|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|
|Amount spent (Value)||1.6||2.5||-0.4||1.2|
|Quantity bought (Volume)||0.6||1.8||-0.8||0.2|
|Value excluding automotive fuel||1.9||2.8||-0.3||0.6|
|Volume excluding automotive fuel||1.1||2.2||-0.7||0.1|
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 the 900 largest retailers, i.e. 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 October 2012 period covers the dates 30 September 2012 to 27 October 2012.
In October 2012 the quantity of goods bought in the retail sector (volume) was estimated to have increased by 0.6 per cent compared with October 2011. The amount spent (value) was estimated to have increased by 1.6 per cent over the same period. The estimated prices of goods sold in the retail sector (as measured by the implied price deflator) have increased by 0.9 per cent since October 2011.
To enable a comparison of change, Figure 1 shows the quantity of goods bought in the retail sector (all retailing sales volumes) as indices referenced to 2009. It shows that in the early years of this series the underlying pattern in the retail sector was one of growth. However, this changed around November 2007, and the quantity of goods bought in the retail sector hovered around the 100 index points level until September 2011. This indicates that during this period the quantity of goods bought in the retail sector was relatively flat. From September 2011 the quantity of goods bought in the retail sector has increased but more slowly compared with between 2000 and 2007.
The retail industry is divided into four retail sectors; predominantly food stores, predominantly non-food stores, non-store retailing and stores selling automotive fuel. Each sector contributes a different amount to all retailing as shown in Figure 2. More information on the stores within each sector can be found in the reference table Index Categories and their Percentage Weights (37.5 Kb Excel sheet) .
Between September 2012 and October 2012, the quantity of goods bought in the retail sector was estimated to have fallen by 0.8 per cent. Over the same period, the quantity of goods bought:
in the food store sector was estimated to have fallen by 0.6 per cent,
in the non-food sector was estimated to have fallen by 1.0 per cent,
in the non-store sector was estimated to have increased by 1.3 per cent,
in petrol stations was estimated to have fallen by 1.7 per cent.
Given that the contribution of non-store retailing is equivalent to five pence in every pound spent, the rise in the quantity of goods bought in this sector did not offset the falls seen in the other sectors.
Looking at the annual picture the impact of the non-store retailing sector is significant. Comparing October 2012 with October 2011, the quantity of goods bought:
in the food store sector was estimated to have fallen by 0.7 per cent,
in the non-food sector was estimated to have increased by 1.3 per cent,
in the non-store sector was estimated to have increased by 12.1 per cent,
and in petrol stations was estimated to have fallen by 3.4 per cent.
In terms of contributions to all retailing (see Figure 2), the large estimated growth in the non-store retailing sector far outweighs the falls seen in the food sector and petrol stations. Even though the non-food sector has a far greater weight than non-store, it was the non-store sector that provided the largest contribution to the all retailing year-on-year growth.
The Retail Sales Index (RSI) measures spending on retail goods (value) and the quantity 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||-0.7||-0.3||2.0||0.8|
|Predominantly non-food stores|
|Textile, clothing and footwear stores||12.3||2.0||0.2||2.3||0.3|
|Household goods stores||8.8||-4.0||-0.4||-4.0||-0.4|
In the October 2012 four week reporting period the estimated amount spent in the retail sector was £27 billion (non-seasonally adjusted). This compares with an estimated £33 billion in the September 2012 five week reporting period and £27 billion in the October 2011 four week reporting period.
This equates to an average estimated weekly spend of £6.8 billion in October 2012, £6.6 billion in September 2012, and £6.7 billion in October 2011.
The average weekly spend online (Internet sales values non-seasonally adjusted) in October 2012 was estimated at £562 million, which was an increase of 11.0 per cent when compared with October 2011.
The amount spent online was estimated to account for 9.4 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 62.2 per cent of total spending in this sector, up from 62.1 per cent in October 2011.
In the food sector 3.2 per cent of spending was spent online, up from 2.8 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 % points|
|Textile, clothing and footwear stores||11.7||22.2||2.7|
|Household goods stores||8.2||18.5||1.6|
Predominantly food stores in October 2012 saw a decrease in the quantity of goods bought (0.7 per cent) and an increase in the amount spent (2.0 per cent) when compared with October 2011. The prices of goods sold were estimated to have increased by 2.7 per cent in the year to October 2012.
In October 2012 estimated average weekly sales were £2.8 billion; of this, 3.2 per cent of sales (£89 million) were made via the Internet.
Predominantly non-food stores in October 2012 saw an increase in the quantity of goods bought (1.3 per cent) and the amount spent (0.6 per cent) when compared with October 2011. The prices of goods sold were estimated to have decreased by 0.6 per cent in the year to October 2012.
In October 2012 the estimated average weekly sales were £2.8 billion; of this, 7.7 per cent of sales (£217 million) were made via the Internet.
Non-specialised stores, or department stores, in October 2012 saw an increase in the quantity of goods bought (8.2 per cent) and the amount spent (6.3 per cent) when compared with October 2011. The prices of goods sold were estimated to have decreased by 1.7 per cent in the year to October 2012.
In October 2012 estimated average weekly sales were £0.5 billion; of this, 7.5 per cent of sales (£40 million) were made via the Internet.
Textile, clothing and footwear stores in October 2012 saw an increase in the quantity of goods bought (2.0 per cent) and the amount spent (2.3 per cent) when compared with October 2011. The prices of goods sold were estimated to have increased by 0.4 per cent in the year to October 2012.
In October 2012 estimated average weekly sales were £0.9 billion; of this, 10.2 per cent of sales (£87 million) were made via the Internet.
Household goods stores in October 2012 saw a decrease in the quantity of goods bought (4.0 per cent) and the amount spent (4.0 per cent) when compared with October 2011. The prices of goods sold were estimated to have remained unchanged in the year to October 2012.
In October 2012 estimated average weekly sales were £0.6 billion; of this, 5.5 per cent of sales (£32 million) were made via the Internet.
Other stores in October 2012 saw an increase in the quantity of goods bought (0.2 per cent) but a decrease in the amount spent (1.1 per cent) when compared with October 2011. The prices of goods sold were estimated to have decreased by 1.3 per cent in the year to October 2012.
In October 2012 estimated average weekly sales were £0.8 billion; of this, 6.8 per cent of sales (£58 million) were made via the Internet.
Non-store retailing in October 2012 saw an increase in the quantity of goods bought (12.1 per cent) and the amount spent (10.7 per cent) when compared with October 2011. The prices of goods sold were estimated to have decreased by 1.1 per cent in the year to October 2012.
In October 2012 estimated average weekly sales were £0.4 billion; of this, 62.2 per cent of sales (£256 million) were made via the Internet.
Predominantly automotive fuel stores in October 2012 saw a decrease in the quantity of goods bought (3.4 per cent) and the amount spent (0.8 per cent) when compared with October 2011. The prices of goods sold were estimated to have increased by 2.7 per cent in the year to October 2012.
In October 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 values of 2.4 per cent between October 2011 and October 2012. In contrast smaller retailers employing 10 to 39 employees reported an average increase in sales of 4.6 per cent.
|Number of employees||Weights (%)||Growth since October 2011 (%)|
The reference table, Business Analysis (30.5 Kb Excel sheet) shows the extent to which individual businesses reported actual changes in their sales between October 2011 and October 2012. The table contains information only from businesses that reported in October 2011 and October 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
From January 2013, ONS plan to stop producing the summary statistics table (57.5 Kb Excel sheet) . If these data are essential to you, please notify ONS at the e-mail address in the 'Contact us' section below and we will reconsider our plans.
Not applicable this month.
Understanding the data
1. Quick Guide to the Retail Sales Index (195 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 the 900 largest retailers and a representative panel of smaller businesses. Collectively all of these businesses cover approximately 90 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 the estimated price of goods 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. These 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 October 2012 was 30 September 2012 to 27 October 2012, compared with 2 October 2011 to 29 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. This means that the year-on-year growth rate for all retail sales volumes falls within the range 0.6 ± 1.4 per cent with a probability of 95 per cent.
The standard error for month-on-month growth in all retail sales volumes is 0.4 per cent. This means that the month-on-month growth rate for all retail sales volumes falls within the confidence interval -0.8 ± 0.8 with a probability of 95 per cent.
3. Summary quality report
The Summary Quality Report (245.6 Kb Pdf) for the RSI 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 (1.81 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||0.2||-0.24||0.36|
|Latest month compared with previous month||-0.8||-0.10||0.43|
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 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 email@example.com.
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: firstname.lastname@example.org
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||ONSemail@example.com|