|Most recent month on a year earlier||Most recent 3 months on a year earlier||Most recent month on previous month||Most recent 3 months on previous 3 months|
|Value excluding automotive fuel||3.4||3.3||0.8||1.0|
|Volume excluding automotive fuel||2.9||2.9||0.6||0.7|
The ONS Retail Sales Index (RSI) is calculated from a sample of 5,000 retailers representing approximately 90 per cent of all known retail activity within Great Britain. The sample contains 900 large retailers, that is, businesses employing more than 100 employees or with annual turnover greater than £60 million, and a random sample of smaller retailers. Retailers in the sample are asked to provide their total retail sales turnover and total turnover for sales made via the Internet for the specified period. The RSI is used to inform decisions on the current economic performance of the retail sector and is a data source for Gross Domestic Product. The September 2012 period covers the dates 26 August 2012 to 29 September 2012.
In September 2012 the amount of goods bought (volume) in the retail sector was estimated to have increased by 2.5 per cent compared with September 2011. The amount spent on goods (value) in the retail sector was estimated to have increased by 3.2 per cent over the same period, whilst the price of goods sold (store price inflation) increased by 0.7 per cent year-on-year, up from 0.2 per cent in August 2012.
The amount spent on goods in the retail sector (all retailing sales values) has been increasing since the beginning of the series in January 1996. The amount of goods bought also increased until 2007 and then stagnated up to August 2011. This indicates that since 2007, consumers have continued to buy a similar amount of goods but have spent more to do so.
The amount spent on goods is affected by the amount consumers buy and the price of the goods bought. An increase in the amount spent is therefore due to an increase in the prices of goods sold, an increase in the amount bought or a combination of both.
The increase in the amount spent between 2000 and 2007 was mainly due to an increase in the amount bought as prices generally fell over this period. However since 2007 the increase in the amount spent is primarily due to a rise in the prices of goods sold.
Figure 1 shows the seasonally adjusted levels of the amount spent on retail goods (value) and the amount of goods bought (volume) in the retail sector. Also shown is the index level for the price of goods sold (non-seasonally adjusted).
From August 2011 the amount of goods bought (volume) has increased, this is mainly due to the rate of annual price increases slowing, however, looking at the monthly change we see that the price of goods sold has increased in August and September 2012. The main contributions to the increase in the amount bought came from the non food sector and stores selling online or through mail order (non-store retailing).
In September 2012, the amount of goods bought (volume) in the non-food sector was estimated to have increased by 4.3 per cent compared with September 2011. Department stores, stores selling textiles, clothing and footwear and other stores (which includes, for example, stores selling sporting goods and toys, watches and jewellery and computers and telecoms) all saw an increase in sales, whilst in household goods stores less goods were sold.
The amount of goods bought in the clothing sector was estimated to have increased by 5.1 per cent in September 2012 compared with September 2011. The amount spent was estimated to have increased by 5.0 per cent and the price of goods fell by 0.1 per cent over the same period.
Figure 2, shows the seasonally adjusted levels of the amount spent on retail goods (value) and the amount of goods bought (volume) in the textile, clothing and footwear stores. Also shown is the index level for the price of goods sold (non-seasonally adjusted).
The chart shows the seasonality of the price of goods within this sector. Prices are at their lowest in January and July of each year which is consistent with the traditional winter and summer sales periods for the clothing sector.
Although prices were at a similar level in September 2012 compared with a year ago, the textile clothing and footwear sector provided the main source of upward pressure to the monthly rise in the prices of goods sold across all retailing. It is estimated that the prices of goods sold increased by 3.8 per cent between August and September 2012 and by 2.4 per cent between July and August 2012.
Sales in this sector are dominated by clothing stores which account for approximately 86 pence of every pound spent in Textile, clothing and footwear stores, footwear stores account for 10 pence of every pound and textile stores 4 pence of every pound. Feedback from retailers in this sector suggest that sales were boosted as consumers put off purchases of school uniforms until early September and that new winter collections had increased sales.
The Retail Sales Index (RSI) measures spending on retail goods (value) and the amount of goods bought (volume) in Great Britain. Figures are adjusted for seasonal variations unless otherwise stated and the reference year for both value and volume statistics is 2009=100. For an explanation of the terms used in this bulletin, please see the background notes section. Care should be taken when using the month-on-month growth rates due to their volatility; an assessment of the quality of the retail statistics is available in the background notes.
|% of all retailing||Volume year-on-year growth (%)||Contribution to all retailing (% points)||Value year-on-year growth (%)||Contribution to all retailing (% points)|
|Predominantly food stores||41.3||0.5||0.3||2.5||1.0|
|Predominantly non-food stores|
|Textile, clothing and footwear stores||12.3||5.1||0.6||5.0||0.6|
|Household goods stores||8.8||-2.7||-0.2||-2.4||-0.2|
In the five week period of September 2012 the total non-seasonally adjusted value of spending in the retail sector was estimated to be £33.0 billion. This compares with the figure of £26.0 billion in the four weeks of August 2012 and £32.0 billion in the five weeks of September 2011.
This equates to an average weekly spend of £6.6 billion in September 2012, £6.5 billion in August 2012 and £6.4 billion in September 2011.
The average weekly online spend (Internet sales values non-seasonally adjusted) in September 2012 was estimated to be £507.8 million, which was an increase of 9.4 per cent when compared with September 2011.
The amount spent online was estimated to account for 8.8 per cent of all retail spending excluding automotive fuel.
More was spent online in the non-store retailing sector than any other sector. Spending online now accounts for 63.0 per cent of total spending in this sector up from 62.9 per cent in September 2011. In the food sector 3.1 per cent of spending was spent online, up from 2.7 per cent a year earlier. This sector has the lowest proportion of online spend in relation to all spending.
Internet sales measure how much was spent online through retailers in Great Britain. Figures are non-seasonally adjusted and the reference year is 2010=100. Table 3 shows the year-on-year growth rates for total Internet sales, by sector and the contribution that each sector makes to total Internet sales.
|Category||Weight||Year on year growth||Contribution to year on year growth|
|Textile, clothing and footwear stores||11.7||13.7||1.6|
|Household goods stores||8.2||10.4||0.9|
Predominantly food stores in September 2012 saw an increase in the amount of goods bought (0.5 per cent) and the amount spent (2.5 per cent) when compared with September 2011. Average prices were estimated to have increased by 2.0 per cent in the year to September 2012.
In September 2012 estimated average weekly sales were £2.7 billion; of this, 3.1 per cent of sales (£83.8 million) were made via the Internet.
Predominantly non-food stores in September 2012 saw an increase in the amount of goods bought (4.3 per cent) and the amount spent (3.6 per cent) when compared with September 2011. Average prices were estimated to have decreased by 0.6 per cent in the year to September 2012.
In September 2012 the estimated average weekly sales were £2.7 billion; of this, 7.3 per cent of sales (£195.3 million) were made via the Internet.
Non-specialised stores in September 2012 saw an increase in the amount of goods bought (7.7 per cent) and the amount spent (6.2 per cent) when compared with September 2011. Average prices were estimated to have decreased by 1.3 per cent in the year to September 2012.
In September 2012 estimated average weekly sales were £0.5 billion; of this, 6.9 per cent of sales (£34.2 million) were made via the Internet.
Textile, clothing and footwear stores in September 2012 saw an increase in the amount of goods bought (5.1 per cent) and the amount spent (5.0 per cent) when compared with September 2011. Average prices were estimated to have decreased by 0.1 per cent in the year to September 2012.
In September 2012 estimated average weekly sales were £0.8 billion; of this, 8.8 per cent of sales (£71.7 million) were made via the Internet.
Household goods stores in September 2012 saw a decrease in the amount of goods bought (2.7 per cent) and the amount spent (2.4 per cent) when compared with September 2011. Average prices were estimated to have increased by 0.3 per cent in the year to September 2012.
In September 2012 estimated average weekly sales were £0.6 billion; of this, 5.5 per cent of sales (£30.2 million) were made via the Internet.
Other stores in September 2012 saw an increase in the amount of goods bought (6.5 per cent) and the amount spent (5.0 per cent) when compared with September 2011. Average prices were estimated to have decreased by 1.5 per cent in the year to September 2012.
In September 2012 estimated average weekly sales were £0.8 billion; of this, 7.2 per cent of sales (£59.2 million) were made via the Internet.
Non-store retailing in September 2012 saw an increase in the amount of goods bought (9.5 per cent) and the amount spent (8.5 per cent) when compared with September 2011. Average prices were estimated to have decreased by 0.9 per cent in the year to September 2012.
In September 2012 estimated average weekly sales were £0.4 billion; of this, 63.0 per cent of sales (£228.6 million) were made via the Internet.
Predominantly automotive fuel stores in September 2012 saw a decrease in the amount of goods bought (1.1 per cent) and an increase in the amount spent (1.7 per cent) when compared with September 2011. Average prices were estimated to have increased by 2.9 per cent in the year to September 2012.
In September 2012 estimated average weekly sales were £0.8 billion.
Table 4 illustrates the mix of experiences among different sized retailers. It shows the distribution of reported change in sales values of businesses in the RSI sample, ranked by size of business (based on number of employees). This table shows for example, that the largest retailers, with 100 or more employees, reported an average increase in sales of 3.5 per cent between September 2011 and September 2012. In contrast smaller retailers employing 10 to 39 employees reported an average increase in sales of 13.4 per cent.
|Number of employees||Weights (%)||Growth since September 2011 (%)|
The reference table, Business Analysis (30.5 Kb Excel sheet) shows the extent to which individual businesses experienced actual changes in their sales between September 2011 and September 2012. The table contains information only from businesses that reported in September 2011 and September 2012. Cells with values less than 10 are suppressed for some classification categories; this is denoted by n.a. Note that ‘large’ businesses are defined as those with 100+ employees and 10–99 employees with annual turnover of more than £60 million, while ‘small and medium’ is defined as 0–99 employees.
Improvements to be introduced next month
No improvements next month.
The findings of the annual Seasonal Adjustment Review (SAR) have been implemented.
The Olympics took place from 27 July to 12 August 2012 (with a few events starting on 25 July), and the Paralympics from 29 August to 9 September. For most economic statistics, any direct effects of the Olympics was mainly reflected in the August estimate, although some of the Paralympics-associated activity took place in September. Wider effects, for example if the presence of the Olympics has influenced the number of non-Olympics tourist visits, may of course affect any of the summer months.
This commentary is intended to help users to interpret the statistics in the light of events. As explained in ONS’s Special Events policy, it is not possible to make an estimate of the effect of the Olympics and Paralympics on particular series only on the basis of information collected in those series. More details of how certain series are affected are in an Information Note and an article explaining how various elements are reflected in the National Accounts was published in July 2012.
Understanding the data
1. Quick Guide to the Retail Sales Index (116.9 Kb Pdf) .
2. Interpreting the data
The Retail Sales Index (RSI) is derived from a monthly survey of 5,000 businesses in Great Britain. The sample represents the whole retail sector and includes all large retailers and a representative panel of smaller businesses. Collectively all of these businesses cover approximately 95 per cent of the retail sector in terms of turnover.
The RSI covers sales only from businesses registered as retailers according to the Standard Industrial Classification (SIC), an internationally agreed convention for classifying industries. The retail sector is division 47 of the SIC 2007 and retailing is defined as the sale of goods to the general public for household consumption. Consequently, the RSI includes all Internet businesses whose primary function is retailing and also covers Internet sales by other British retailers, such as online sales by supermarkets, department stores and catalogue companies. The RSI does not cover household spending on services bought from the retail sector as it is designed to only cover goods. Respondents are asked to separate out the non-goods elements of their sales, for example income from cafeterias. Consequently, online sales of services by retailers, such as car insurance, would also be excluded.
The monthly survey collects two figures from each sampled business: the total turnover for retail sales for the standard trading period, and a separate figure for sales made over the Internet. The total turnover will include Internet sales. The separation of the Internet sales figure allows an estimate relating to Internet sales to be calculated separately.
3. Definitions and explanations
The value or current price series records the growth since the base period (currently 2009) of the value of sales ‘through the till’ before any adjustment for the effects of price changes.
The volume or constant price series are constructed by removing the effect of price changes from the value series. The Consumer Prices Index (CPI) is the main source of the information required on price changes. In brief, a deflator for each type of store (5-digit SIC) is derived by weighting together the CPIs for the appropriate commodities, the weights being based on the pattern of sales in the base year. These deflators are then applied to the value data to produce volume series.
The implied deflator or store price inflation is derived by comparing the value and volume data non-seasonally adjusted. In general, this implied price deflator should be quite close to the retail component of the CPI.
4. Use of the data
The value and volume measures of retail sales estimates are widely used in private and public sector organisations. For example, private sector institutions such as investment banks, the retail sector itself and retail groups use the data to inform decisions on the current economic performance of the retail sector, these organisations are most interested in a long term view of the retail sector that can be obtained from year-on-year growth rates. Public sector institutions use the data to assist in informed decision and policy making and tend to be most interested in a snapshot view of the retail sector, which is taken from the month-on-month growth rates.
Information on retail sales methodology is available in Retail Sales Methodology and Articles.
1. Composition of the data
Estimates in this statistical bulletin are based on financial data collected through the monthly Retail Sales Inquiry. The response rates for the current month reflect the response rates at the time of publication. Late returns for the previous month’s data are included in the results each month. Response rates for historical periods are updated to reflect the current level of response at the time of this publication.
|Overall response rates|
2. Seasonal adjustment
Seasonally adjusted estimates are derived by estimating and removing calendar effects (for example Easter moving between March and April) and seasonal effects (for example increased spending in December as a result of Christmas) from the non-seasonally adjusted (NSA) estimates. Seasonal adjustment is performed each month, and reviewed each year, using the standard, widely used software, X-12-ARIMA. Before adjusting for seasonality, prior adjustments are made for calendar effects (where statistically significant), such as returns that do not comply with the standard trading period (see section Methods, Calendar effects), bank holidays, Easter and the day of the week on which Christmas occurs.
The data collected from the retail sales survey is the amount of money taken through the tills of retailers; these are non-seasonally adjusted data. This data consists of three components:
Trend which describes long-term or underlying movements within the data.
Seasonal which describes regular variation around the trend, that is peaks and troughs within the time series, the most obvious in this case being the peak in December and the fall in January.
Irregular or ‘noise’, for example deeper falls within the non-seasonally adjusted series due to harsh weather impacting on retail sales.
To ease interpretation of the underlying movements in the data, the seasonal adjustment process estimates and removes the seasonal component to leave a seasonally adjusted time series consisting of the trend and irregular components.
In the non-seasonally adjusted retail sales index we see large rises in December each year and a fall in the following January, but these are not evident in the seasonally adjusted index. This peak in December is larger than the subsequent fall but the trend and irregular components in both months are likely to be similar, meaning that the movements in the unadjusted series are almost completely as a result of the seasonal pattern.
3. Calendar effects
The calculation of the RSI has an adjustment to compensate for calendar effects that arise from the differences in the reporting periods. The reporting period for September 2012 was 26 August 2012 to 29 September 2012, compared with 28 August 2011 to 1 October 2011 the previous year. Table 6 shows the differences between the calendar and seasonally adjusted estimates.
|Year on year percentage change|
1. Basic quality information
The standard reporting periods can change over time due to the movement of the calendar. Every five or six years the standard reporting periods are brought back into line by adding an extra week. For example, January is typically a four-week standard period but January 1986, 1991, 1996, 2002 and 2008 were all five-week standard periods. The non-seasonally adjusted estimates will still contain calendar effects. If the non-seasonally adjusted estimates are used for analysis this can lead to a distortion depending on the timing of the standard reporting period in relation to the calendar, previous reporting periods and how trading activity changes over time.
The non-seasonally adjusted series contain elements relating to the impact of the standard reporting period, moving seasonality and trading day activity. When making comparisons it is recommended that users focus on the seasonally adjusted estimates as these have the systematic calendar related component removed. Due to the volatility of the monthly data, it is recommended that growth rates are calculated using an average of the latest three months of the seasonally adjusted estimates.
When interpreting the data, consideration should be given to the relative weighted contributions of the sectors within the all retailing series. Based on SIC 2007 data, total retail sales consists of: predominantly food stores 41.3 per cent, predominantly non-food stores 41.6 per cent, non-store retailing 5.3 per cent and automotive fuel 11.8 per cent.
2. Standard errors
The standard error of an index movement is a measure of the spread of possible estimates of that movement likely to be obtained when taking a range of different samples of retail companies of the same size. This provides a means of assessing the accuracy of the estimate: the lower the standard error, the more confident one can be that the estimate is close to the true value for the retail population. An approximate 95 per cent confidence interval for the index movement is roughly twice the standard error. The paper ‘ Measuring the accuracy of the Retail Sales Index’ (1.04 Mb Pdf) , written by Winton, J and Ralph, J (2011) reports on the calculation of standard errors for month-on-month and year-on-year growth rates in the RSI as well as providing an overview of standard errors and how they can be interpreted.
The standard error for year-on-year growth in all retail sales volumes is 0.7 per cent. Using a 95 per cent confidence interval this means that the year-on-year growth rate for all retail sales volumes falls within the range 2.4 ± 1.4 per cent.
The standard error for month-on-month growth in all retail sales volumes is 0.4 per cent. Using a 95 per cent confidence interval this means that the month-on-month growth rate for all retail sales volumes falls within the confidence interval 1.8 ± 0.8.
3. Summary quality report
A Summary Quality (93.5 Kb Pdf) Report for the RSI.
This report describes, in detail the intended uses of the statistics presented in this publication, their general quality and the methods used to produce them.
4. Revision triangles
Revisions to data provide one indication of the reliability of key indicators. The table below shows summary information on the size and direction of the revisions which have been made to the volume data covering a five-year period. Note that changes in definition and classification mean that the revision analysis is not conceptually the same over time. A statistical test has been applied which has shown that the average revision in month-to-month statistics are not statistically different from zero.
A spreadsheet giving these estimates and the calculations behind the averages in the table is available on the ONS website (1.8 Mb ZIP) .
|Growth in latest period (per cent)||Revisions between first publication and estimates twelve months later (percentage points)|
|Average over the last five years (mean revision)||Average over the last five years without regard to sign (average absolute revision)|
|Latest three months compared with previous three months||1.0||-0.23||0.35|
|Latest month compared with previous month||0.6||-0.10||0.44|
Methodological changes were introduced in the April 2009 and January 2010 releases. For more detail see:
Details of the policy governing the release of new data are available from the Media Relations Office. Also available is a list of the organisations given pre-publication access (38.5 Kb Pdf) to the contents of this bulletin.
The complete run of data in the tables of this statistical bulletin is available to view and download in electronic format using the ONS Time Series Data service. Users can download the complete bulletin in a choice of zipped formats, or view and download their own sections of individual series. The Time Series Data are available.
Alternatively, for low-cost tailored data call 0845 601 3034 or email firstname.lastname@example.org
Copyright and reproduction
© Crown copyright 2012
Under the terms of the Open Government Licence and UK Government Licensing Framework, anyone wishing to use or re-use ONS material, whether commercially or privately, may do so freely without a specific application for a licence, subject to the conditions of the OGL and the Framework.
For further information, contact the Office of Public Sector Information, Crown Copyright Licensing and Public Sector Information, Kew, Richmond, Surrey, TW9 4DU.
Tel: +44 (0)20 8876 3444
Details of the policy governing the release of new data are available by visiting www.statisticsauthority.gov.uk/assessment/code-of-practice/index.html or from the Media Relations Office email: email@example.com
These National Statistics are produced to high professional standards and released according to the arrangements approved by the UK Statistics Authority.
|Kate Davies||+44 (0)1633 455602||ONSfirstname.lastname@example.org|