|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||3.9||3.3||0.8||0.9|
|Volume excluding automotive fuel||3.0||1.9||0.9||0.9|
The ONS retail sales index 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 retailer’s, businesses with employment of more than 100 or 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 May 2012 period covers the dates 29 April 2012 to 26 May 2012.
In May 2012 the estimated all retail sales volumes index increased by 2.4 per cent compared with May 2011 and increased by 1.4 per cent compared with April 2012.
The estimated all retail sales value index increased by 3.3 per cent compared with May 2011 and increased by 1.0 per cent compared with April 2012.
Store price inflation slowed to 0.9 per cent, its lowest rate since October 2009. The Consumer Prices Index slowed to 2.8 per cent in May, its lowest rate since November 2009. Two of the main sources of downward pressure to store price inflation came from the non-specialised stores sector where prices are estimated to have fallen by 2.0 per cent in May 2012 compared with May 2011, and other stores where prices are 1.9 per cent lower over the same period.
Figure 1 shows the seasonally adjusted index level of both sales volumes and sales values for the non-specialised non-food stores sector, which includes department stores and stores that sell a multitude of products.
Sales values for any retail sector can be viewed as how much has been spent on goods sold by this sector. An increase in sales values could be down to an increase in the prices of goods sold, an increase in the amount of goods bought or a combination of both. To estimate the amount of goods bought or volume, the value series is adjusted to remove the effect of price changes.
Between May 2010 and December 2010, sales volumes and values in these stores were relatively flat and feedback from retailers suggests that the peak in January 2011 was caused by consumers purchasing big ticket items in a rush to beat the VAT rise from 17.5 per cent to 20.0 per cent in that month.
From May to November 2011 the value and volume series increase at a similar rate and this suggests that the change in the value series is mainly down to an increase in the number of goods bought.
The implied price deflator can be viewed as a measure of store price inflation and as shown in Figure 1 from December 2011 prices are lower than they were in the previous year. Therefore this sector is experiencing store price deflation, that is the prices of goods sold by this sector have been falling. The faster rate of growth in the value and volume series in this sector from November 2011 onwards is a consequence of consumers purchasing more in these stores as prices fall. Feedback from retailers in this sector suggests that the increase in sales is a result of promotions.
In May 2012, sales volumes in this sector have increased by 11.3 per cent compared with May 2011 and by 0.8 per cent compared with April 2012. Sales values increased by 9.3 per cent compared with May 2012 and by 0.5 per cent compared with April 2012. The prices of goods sold within these stores were estimated to have fallen by 2.0 per cent between May 2011 and May 2012.
The Retail Sales Index (RSI) measures spending (value) and volume of retail sales in Great Britain. Figures are adjusted for seasonal variations unless otherwise stated and the reference year for both value and volume statistics is 2008=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||41.7||1.0||0.5||4.1||1.7|
|Predominantly non-food stores|
|Textile, clothing and footwear stores||12.2||-1.0||-0.1||0.7||0.1|
|Household goods stores||9.7||5.1||0.5||3.9||0.4|
In the four week period of May 2012 the total non-seasonally adjusted value of spending in the retail sector was estimated to be £26.4 billion. This compares with £26.0 billion in the four weeks of April 2012 and £25.6 billion in the four week period of May 2011.
In May 2012 the average weekly non-seasonally adjusted value of spending in the retail sector was estimated to be £6.6 billion.
Internet average weekly sales values (non-seasonally adjusted) in May 2012 were estimated to be £510.9 million, an increase of 21.6 per cent when compared with May 2011.
Internet sales are now estimated to account for 8.8 per cent of all retail sales values excluding automotive fuel.
The Internet sales statistics measure how much has been spent online through retailers in Great Britain. Figures are non-seasonally adjusted and the reference year is 2010=100. The table below shows the year-on-year growth for total Internet sales, for each 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||21.9||2.4|
|Household goods stores||8.2||34.7||2.7|
Predominantly food stores sales volumes in May 2012 increased by 1.0 per cent when compared with May 2011. Over the same period the value of sales increased by 4.1 per cent. Average price inflation in predominantly food stores was 3.0 per cent in the year to May 2012, the lowest rate since July 2010 (2.8 per cent). This is reasonably consistent with the Consumer Prices Index for food and non-alcoholic beverages, which shows an increase of 3.3 per cent in May, compared with May 2011.
In May 2012 the estimated average weekly sales were £2.8 billion, more than any other sector; of this, 3.3 per cent of sales (£92.4 million) were made via the Internet.
Predominantly non-food stores sales volumes in May 2012 increased by 3.3 per cent compared with volumes in May 2011 while the value of sales increased by 2.6 per cent. Average prices showed deflation of 0.6 per cent in the year to May 2012.
In May 2012 the estimated average weekly sales were £2.7 billion; of this, 7.4 per cent of sales (£197.7 million) were made via the Internet.
Non-specialised stores sales volumes increased by 11.3 per cent in May 2012 when compared with May 2011. This was the highest increase since January 2000 (12.4 per cent). A contributor to the increase in volume sales was an estimated fall in prices of 2.0 per cent between May 2011 and May 2012, the largest fall since January 2009 when prices fell by 2.6 per cent. This is consistent with feedback from retailers that increased sales are due to store promotions. The value of sales increased by 9.3 per cent in the year to May 2012, which is the highest since January 2011 (10.5 per cent).
In May 2012 the estimated average weekly sales were £0.5 billion; of this, 7.0 per cent of sales (£35.5 million) were made via the Internet.
Textile, clothing and footwear stores sales volumes in May 2012 fell by 1.0 per cent when compared with May 2011. Sales values grew by 0.7 per cent over the same period. This sector saw price inflation of 1.8 per cent in the year to May 2012, which is the same as April 2011 and the lowest since October 2010 (1.3 per cent).
In May 2012 the estimated average weekly sales were £0.8 billion; of this, 8.9 per cent of sales (£68.1 million) were made via the Internet.
Household goods stores sales volumes rose by 5.1 per cent in May 2012 compared with May 2011, the largest rise since January 2011 (6.9 per cent). The value of sales rose by 3.9 per cent over the same period, the largest increase since a rise of 7.6 per cent in January 2011. Average prices are estimated to show deflation of 0.5 per cent.
In May 2012 the estimated average weekly sales were £0.6 billion; of this, 5.7 per cent of sales (£33.2 million) were made via the Internet.
Other stores sales volumes increased by 1.4 per cent in the year to May 2012. Sales values fell by 0.6 per cent over the same period. Average prices are estimated to have fallen by 1.9 per cent in the year to May 2012, the largest fall since July 2009 (2.2 per cent).
In May 2012 the estimated average weekly sales were £0.8 billion; of this, 7.6 per cent of sales (£60.9 million) were made via the Internet.
Non-store retailing sales volumes increased by 14.9 per cent in May 2012 compared with May 2011. Sales values increased by 13.5 per cent over the same period. Store price inflation is estimated to have fallen by 1.2 per cent in the year to May 2012, the largest fall since November 2009 (1.4 per cent).
In May 2012 the estimated average weekly sales were £0.4 billion; of this, 61.2 per cent of sales (£220.8 million) were made via the Internet.
Predominantly automotive fuel stores sales volumes decreased by 2.9 per cent in the year to May 2012. Sales values decreased by 1.8 per cent in May 2012 compared with May 2011. Average prices are estimated to have increased by 1.2 per cent in the year to May 2012.
In May 2012 the estimated average weekly sales were £0.8 billion.
The Increase in Reported Retail Sales Values table illustrates the mix of experiences among different sized retailers. It shows the distribution of the reported increase in sales values of businesses in the RSI sample, ranked by size of business (based on number of employment). For example, this shows that the largest retailers, with 100 or more employment, reported an average increase in sales of 2.9 per cent between May 2011 and May 2012.
|Number of employment||Weights (%)||Growth since May 2011 (%)|
The Changes in reported retail sales between May 2011 and May 2012 standard reporting period table (30.5 Kb Excel sheet) illustrates the extent to which individual businesses experienced actual changes in their sales between May 2011 and May 2012. The table contains information only from businesses that reported in both periods. Cells with values less than 10 are suppressed for some classification categories; this is denoted by n.a. Note that ‘large’ is defined as 100+ employment and 10–99 employment with annual turnover of more than £60 million, while ‘small and medium’ is defined as 0–99 employment.
Improvements to be introduced next month
From 19 July 2012, the Retail Sales estimate will incorporate a rebase of the indices to 2009=100 to align with National Accounts outputs.
We welcome feedback on this statistical release and its associated products from our users. In particular we are interested in feedback on the content, format, number and structure of data tables available when printing the pdf version of this statistical bulletin. Please email email@example.com with your feedback.
1. In streamlining the Retail Sales, Data Tables the following changes have been made:
Tables 1A to 1L, table 10 in last month’s publication, provide the chained volume of retail sales (2008=100), seasonally adjusted indexes for all retailing and individual retail industries,
Tables 2A to 2L, table 9 in last month’s publication, provide the value of retail sales at current prices (2008=100), seasonally adjusted indexes for all retailing and individual retail industries,
Tables 3A to 3T, table 8 in last month’s publication, provide the chained volume of retail sales (2008=100) non-seasonally adjusted indexes for all retailing, individual retail industries and where non-disclosive by size of store,
Tables 4A to 4T, table7 in last month’s publication provide the value of retail sales at current prices (2008=100) non-seasonally adjusted indexes for all retailing, individual retail industries and where non-disclosive by size of store.
2. As part of the celebrations for the Queen’s Diamond Jubilee there are changes to bank holidays in May and June 2012. The late May bank holiday, which would have fallen in the RSI June trading period, has been moved to the calendar month of June and an additional day’s holiday has been added. The change to the holidays will count as a statistical special event in line with ONS’s policy on Special Events. Users are therefore likely to see an effect in June 2012 data. ONS will include commentary with releases as usual, including commentary specifically to help users with the interpretation of statistics in these two months. Nevertheless, caution should be taken when interpreting the monthly movements in affected outputs involving May and June 2012.
National Statistics are produced to high professional standards set out in the Code of Practice for Official Statistics. They undergo regular quality assurance reviews to ensure that they meet customer needs. They are produced free from any political interference.
Understanding the data
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 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.
The value or current price series records the growth since the base period (currently 2008) 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 CPI’s 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 estimated prices of retail sales (sometimes called the implied price deflator) 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 institutions. 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 institutions 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 (124.3 Kb Pdf) is available on the ONS website.
A video explaining retail sales is available on the ONS YouTube Channel.
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.
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 May 2012 was 29 April 2012 to 26 May 2012, compared with 1 May 2011 to 28 May 2011 the previous year. For example, the annual growth in sales volume between May 2011 and May 2012 requires a 0.2 per cent adjustment to take account of the differences in reporting periods and other calendar effects.
|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 41.7 per cent, predominantly non-food stores 43.2 per cent, non-store retailing 4.9 per cent and automotive fuel 10.2 per cent.
2. Standard errors
A measure of the accuracy of the RSI (1.04 Mb Pdf) has been produced by estimating the standard errors of index movements. The paper ‘Measuring the accuracy of the Retail Sales Index’, written by Winton, J and Ralph, J (2011) as part of the Economic & Labour Market Review, February 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.
3. Summary quality report
A Summary Quality Report for the RSI (114 Kb Pdf) can be found on the ONS website.
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.
|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||0.5||-0.22||0.34|
|Latest month compared with previous month||1.4||-0.10||0.45|
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 (38.5 Kb Pdf) .
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 can be accessed on the ONS website.
Alternatively, for low-cost tailored data call 0845 601 3034 or email firstname.lastname@example.org
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 455617||ONSfirstname.lastname@example.org|