing for creating each quarter’s survey frame is consistent with that of other ABS business surveys. This provides for greater consistency when comparing data across surveys.
16 Additionally, with these revisions to the sample, some of the units from the sampled sector are rotated out of the survey and are replaced by others, to spread the reporting workload equitably.
17 The quarterly original estimates in this publication are affected in varying degrees by seasonal influences. The seasonal adjustment process estimates and removes the effects of normal seasonal variations from the original estimates so that the effects of other influences can be more clearly recognised.
18 In the seasonal adjustment process, account has been taken of both normal seasonal factors (e.g. increase in retail sales due to the Christmas period) and also trading day effects when significant (arising from the varying lengths of the quarters and the varying numbers of Sundays, Mondays, Tuesdays etc. in each quarter) to produce the seasonally adjusted estimates. Particular care should be taken in interpreting quarterly movements in the seasonally adjusted estimates because seasonal adjustment does not remove the effect of irregular or non-seasonal influences (e.g. change in interest rates) and reflects the sampling and other errors to which the original estimates are subject.
19 In this publication, the seasonally adjusted estimates are produced by the concurrent seasonal adjustment method which takes account of the latest available original estimates. This method improves the estimation of seasonal factors, and therefore, the seasonally adjusted and trend estimates for the current and previous quarters. As a result of this improvement, revisions to the seasonally adjusted and trend estimates will be observed for recent periods. A more detailed review is conducted annually prior to the September quarter release using data up to and including the June quarter.
20 The revision properties of the seasonally adjusted and trend estimates can be improved by the use of autoregressive integrated moving average (ARIMA) modelling. ARIMA modelling relies on the characteristics of the series being analysed to project future period data. The projected values are temporary, intermediate values, that are only used internally to improve the estimation of the seasonal factors. The projected data do not affect the original estimates and are discarded at the end of the seasonal adjustment process. The Quarterly Business Indicators Survey uses ARIMA modelling where appropriate for individual time series. The ARIMA model is assessed as part of the annual reanalysis and following the 2010 annual reanalysis, 22% of the Quarterly Business Indicators Survey eligible series use an ARIMA model. For more information on the details of ARIMA modelling see Feature article: Use of ARIMA modelling to reduce revisions in the October 2004 issue of Australian Economic Indicators (cat. no. 1350.0).
21 The trend estimates are derived by applying a 7-term Henderson moving average to the seasonally adjusted estimates. The 7-term Henderson moving average is symmetric, but as the end of a time series is approached, asymmetric forms of the moving average are applied. The asymmetric moving average has been tailored to suit the particular characteristics of individual series and enable trend estimates for recent quarters to be produced. Estimates of the trend will be improved at the current end of the time series as additional observations become available. This improvement is due to the combined effect of the concurrent seasonal adjustment methodology and the application of different asymmetric moving averages for the most recent three quarters. As a result of the improvement, revisions to the trend estimates will generally be observed for the most recent three quarters. ABS research shows that about 75% of the total revision to the trend estimate at the current end is due to the use of different asymmetric moving averages when the original estimate is available for the next quarter.
22 There may also be revisions because of changes in the original estimates. As a result of these revisions, the seasonally adjusted and trend estimates will also be revised. For further information, see Information Paper: A Guide to Interpreting Time Series - Monitoring Trends (cat. no. 1349.0) or contact the Assistant Director, Time Series Analysis on Canberra (02) 6252 6345 or email <email@example.com>.
CHAIN VOLUME MEASURES
23 The chain volume measures appearing in this publication are annually reweighted chain Laspeyres indexes referenced to current price values in the chosen reference year (currently 2009-10). The current price values may be thought of as being the product of a price and quantity. The value in chain volume terms can be derived by linking together movements in volumes, calculated using the average prices of the previous financial year and applying compound movements to the current price estimates of the reference year. Each year’s quarter-to-quarter growth rates in the chain volume series are based on the prices of the previous financial year, except for those quarters of the latest incomplete year which are based upon the second most recent financial year. Quarterly chain volume estimates are benchmarked to annual chain volume estimates, so that the quarterly estimates for a financial year sum to the corresponding annual estimate.
24 With each release of the September quarter issue of this publication, a new base year is introduced and the reference year is advanced one year to coincide with it. This means that with the release of the September quarter 2011 issue of this publication, the chain volume measures for 2010-11 will have 2009-10 (the previous financial year) as their base year rather than 2008-09, and the reference year is 2009-10. A change in the reference year changes levels but not growth rates for all periods. A change in the base year can result in revisions, small in most cases, to growth rates for the last year.
25 Chain volume measures are not generally additive. In other words, component chain volume measures do not, in general, sum to a total in the way original current price components do. For inventories and sales data, this means that the chain volume estimates for industry groups will not add to the total for Australia. In order to minimise the impact of this, the ABS uses the latest base year as the reference year. By adopting this approach, additivity does exist for the quarters following the reference year and non-additivity is relatively small for the quarters in the reference year and those immediately preceding it. For further information on chain volume measures, refer to the Information Paper: Introduction of Chain Volume Measures in the Australian National Accounts (cat. no. 5248.0).
COMPARABILITY WITH NATIONAL ACCOUNTS AND OTHER ABS ESTIMATES
26 The data collected in the Quarterly Business Indicators Survey are used in the compilation of the quarterly estimates of the Australian National Accounts. Inventories data are used to compile estimates of the increase in book value of non-farm inventories. Estimates of sales of goods and services are used to help derive quarterly chain volume measures of gross value added for selected industries. Company gross operating profits data are used to compile estimates of gross operating surplus of private non-financial corporations. From March quarter 2002, estimates of wages and salaries are being used to compile estimates for compensation of private sector employees. For further details see Australian National Accounts: Concepts, Sources and Methods (cat. no. 5216.0).
27 However the statistics in this publication will differ from corresponding statistics in the quarterly Australian National Accounts for the following reasons:
28 The estimates for sales of goods and services by Retail trade in this publication will differ from turnover estimates included in Retail Trade, Australia (cat. no. 8501.0). The latter publication presents monthly estimates of the value of turnover of retail businesses, and is sourced from the Retail Business Survey. Estimates for sales of goods and services in this publication exclude the Goods and Services Tax, while turnover collected in the Retail Business Survey includes the Goods and Services Tax. In addition, the Retail Business Survey includes some businesses classified to ANZSIC divisions other than the Retail trade division, and includes retail establishments associated with management units that are not classified to the Retail trade division. The use of different samples in the Retail Business Survey and Quarterly Business Indicators Survey will also contribute to differences.
AUSTRALIAN INTERNATIONAL FINANCIAL REPORTING STANDARDS
29 The new Australian equivalents to International Financial Reporting Standards (AIFRS) began to be progressively implemented in Australia from 1 January 2005. As a result, a number of items in the financial accounts of Australian businesses have been affected by changed definitions which have in turn impacted upon both Income Statements and Balance Sheets. A range of ABS economic collections source data from financial accounts of businesses and use those data to derive economic statistics. There have been no changes in the associated economic definitions.
30 After monitoring data items since March quarter 2005 it has been concluded that most affected published data series have been impacted by data breaks, but that the magnitude of such breaks cannot be determined without imposing disproportionate load upon data providers to ABS surveys and other administratively collected data. ABS will continue to monitor developments and report any significant identified impacts or changes in methodology as a result of AIFRS.
31 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated; without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.
32 Users may also wish to refer to the following publications:
ABS WEB SITE
33 Information on the Quarterly Business Indicators Survey and survey outputs are published on this web site: see the Topics @ a Glance pages.
DATA AVAILABLE ON REQUEST
34 As well as the statistics included in this and related publications, the ABS may have other relevant data available on request. These series include more detailed industry data (e.g. Manufacturing subdivision), and wages and salaries by state/territory by industry. The availability of more detailed data are subject to confidentiality and quality checks. Inquiries should be made to the National Information and Referral Service on 1300 135 070.
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This page last updated 31 August 2012