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Retail Trade, Australia methodology

Reference period
April 2020

Explanatory notes

Introduction

1 This publication presents estimates of the value of turnover of "retail trade" for Australian businesses classified by industry, and by state and territory. For the purposes of this publication "retail trade" includes those industries as defined in paragraphs 5 and 6.

2 The estimates of turnover are compiled from the monthly Retail Business Survey. About 500 'large' businesses are included in the survey every month, while a sample of about 2,700 'smaller' businesses is selected. The 'large' business' contribution of approximately 69% of the total estimate ensures a highly reliable Australian total turnover estimate.

3 Monthly estimates are presented in current price terms. Quarterly chain volume measures at the state and industry levels are updated with the March, June, September and December issues of this publication.

Definition of turnover

4 Turnover includes:

  • retail sales;
  • online sales from both store-based and non-store based retailers (except non-employing and non-resident businesses)
  • 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
  • from July 2000, the goods and services tax.
     

Defining retail trade

5 The industries included in the survey are as defined in the Australian and New Zealand Standard Industrial Classification (ANZSIC) 2006 (cat. no. 1292.0). Industry statistics in this publication are presented at two levels of detail:

  • Industry group - the broadest industry level comprising 6 industry groups. This level is used to present monthly current price and quarterly chain volume measure estimates in this publication.
  • Industry subgroup - the most detailed industry level comprising 15 industry subgroups. This level is used to present monthly current price estimates in time series spreadsheets.
     

6 The following shows the level at which retail trade statistics are released and defines each industry group and subgroup in terms of ANZSIC 2006 classes:

  • Food retailing
    • Supermarket and grocery stores and non-petrol sales (convenience stores) of selected fuel retailing
      • Supermarket and grocery stores (4110)
      • non-petrol sales (convenience stores) of selected Fuel retailing (4000)
    • Liquor retailing
      • Liquor retailing (4123)
    • Other specialised food retailing
      • Fresh meat, fish and poultry retailing (4121)
      • Fruit & vegetable retailing (4122)
      • Other specialised food retailing (4129)
  • Household goods retailing
    • Furniture, floor coverings, houseware and textile goods retailing
      • Furniture retailing (4211)
      • Floor coverings retailing (4212)
      • Houseware retailing (4213)
      • Manchester and other textile goods retailing (4214)
    • Electrical and electronic goods retailing
      • Electrical, electronic and gas appliance retailing (4221)
      • Computer and computer peripheral retailing (4222)
      • Other electrical and electronic goods retailing (4229)
    • Hardware, building & garden supplies retailing
      • Hardware and building supplies retailing (4231)
      • Garden supplies retailing (4232)
  • Clothing, footwear and personal accessory retailing
    • Clothing retailing
      • Clothing retailing (4251)
    • Footwear and other personal accessory retailing
      • Footwear retailing (4252)
      • Watch and jewellery retailing (4253)
      • Other personal accessory retailing (4259)
  • Department stores (4260)
  • Other retailing
    • Newspaper and book retailing
      • Newspaper and book retailing (4244)
    • Other recreational goods retailing
      • Sport and camping equipment retailing (4241)
      • Entertainment media retailing (4242)
      • Toy and game retailing (4243)
    • Pharmaceutical, cosmetic and toiletry goods retailing
      • Pharmaceutical, cosmetic and toiletry goods retailing (4271)
    • Other retailing n.e.c
      • Stationery goods retailing (4272)
      • Antique and used goods retailing (4273)
      • Flower retailing (4274)
      • Other-store based retailing n.e.c (4279)
      • Non-store retailing (4310)
      • Retail commission-based buying and/or selling (4320)
  • Cafes, restaurants and takeaway food services
    • Cafes, restaurants and catering services
      • Cafes and restaurants (4511)
      • Catering services (4513)
    • Takeaway food services
      • Takeaway food services (4512)
         

Scope and coverage

7 The scope of the Retail Business Survey is all employing retail trade businesses who predominantly sell to households. Like most Australian Bureau of Statistics (ABS) economic surveys, the frame used for the Survey is taken from the ABS Business Register which includes registrations to the Australian Taxation Office's (ATO) pay-as-you-go withholding (PAYGW) scheme. Each statistical unit included on the ABS Business Register is classified to the ANZSIC industry in which it mainly operates. The frame is supplemented with information about a small number of businesses which are classified to a non-retail trade industry but which have significant retail trade activity.

8 The frame is updated quarterly to take account of new businesses, businesses which have ceased employing, changes in industry and other general business changes. The estimates include an allowance for the time it takes a newly registered business to get on to the survey frame. Businesses which have ceased employing are identified when the ATO cancels their Australian Business Number (ABN) and/or PAYGW registration. In addition, businesses with less than 50 employees which do not remit under the PAYGW scheme in each of the previous five quarters are removed from the frame.

9 To improve coverage and the quality of the estimates and to reduce the cost to the business community of reporting information to the ABS, turnover for franchisees is collected directly from a number of franchise head offices. The franchisees included in this reporting are identified and removed from the frame.

Statistical unit

10 The ABS uses an economic statistics units model based on the ABS Business Register to describe the characteristics of businesses and the structural relationships between related businesses. Within large and diverse business groups, the units model is used to define reporting units that can provide data to the ABS at suitable levels of detail. In mid 2002, the ABS commenced sourcing its register information from the Australian Business Register and at that time changed its business register to a two population model. The two populations comprise what is called the Profiled Population and the Non-Profiled Population. The main distinction between businesses in the two populations relates to the complexity of the business structure and the degree of intervention required to reflect the business structure for statistical purposes.

Non-profiled population

11 The majority of businesses included on the ABS Business Register are in the Non-Profiled Population. Most of these businesses are understood to have simple structures. For these businesses, the ABS is able to use the ABN as the basis for a statistical unit. One ABN equates to one statistical unit.

Profiled population

12 For a small number of businesses, the ABN unit is not suitable for ABS economic statistics purposes and the ABS maintains its own units structure through direct contact with businesses. These businesses constitute the Profiled Population. This population consists typically of large or complex groups of businesses. The statistical units model below caters for such businesses:

  • Enterprise group: This is a unit covering all the operations in Australia of one or more legal entities under common ownership and/or control. It covers all the operations in Australia of legal entities which are related in terms of the current Corporations Law (as amended by the Corporations Legislation Amendment Act 1991), including legal entities such as companies, trusts and partnerships. Majority ownership is not required for control to be exercised.
  • Enterprise: The enterprise is an institutional unit comprising:
    • a single legal entity or business entity, or
    • more than one legal entity or business entity within the same enterprise group and in the same institutional subsector (i.e. they are all classified to a single Standard Institutional Sector Classification of Australia (SISCA) subsector).
  • Type of activity unit (TAU): The 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 ANZSIC). Where a business cannot supply adequate data for each industry, a TAU is formed which contains activity in more than one industry subdivision.
     

Survey methodology

13 The Survey is conducted monthly primarily by telephone interview although a small number of questionnaires are mailed to businesses. The businesses included in the survey are selected by random sample from a frame stratified by state, industry and business size. The survey uses annualised turnover as the measure of business size. For the Non-Profiled Population, the annualised turnover is based on the ATO's Business Activity Statement item Total Sales and for the Profiled Population a modelled annualised turnover is used. For stratification purposes the annualised turnover allocated to each business is updated quarterly with the most recent Business Activity Statement (BAS) information.

14 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. This sample replacement occurs in the first month of each quarter which may increase the volatility of estimates between this month and the previous month especially at the state by industry subgroup level.

15 Generalised regression estimation methodology is used for estimation. For estimation purposes, the annualised turnover allocated to each business is updated each quarter.

16 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.

17 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 mailing address as recorded on the ABS Business Register.

18 Stratified sampling is employed when, within a survey population, there are subpopulations which vary from the entire population. Stratification offers the advantage of sampling each stratum independently. The Retail Business Survey uses stratification to group the retail businesses to be surveyed into homogenous strata based on the annualised turnover allocated to each business. The annualised turnover variable is derived from BAS information from the taxation system and is used both as a sizing variable for stratification purposes and to form auxiliary information (estimation benchmarks) to support the regression estimation methodology used in the Retail Business Survey. The utilisation of BAS information enables the most efficient design for the survey, keeping sample sizes to a minimum while providing accurate results. From October 2013, the stratification benchmarks have been updated every quarter so as to improve the accuracy of level estimates derived from the survey as well as addressing the issue of aging stratification benchmarks which must otherwise be periodically updated.

19 The results of these statistics are based, in part, on ABR data supplied by the Registrar to the ABS under A New Tax System (Australian Business Number) Act 1999 and tax data supplied by the ATO to the ABS under the Taxation Administration Act 1953. These require that such data is only used for the purpose of carrying out functions of the ABS. No individual information collected under the Census and Statistics Act 1905 is provided back to the Registrar or ATO for administrative or regulatory purposes. Any discussion of data limitations or weaknesses is in the context of using the data for statistical purposes, and is not related to the ability of the data to support the ABR or ATO’s core operational requirements. Legislative requirements to ensure privacy and secrecy of this data have been followed. Only people authorised under the Australian Bureau of Statistics Act 1975 have been allowed to view data about any particular firm in conducting this survey. In accordance with the Census and Statistics Act 1905, results have been confidentialised to ensure that they are not likely to enable identification of a particular person or organisation.

Seasonal adjustment and trend estimation

20 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. annual patterns in sales, such as increased spending in December as a result of Christmas
  • trading day influences arising from weekly patterns in sales and the varying length of each month and the varying number of Sundays, Mondays, Tuesdays, etc. in each month
  • an Easter proximity effect, which is caused when Easter, a moveable holiday, falls late in March or early in April
  • a Father's Day effect, which is caused when the first Sunday in September falls in the first few days of the month and Father's Day shopping occurs in August.
     

21 Each of these influences is estimated by separate factors which, when combined, are referred to as the combined adjustment factors. The combined adjustment factors are based on observed patterns in the historical data. It is possible that with the introduction of ANZSIC 2006 from July 2009 the historical patterns may not be as relevant to some series. For example Watch and jewellery retailing moved from the Other retailing n.e.c industry subgroup to the Footwear and other personal accessory retailing industry subgroup under ANZSIC 2006. The seasonal patterns for other businesses in the Footwear and other personal accessory retailing industry subgroup appear to differ from watch and jewellery retailers. The combined adjustment factors will evolve over time to reflect any new seasonal or trading day patterns, although in this example, an estimate for this impact (seasonal break) has been implemented in the combined adjustment factors.

22 The following Retail trade series are directly seasonally adjusted:

  • Australian turnover
  • each state total
  • each Australian industry subgroup total
  • each state by industry subgroup.
     

23 A "two-dimensional reconciliation" methodology is used on the seasonally adjusted time series to force additivity - that is, to force the sum of fine-level (state by industry subgroup) estimates to equal the Australian, state and industry subgroup totals. The industry group totals are derived from the lower level estimates.

24 Quarterly seasonally adjusted series used in the compilation of the chain volume measures are the sum of their applicable monthly series.

25 Autoregressive integrated moving average (ARIMA) modelling can improve the revision properties of the seasonally adjusted and trend estimates. 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 retail collection uses an individual ARIMA model for each of the industry totals and state totals. The ARIMA model is assessed as part of the annual reanalysis.

26 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 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).

27 The seasonal and trading day factors are reviewed annually at a more detailed level than possible in the monthly processing cycle. The annual reanalysis can result in relatively higher revisions to the seasonally adjusted series than during normal monthly processing.

28 The seasonally adjusted estimates still reflect the sampling and non-sampling errors to which the original estimates are subject. This is why it is recommended that trend series be used with the seasonally adjusted series to analyse underlying month-to-month movements.

29 The trend estimates are derived by applying a 13-term Henderson moving average to the seasonally adjusted monthly series and a 7-term Henderson moving average to the seasonally adjusted 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. An end-weight parameter 2.0 of the asymmetric moving average is used to produce trend estimates for the Australia, State and Australian industry group totals. For the other series a standard end-weight parameter 3.5 of the asymmetric moving average is used. 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 application of different asymmetric moving averages for the most recent six months for monthly series and three quarters for quarterly series. As a result of the improvement, most revisions to the trend estimates will be observed in the most recent six months or three quarters.

30 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.

31 For further information on seasonally adjusted and trend estimates, see:

Chain volume measures

32 Monthly current price estimates presented in this publication reflect both price and volume changes. However, the quarterly chain volume estimates measure changes in value after the direct effects of price changes have been eliminated and hence only reflect volume changes. The chain volume measures of retail turnover appearing in this publication are annually reweighted chain Laspeyres indexes referenced to current price values in a chosen reference year. The reference year is advanced each September issue and is currently 2017-18. 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 2019-20 financial year which will initially be based upon price data for the 2017-18 financial year. Comparability with previous years is achieved by linking (or chaining) the series together to form a continuous time series. 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

33 There are two types of error possible in estimates of retail turnover:

Sampling error which occurs because a sample, rather than the entire population, is surveyed. One measure of the likely difference resulting from not including all establishments in the survey is given by the standard error. Sampling error may be influenced by the sample replacement that occurs in the first month of each quarter. This may increase the volatility of estimates between this month and the previous month especially at the state by industry subgroup level.

Non sampling error which arises from inaccuracies in collecting, recording and processing the data. The most significant of these errors are: misreporting of data items; deficiencies in coverage; non-response; and processing errors. Every effort is made to minimise reporting error by the careful design of questionnaires, intensive training and supervision of interviewers, and efficient data processing procedures.

Standard errors

34 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 quarterly 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.

35 Estimates, in original terms, are available from the data download section of this issue on the ABS website. Estimates 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 a 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 a 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.

36 To further assist users in assessing the reliability of estimates, key data series have been given a grading of A to B. Where:

  • A represents a relative standard error on level of less than 2%. The published estimates are highly reliable for movement analysis.
  • B represents a relative standard error on level between 2% and 5%, meaning the estimates are reliable for movement analysis purposes.
     

37 The tables below provide an indicator of reliability for the estimates in original terms. The reliability indicator is based on an average RSE derived over four years.

Relative Standard Errors by industry group

 Food retailingHousehold goods retailingClothing, footwear and personal accessory retailingDepartment storesOther retailingCafes, restaurants and takeaway food servicesTotal
RSE (%)
A
A
B
A
B
B
A
   

Relative Standard Errors by state

 NSWVic.QldSAWATas.NTACTAust.
RSE (%)
A
A
A
A
A
B
A
A
A


38 Standard errors for the Australian estimates (original data) for April 2020 contained in this publication are:

Data SeriesEstimateStandard Error
Level of retail turnover ($m)
23 619.5
151.2
Change from preceding month ($m)
-5 539.7
150.6
% change from preceding month (%)
-19.0
0.5
   

Reliability of trend estimates

39 The trending process dampens the volatility in the original and seasonally adjusted estimates. However, trend estimates are subject to revisions as future observations become available.

Comparability with other ABS estimates

40 The estimates of Retail turnover in this publication will differ from sales of goods and services by the Retail trade industry in Business Indicators, Australia (cat. no. 5676.0). This publication presents monthly estimates of the value of turnover of retail businesses, is sourced from the Retail Business Survey, includes the Goods and Services Tax and includes some retail trade businesses classified to a non-retail trade industry but which have significant retail trade activity. Estimates for sales of goods and services in Business Indicators, Australia are sourced from the economy wide Quarterly Business Indicators Survey and exclude the Goods and Services Tax. In addition, the Retail Business Survey does not include all classes in the ANZSIC Retail trade Division but includes Cafes, restaurants and takeaway food services from the Accommodation and Food Services Division. The use of different samples in the two surveys also contributes to differences.

41 Quarterly Retail trade chain volume estimates contribute to the quarterly national accounts in two main areas. First, they are an indicator of Household Final Consumption Expenditure in the expenditure side of Gross domestic product. Historically Retail trade estimates contribute about 55-60% of Household Final Consumption Expenditure but this relative contribution can vary from quarter to quarter as household expenditure shifts between retail trade and areas like personal services, travel and leisure activities which are outside the scope of retail trade. Second, Retail trade estimates, along with estimates from Business Indicators, Australia, contribute to estimates for the Retail trade Division in the production side of Gross domestic product.

Retail trade per capita

42 The estimates of retail turnover per capita are compiled from the monthly Retail Business Survey and the quarterly Estimated Resident Population (ERP) published within Australian Demographic Statistics (Cat. no. 3101.0). Retail turnover per capita estimates are the ratios of total quarterly retail turnover to the quarterly ERP. The methods used in deriving Retail turnover per capita estimates are consistent with those used for the derivation of GDP per capita. As quarterly ERP estimates currently lag quarterly retail trade estimates by approximately six months, the two most recent quarters of Retail per capita estimates use ERP projections based on current trend.

43 The scope, coverage and methodology for the Retail Business Survey and ERP estimates are included in the explanatory notes of the corresponding publications. Detailed discussion around the derivation methodology, ERP projection and interpretation of retail turnover per capita estimates are available as an Appendix within the Explanatory notes tab to the June 2014 release of this publication.

44 Current price estimates and chain volume measures, in original, seasonally adjusted and trend terms are available from the data download section of this issue on the ABS website. Revisions to the retail turnover per capita series will occur with every future revision of quarterly ERP estimates and also following any revisions to Retail Trade estimates.

45 Current publications and other products released by the ABS are available from the Statistics View. The ABS also issues a daily Release Advice on the web site which details products to be released in the week ahead. Users may also wish to refer to the following publications:

46 As well as the statistics included in this and related publications, the ABS may have other relevant data available. Inquiries should be made to the National Information and Referral Service on 1300 135 070.

Appendix - experimental estimates of online retail turnover

Show all

Introduction

1 This appendix presents estimates of the value of 'online retail turnover' in Australia (i.e. turnover from domestic online retail sales) from July 2013 and onwards.

2 The estimates are compiled from the monthly Retail Business Survey. The scope, coverage and methodology of this survey are provided in the explanatory notes of this publication.

3 Monthly estimates are presented in current price terms. Original estimates only are available, with a view to publishing seasonally adjusted and trend estimates in the future.

4 The estimates in this appendix are considered experimental. They are subject to evaluation and should therefore be used with caution.

5 Further discussion on the scope of the Retail Business Survey and the enhanced measurement of online retail trade activity can be found in the information paper Measurement of Online Retail Trade in Macroeconomics(cat. no. 8501.0.55.007).

Key statistics

A1 Online retail turnover, Australia, by type of activity

MonthPure-play Online Retail TradeMulti-channel Online Retail TradeTotal Online Retail Trade
$m$m$m
 
Original
2015   
 September
318.8
475.8
794.6
 October
306.1
473.5
779.6
 November
331.3
526.2
857.6
 December
343.9
626.0
969.9
2016   
 January
260.3
485.3
745.6
 February
270.6
425.5
696.2
 March
297.3
476.4
773.7
 April
296.5
448.9
745.4
 May
312.1
488.4
800.4
 June
332.1
510.0
842.1
 July
313.3
481.0
794.3
 August
329.0
501.9
830.9
 September
385.5
504.3
889.8
 October
391.2
609.8
1 001.0
 November
468.9
639.9
1 108.8
 December
510.5
754.6
1 265.1
2017   
 January
324.1
578.9
903.0
 February
301.3
524.1
825.3
 March
334.9
604.2
939.1
 April
259.2
568.7
827.9
 May
320.9
662.8
983.7
 June
335.9
703.3
1 039.2
 July
403.3
678.8
1 082.2
 August
452.2
698.6
1 150.8
 September
447.2
662.0
1 109.2
 October
529.3
705.6
1 234.9
 November
620.0
890.5
1 510.6
 December
590.6
1 011.2
1 601.8
2018   
 January
441.5
787.1
1 228.6
 February
433.4
754.2
1 187.6
 March
507.2
840.4
1 347.6
 April
501.9
836.6
1 338.6
 May
549.5
915.9
1 465.5
 June
538.6
924.6
1 463.2
 July
544.8
874.7
1 419.5
 August
578.1
903.9
1 482.1
 September
570.9
882.7
1 453.6
 October
597.8
1 008.5
1 606.3
 November
740.3
1 152.6
1 892.9
 December
685.6
1 249.6
1 935.2
2019   
 January
508.1
979.2
1 487.3
 February
506.2
845.2
1 351.5
 March
508.3
1 009.9
1 518.1
 April
550.3
935.9
1 486.2
 May
590.2
1 054.5
1 644.7
 June
562.2
1 045.8
1 608.0
 July
619.2
1 005.5
1 624.7
 August
649.5
1 022.5
1 672.0
 September
688.6
997.8
1 686.4
 October
718.5
1 111.6
1 830.1
 November
850.2
1 246.2
2 096.3
 December
849.8
1 456.6
2 306.4
2020   
 January
603.8
1 108.7
1 712.5
 February
602.0
1 073.8
1 675.8
 March
769.4
1 299.7
2 069.0
 April
1 152.3
1 463.2
2 615.5
   

A2 Online retail turnover, Australia, by type of activity - percentage change from previous month

MonthPure-play Online Retail TradeMulti-channel Online Retail TradeTotal Online Retail Trade
%%%
 Original
2015   
 September
9.1
1.5
4.4
 October
-4.0
-0.5
-1.9
 November
8.2
11.1
10.0
 December
3.8
19.0
13.1
2016   
 January
-24.3
-22.5
-23.1
 February
4.0
-12.3
-6.6
 March
9.9
12.0
11.1
 April
-0.3
-5.8
-3.7
 May
5.3
8.8
7.4
 June
6.4
4.4
5.2
 July
-5.7
-5.7
-5.7
 August
5.0
4.3
4.6
 September
17.2
0.5
7.1
 October
1.5
20.9
12.5
 November
19.9
4.9
10.8
 December
8.9
17.9
14.1
2017   
 January
-36.5
-23.3
-28.6
 February
-7.1
-9.5
-8.6
 March
11.2
15.3
13.8
 April
-22.6
-5.9
-11.8
 May
23.8
16.5
18.8
 June
4.7
6.1
5.6
 July
20.1
-3.5
4.1
 August
12.1
2.9
6.3
 September
-1.1
-5.2
-3.6
 October
18.4
6.6
11.3
 November
17.1
26.2
22.3
 December
-4.7
13.5
6.0
2018   
 January
-22.5
-22.2
-22.3
 February
-1.8
-4.2
-3.3
 March
17.0
11.4
13.5
 April
-1.0
-0.5
-0.7
 May
9.5
9.5
9.5
 June
-2.0
0.9
-0.2
 July
1.1
-5.4
-3.0
 August
6.1
3.3
4.4
 September
-1.3
-2.3
-1.9
 October
4.7
14.2
10.5
 November
23.8
14.3
17.8
 December
-7.4
8.4
2.2
2019   
 January
-25.9
-21.6
-23.1
 February
-0.4
-13.7
-9.1
 March
0.4
19.5
12.3
 April
8.3
-7.3
-2.1
 May
7.2
12.7
10.7
 June
-4.7
-0.8
-2.2
 July
10.1
-3.9
1.0
 August
4.9
1.7
2.9
 September
6.0
-2.4
0.9
 October
4.3
11.4
8.5
 November
18.2
12.1
14.5
 December
-
16.9
10.0
2020   
 January
-28.9
-23.9
-25.8
 February
-0.3
-3.2
-2.1
 March
27.8
21.0
23.5
 April
49.8
12.6
26.4
- nil or rounded to zero (including null cells)

 

A3 Online retail turnover, Australia, by type of activity - percentage of total Australian retail turnover

MonthPure-play Online Retail TradeMulti-channel Online Retail TradeTotal Online Retail Trade
%%%
 Original
 September
1.3
2.0
3.3
 October
1.2
1.9
3.1
 November
1.3
2.0
3.3
 December
1.1
2.0
3.0
2016   
 January
1.1
2.0
3.0
 February
1.2
1.9
3.1
 March
1.2
1.9
3.2
 April
1.2
1.9
3.1
 May
1.3
2.0
3.3
 June
1.4
2.1
3.5
 July
1.3
2.0
3.2
 August
1.3
2.0
3.4
 September
1.5
2.0
3.6
 October
1.5
2.3
3.9
 November
1.8
2.4
4.1
 December
1.5
2.3
3.8
2017   
 January
1.3
2.3
3.6
 February
1.3
2.3
3.6
 March
1.3
2.4
3.7
 April
1.1
2.3
3.4
 May
1.3
2.6
3.9
 June
1.3
2.8
4.1
 July
1.6
2.7
4.3
 August
1.8
2.8
4.6
 September
1.8
2.6
4.4
 October
2.0
2.7
4.7
 November
2.2
3.2
5.5
 December
1.8
3.0
4.8
2018   
 January
1.7
3.0
4.7
 February
1.9
3.2
5.1
 March
1.9
3.2
5.1
 April
2.0
3.4
5.4
 May
2.1
3.5
5.6
 June
2.1
3.6
5.7
 July
2.1
3.4
5.5
 August
2.2
3.4
5.6
 September
2.2
3.4
5.6
 October
2.2
3.7
5.9
 November
2.6
4.0
6.6
 December
2.0
3.6
5.6
2019   
 January
1.9
3.7
5.6
 February
2.1
3.5
5.6
 March
1.9
3.8
5.7
 April
2.1
3.6
5.7
 May
2.2
3.9
6.2
 June
2.1
4.0
6.1
 July
2.3
3.8
6.1
 August
2.4
3.8
6.2
 September
2.6
3.8
6.3
 October
2.6
3.9
6.5
 November
2.9
4.2
7.1
 December
2.4
4.1
6.6
2020   
 January
2.2
4.1
6.3
 February
2.4
4.2
6.6
 March
2.6
4.5
7.1
 April
4.9
6.2
11.1
   

Definition of online retail turnover

6 For the purposes of this publication, 'online retail turnover' is the value of turnover of 'retail trade' which is derived from 'online sales'. 'Retail trade' includes those industries defined in paragraphs 5 and 6 of the explanatory notes of this publication. 'Online sales' are defined as sales of goods and/or services where the order is placed by the buyer via the Internet or any other computer network, regardless of whether payment is made online or not.

Classification

7 The estimates are disaggregated between "pure-play" and "multi-channel" online retail trade activity. Pure-play online retail trade includes only the online sales of sole e-commerce retailers (i.e. retailers that trade with consumers solely via an online store and have no physical store). All other online sales are included in Multi-channel online retail trade, comprised of retailers which combine an online store with a physical store and/or other non-traditional means such as catalogues, mail-order and/or telephone-order.

Scope and coverage

8 The estimates of online retail turnover are compiled from the monthly Retail Business Survey. The scope of this survey includes all employing businesses within Australia from selected retail trade and food services industries which predominately sell to households.

9 The online retail sales of both store based and non-store based retailers, including pure-play online retailers, will be included in this scope. However, online sales by non-employing businesses and non-resident retailers overseas which sell directly to the Australian general public via an online store are not included, nor are they within the primary purpose or scope of the Retail Business Survey.

10 The survey also excludes online retail sales from businesses with a non-retail industry classification, such as businesses which sell predominantly to other businesses (which are predominantly wholesalers) and businesses which produce goods for direct selling to consumers from the same premises (which are predominantly manufacturers).

11 The methodology used to derive the estimates of online retail turnover is also based on the same sample design and generalised estimation methodology which is used for the Retail Business Survey.

Ongoing investigations and upcoming changes

12 Further enhancements to improve the coverage and presentation of estimates of online retail turnover are the subject of ongoing investigation by the ABS. These include (but are not limited to) potential enhancements to the methodology of the Retail Business Survey which would optimise the survey design for estimating both online and total retail turnover, rather than the current design which is optimised for estimating total retail turnover only.

13 Changes to the presentation of the estimates are planned for future issues of Retail Trade. Future issues are expected to include:

  • Estimates of the sampling variability associated with the new estimates of online retail turnover;
  • Spreadsheets including the new estimates, available from the data download section of this publication on the ABS website; and
  • Discussion on the potential disaggregation of the new estimates by state and territory, and conceptual issues associated with disaggregating online retail turnover by location of business and/or consumer.
     

Suggestions and feedback

14 As part of our ongoing investigations, we are currently seeking user feedback and suggestions about the presentation of the experimental time series in this publication and the upcoming changes planned for future issues. In particular, comment is sought on the usefulness of the proposed industry disaggregation.

15 If you have any feedback or suggestions please contact Ben Faulkner by email at ben.faulkner@abs.gov.au or by phone on (02) 9268 4052.

16 As well as the statistics included in this and related publications, the ABS may have other relevant data available. Inquiries should be made to the National Information and Referral Service on 1300 135 070.

Appendix - experimental estimates of consumer sales

Show all

Introduction

1 The feature article 'Coverage of Household Final Consumption Expenditure' published in Retail Trade, Australia September 2013 discussed changes in household expenditure patterns over time and describes ongoing investigations to improve coverage of Coverage of Household Final Consumption Expenditure (HFCE) in this publication.

2 With a focus on services and other categories which are outside the scope of Retail Trade the Survey of Consumer Sales was introduced and currently consists of two activity based collections; Survey of Consumer Sales - Energy Retailing and the Survey of Consumer Sales - Communication Services.

3 The Survey of Consumer Sales will provide key quarterly indicators on the performance of the Australian economy and will be an important component in the compilation of HFCE in the National Accounts. Details on the compilation of HFCE is available from Australian System of National Accounts: Concepts, Sources and Methods (cat. no. 5216.0). Chapter 10 Gross Domestic Product - Expenditure Approach (GDP(E)) outlines the data sources and methods used in the estimation of annual and quarterly household final consumption expenditure by Classification of Individual Consumption by Purpose (COICOP) category.

4 The Survey of Consumer Sales - Energy Retailing is considered a census of energy retailing activity. The scope excludes energy generation and energy distribution. It collects estimates for the sale of electricity and gas to consumer customers in Australia. A quarterly indicator is derived from the revenue data obtained from the service providers.

5 The Survey of Consumer Sales - Communication Services is a sample of telecommunication providers considered to be major service providers. It collects estimates for the sale of mobile services, fixed line phone services and fixed internet services to consumer customers in Australia. A quarterly indictor is derived using only the revenue data obtained from these major service providers. The revenue data is not weighted to account for the smaller providers. The indicator currently includes telephone and internet services and excludes the sale of equipment. The survey may be expanded in the future to include postal services.

6 Available in this publication are experimental estimates for Electricity Retailing, Gas Retailing and Telecommunication Services Retailing. The full time series are available from the data download section of this publication on the ABS website. The Electricity and Gas retailing series commenced in June quarter 2012. The Telecommunication Services Retailing series commenced in December quarter 2012.

7 Quarterly estimates are presented in current price values. Original estimates only are available, with a view to publishing seasonally adjusted and trend estimates in the future.

8 The estimates in this appendix are considered experimental. They are subject to evaluation and should therefore be used with caution.

Key statistics

A4 Consumer sales, Australia, by type of activity

QuarterElectricity retailingGas retailingTelecommunications Services retailing
$m$m$m
 Original
2018   
 March
4 327.1
728.9
4 458.1
 June
4 358.5
1 428.4
4 446.1
 September
4 867.1
1 834.8
4 455.5
 December
4 060.5
962.4
4 429.9
2019   
 March
4 403.0
744.8
4 332.6
 June
4 322.7
1 383.7
4 255.6
 September
r4 562.2
1 794.6
4 259.3
 December
4 017.8
934.4
r4 218.3
2020   
 March
4 248.0
781.1
4 161.3
r revised

 

A5 Consumer sales, Australia, by type of activity, percentage change from previous quarter

QuarterElectricity retailingGas retailingTelecommunication Services retailing
%%%
 Original
2018   
 March
6.5
-14.1
-2.1
 June
0.7
96.0
-0.3
 September
11.7
28.5
0.2
 December
-16.6
-47.5
-0.6
2019   
 March
8.4
-22.6
-2.2
 June
-1.8
85.8
-1.8
 September
5.5
29.7
0.1
 December
-11.9
-47.9
-1.0
2020   
 March
5.7
-16.4
-1.3
   

Timing of survey cycle

9 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 the survey data relate. E.g. December quarter returns are completed during January and February.

Definition of consumer sales

10 For the purposes of this publication, "consumer sales" are the value of sales to consumer customers. A consumer customer includes households, individuals and all other customers who are not corporate, business and government customers.

11 The Survey of Consumer Sales - Energy Retailing further details a consumer customer as a residential customer who:

  • Consumes electricity and gas for domestic use;
  • Consumes below 100 megawatt hours (MWh) of electricity annually; and
  • Consumes below 1 terajoule (TJ) of gas annually.
     

Classifications

12 Many ABS publications are classified according to the Australian and New Zealand Standard Industrial Classification (ANZSIC) 2006 (cat. no. 1292.0). Outputs from the Survey of Consumer Sales are not classified according to ANZSIC and are instead classified by activity with reference to the Classification of Individual Consumption according to Purpose (COICOP). The aim of this classification is to survey businesses which sell services to consumers, allowing for those businesses for which the surveyed activity may be a secondary activity.

13 Energy retailing activity is defined with reference to the COICOP category "Electricity, Gas and Other fuels". Electricity retailing is the sale of electricity to consumer customers. Gas retailing is the sale of town and natural gas to consumer customers. The sale of liquefied hydrocarbons (e.g. LPG) is currently excluded, though these are included in the COICOP category for gas.

14 Telecommunication services retailing is defined with reference to COICOP category "Telephone and telefax services". Telecommunication services retailing is the sale of mobile services, fixed line phone services and fixed internet services to consumer customers.

Scope and coverage

15 The scope of the Energy Retailing collection is all businesses that hold a licence obtained from a regulatory body to operate as an energy retailer. Energy generation and distribution activities are outside the scope of the survey.

16 The frame used for the Energy Retailing collection is taken from a registry list of all operating energy retailers in Australia produced by the Energy Supply Association of Australia (ESAA).

17 The scope of the Communication Services collection includes those telephone and internet service providers that retail to consumer customers in Australia. Internet Service Providers (ISPs) are defined as those who operate in Australia and supply internet connectivity and access services to consumer customers. Libraries, internet kiosks, internet cafes and hotspots that provide internet access on a casual basis are excluded.

18 The frame used for the Communication Services collection is drawn from the Internet Activity Survey (IAS) (cat. no. 8153.0). The population frame for this survey is produced from a list of ISPs sourced from the Telecommunication Industry Ombudsman, with whom ISPs are required to register. Currently the coverage of the Communication Services collection is limited to the top size category used in the IAS, which is defined as a 'very large ISP' having 100,001 or more subscribers. Further details on the IAS frame are provided in the IAS explanatory notes.

19 The Survey of Consumer Sales aims to measure expenditure by consumer customers on services. For this reason, the estimates are broader than the income received by retailers, including for example; the Goods and Services Tax (GST), government concessions, discounts and solar rebates.

Survey methodology

20 The Survey of Consumer Sales is conducted electronically on a quarterly basis and may include Government-owned and/or controlled Public Non-Financial Corporations.

21 The statistical unit used to represent each energy retailer is sourced from the ABS Business Register (ABSBR). The majority of the businesses within scope of this survey are large businesses with the statistical unit being the Type of Activity Unit (TAU). However there are a few units where the Australian Business Number (ABN) is the statistical unit and is suitable for ABS statistical needs when the business is simple in structure.

22 Service providers are asked to provide consumer sales data on an accrual basis. 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 the data by summing the individual unit level data. Data are edited at both individual unit level and aggregate level.

23 The Survey of Consumer Sales - Energy Retailing is based on a complete enumeration of businesses that have been identified as holding a licence to retail electricity and/or gas to consumer customers.

24 The Survey of Consumer Sales - Communication Services is based on a sampled enumeration of businesses that have been identified as active ISPs.

Revisions

25 The survey frame and sample are updated annually to ensure that the sample remains representative of the target population.

Seasonally adjusted and trend estimates

26 Original estimates only are available, with a view to publish seasonally adjusted and trend estimates in the future.

Comparability with national accounts and other estimates

27 The Survey of Consumer Sales has collected data to provide new indicators of household expenditure for categories currently outside the scope of Retail Trade. The experimental estimates presented in this publication will differ from corresponding HFCE statistics as published in Australian National Accounts: National Income, Expenditure and Product (cat. no. 5206.0). More detail on the compilation of HFCE is available from Australian System of National Accounts: Concepts, Sources and Methods (cat. no. 5216.0).

28 The Communication Services estimates presented in this publication are estimates derived from revenue data obtained from major telecommunication service providers only and include telephone and internet services only. The aggregate excludes Postal Services and the sale of equipment.

29 The experimental estimates are not comparable to the value of energy sales published in the Business Indicators, Australia (cat. no. 5676.0) and Australian Industry (cat. no. 8155.0) because the estimates within these publications are classified according to ANZSIC and do not exclude sales to business customers and government customers.

General acknowledgement

30 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.

31 As well as the statistics included in this and related publications, the ABS have other relevant data available. Enquiries should be made to the National Information and Referral Service on 1300 135 070.

Technical note - revisions to trend estimates

Effect of new seasonally adjusted estimates on trend estimates

1 As original estimates become available each month, the estimates of the seasonal pattern and trend series are updated to include the most up to date information. This means that most seasonally adjusted and trend estimates are likely to be revised when the next month's data become available. To assist readers of this publication in analysing retail trends, the 'what-if' chart presents the approximate effect that two possible future scenarios would have on the current and previous trend movement estimates of total retail turnover for Australia. Note that the 'what-if' graph gives an idea of possible trend revisions based on future seasonally adjusted estimates and does not account for revised seasonally adjusted estimates based on additional original data. ABS research shows that approximately 75% of the total revision to the trend estimate at the current end of the series is due to the use of different asymmetric moving averages when a new data point becomes available. For more information see the trend estimates section of the Explanatory Notes. The two future scenarios considered are based on the 25th and 75th percentiles of seasonally adjusted movements calculated from the historical series. The two scenarios are as follows:

Scenario 1. Next month's seasonally adjusted estimate of retail turnover rises 0.517%.
Scenario 2. Next month's seasonally adjusted estimate of retail turnover rises 0.052%.

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Abbreviations

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ABNAustralian Business Number
ABSAustralian Bureau of Statistics
ANZSICAustralian and New Zealand Standard Industrial Classification
ARIMAautoregressive integrated moving average
ATOAustralian Taxation Office
n.e.c.not elsewhere classified
PAYGWpay-as-you-go withholding
RSErelative standard error