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STATISTICAL UNITS DEFINED ON THE ABS BUSINESS REGISTER
6 The ABS uses an economic statistics units model on the ABS Business Register to describe the characteristics of businesses, and the structural relationships between related businesses. The units model is also used to break groups of related businesses into relatively homogeneous components that can provide data to the ABS.
7 In mid 2002, to better use the information available as a result of The New Tax System, the ABS changed its economic statistics units model. The new units model allocates businesses to one of two sub-populations. The vast majority of businesses are in what is called the ATO Maintained Population, while the remaining businesses are in the ABS Maintained Population. Together, these two sub-populations make up the ABS Business Register population.
ATO Maintained Population
8 Most businesses and organisations in Australia need to obtain an ABN, and are then included on the ATO Australian Business Register. Most of these businesses have simple structures; therefore the unit registered for an ABN will satisfy ABS statistical requirements. For these businesses, the ABS has aligned its statistical units structure with the ABN unit. The businesses with simple structures constitute the ATO Maintained Population, and the ABN unit is used as the statistical unit for all economic collections.
ABS Maintained Population
9 For the population of businesses where the ABN unit is not suitable for ABS statistical requirements, the ABS maintains its own units structure through direct contact with each business. These businesses constitute the ABS Maintained Population. This population consists typically of large, complex and diverse businesses. The new statistical units model described below has been introduced to cover such businesses.
10 For more information on the impacts of the introduction of the new economic statistics units model, refer to Information Paper: Improvements in ABS Economic Statistics [Arising from the New Tax System] (cat. no. 1372.0).
11 Prior to the July 2002 reference month, the Retail Business survey used the management unit as the statistical unit. From the July 2002 reference month onwards, the statistical unit is the ABN unit for businesses with simple structures, and the TAU for businesses with complex structures. In most cases, ABN/TAU units concord with the management units previously used.
12 The survey is conducted monthly by both telephone interview and a questionnaire mailed to businesses. The businesses included in the survey are selected by random sample from a frame stratified by state, industry and business size. For the ABS Maintained Population, the ABS uses reported employment as the measure of business size. For the ATO Maintained Population, for which employment data are not updated on a regular basis, the ABS uses a derived size benchmark. The derived size benchmark is a modelled employment size measure, based primarily on wages and salaries from Business Activity Statements or number of payees from the ATO, which is scaled to be the same magnitude as the previous employment benchmark, using employment data from the Survey of Employment and Earnings.
13 In the first month of each quarter, some businesses in the sample are replaced, at random, by other businesses so that the reporting load can be spread across smaller retailers.
14 Most businesses can provide turnover on a calendar month basis and this is how the data are presented. When businesses cannot provide turnover on a calendar month basis, the reported data and the period they relate to are used to estimate turnover for the calendar month.
15 Most retailers operate in a single state/territory. For this reason, estimates of turnover by state/territory are only collected from the larger retailers which are included in the survey each month. These retailers are asked to provide turnover for sales from each state/territory in which the business operates. Turnover for the smaller businesses is allocated to the state of their head office or main outlet.
DEFINITION OF TURNOVER
16 Turnover includes retail sales; wholesale sales; takings from repairs, meals and hiring of goods (except for rent, leasing and hiring of land and buildings); commissions from agency activity (e.g. commissions received from collecting dry cleaning, selling lottery tickets, etc.); and net takings from gaming machines etc. From July 2000, turnover includes the Goods and Service Tax.
17 Turnover presented in the Retail Trade series includes net proceeds from licensed gambling activities undertaken in the Hotels and licensed clubs industry. The impact of net proceeds from gambling on movements in the Retail Trade series was discussed in a feature article 'Contribution of gambling to retail estimates' included in the December 2002 issue of this publication. The article concluded that net proceeds from gambling had not had a significant impact on quarterly movements for the series but net proceeds from gambling had increased over time and users should be aware of this when interpreting the series. For March quarter 2003, net proceeds from gambling was 3.7% of the Total Retail series and 39.8% of the turnover of Hotels and licensed clubs.
18 Seasonally adjusted estimates are derived by estimating and removing systematic calendar related effects from the original series. In the Retail trade series, these calendar related effects are known as seasonal (e.g. increased spending in December as a result of Christmas) and trading day influences (arising from the varying length of each month and the varying number of Sundays, Mondays, Tuesdays, etc. in each month). Each influence is estimated by separate seasonal and trading day factors which, when combined, are referred to as the combined adjustment factors.
19 The seasonally adjusted estimates also have an allowance for an Easter proximity effect, which is caused when Easter falls late in March or early in April. This effect, when present, is combined with the seasonal and trading day factors to form the combined adjustment factors. There is also a similar allowance for the variable timing of Father's Day. See the Appendix of the July 2001 and August 2002 issues respectively of this publication for more information.
20 The Retail series uses a concurrent seasonal adjustment methodology to derive the combined adjustment factors. This means that data from the current month are used in estimating seasonal and trading day factors for the current and previous months. For more information see Information Paper: Introduction of Concurrent Seasonal Adjustment into the Retail Trade Series (cat. no. 8514.0).
21 Concurrent adjustment can result in revisions each month to estimates for earlier periods. However, in most instances, the only noticeable revisions will be to the combined adjustment factors for the current month, the previous month and the same month a year ago. The following table shows how the combined adjustment factor for these months, at the total Australian Retail and Hospitality/services level, evolved under the concurrent seasonal adjustment methodology. The table presents two different estimates of the combined adjustment factors. The first row gives the combined adjustment factors estimated following the last annual reanalysis in July 2003 using data up to and including the June 2003 reference month. The second row gives the most recent combined adjustment factors estimated and used in this month's calculation of the concurrent seasonally adjusted series.
22 The seasonal adjustment methodology is able to produce combined adjustment factors for future months. The latest factors for some future months are shown in the following table. While these factors represent the best current estimate, the actual factors used for estimating the seasonally adjusted estimates in these months will differ because they will incorporate subsequent months' data as it becomes available.
23 The seasonal and trading day factors are reviewed annually at a more detailed level than possible in the monthly processing cycle. The annual reanalysis will not normally result in significant changes. For Retail Trade, the results of the latest review are usually shown in the July issue each year.
24 In the seasonal adjustment process, both the seasonal and trading day factors evolve over time to reflect changes in spending and trading patterns. Examples of this evolution include the slow move in spending from December to January; and, increased trading activity on weekends and public holidays. The seasonally adjusted estimates still reflect the sampling and non-sampling errors to which the original estimates are subject.
25 As a result of the different treatment of Australian and State totals in the seasonal adjustment process, the Australian total for an industry group may not necessarily equal the sum of the State totals for that industry group.
26 The monthly trend estimates are derived by applying a 13-term Henderson moving average to the seasonally adjusted estimates (7-term for quarterly series). The Henderson moving average is symmetric, but as the end of a time series is approached, asymmetric forms of the moving average have to be applied. The asymmetric moving averages have been tailored to suit the particular characteristics of individual series and enable trend estimates for recent periods 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 six months (or three quarters). As a result of the improvement, most revisions to the trend estimates will be observed for the most recent six months (or three quarters).
27 Trend estimates are used to analyse the underlying behaviour of the series over time. As a result of the introduction of The New Tax System, a break in the monthly trend series has been inserted between June and July 2000. Care should therefore be taken if comparisons span this period. For more details refer to the Appendix in the December 2000 issue of this publication. Further trend breaks have been inserted between June and July 2002 for some series as a result of volatility associated with the introduction of the new statistical infrastructure.
28 For further information on trend estimates, see Information Paper: A Guide to Interpreting Time Series - Monitoring ‘Trends’: an Overview (cat.no.1348.0) or contact the Assistant Director, Time Series Analysis on Canberra 02 6252 6345.
CHAIN VOLUME MEASURES
29 The chain volume measures of retail turnover appearing in the quarterly issue of this publication are annually reweighted chain Laspeyres indexes referenced to current price values in a chosen reference year. The reference year is advanced in each June issue and is currently 2001-2002. Each year’s data in the Retail chain volume series are based on the prices of the previous year, except for the quarters of the latest incomplete year. Data for the 2003-2004 financial year will initially be based upon price data for the 2001-2002 financial year. Comparability with previous years is achieved by linking (or chaining) the series together to form a continuous time series. While current price estimates reflect both price and volume changes, chain volume estimates measure changes in value after the direct effects of price changes have been eliminated and hence only reflect volume changes. Further information on the nature and concepts of chain volume measures is contained in the ABS publication Information Paper: Introduction of Chain Volume Measures in the Australian National Accounts (cat. no. 5248.0).
RELIABILITY OF ESTIMATES
30 There are two types of error possible in estimates of retail turnover:
31 Seasonally adjusted and trend estimates and chain volume measures are also subject to sampling variability. For seasonally adjusted estimates, the standard errors are approximately the same as for the original estimates. For trend estimates, the standard errors are likely to be smaller. For chain volume measures, the standard errors may be up to 10% higher than those for the corresponding current price estimates because of the sampling variability contained in the prices data used to deflate the current price estimates.
32 Estimates, in original terms, that have an estimated relative standard error (RSE) between 10% and 25% are annotated with the symbol '^' . These estimates should be used with caution as they are subject to sampling variability too high for some purposes. Estimates with an RSE between 25% and 50% are annotated with the symbol '*', indicating that the estimates should be used with caution as they are subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% are annotated with the symbol '**' indicating that the sampling variability causes the estimates to be considered too unreliable for general use.
33 To further assist users in assessing the reliability of estimates, each data series has been given a grading of A to E. Where:
34 The table below provides an indicator of reliability for key retail turnover estimates.
ABS DATA AVAILABLE ON REQUEST
35 Retail Survey Special Data Service provides additional retail trade statistics which include further State industry dissections through to ‘top ten’ industry reports. For more information, contact the Retail Trade Special Data Services manager on Canberra 02 6252 5220.
36 Current publications and other products released by the ABS are listed in the Catalogue of Publications and Products, Australia (cat. no. 1101.0). The Catalogue is available from any ABS office or the ABS web site. The ABS also issues a daily Release Advice on the web site which details products to be released in the week ahead.
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