|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||3.8||3.9||0.5||0.8|
|Volume excluding automotive fuel||3.3||3.1||0.0||1.4|
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 retailers, i.e. businesses employing more than 100 employees 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 July 2012 period covers the dates 1 July 2012 to 28 July 2012.
In July 2012 the estimated all retailing seasonally adjusted sales volume index increased by 2.8 per cent compared with July 2011 and increased by 0.3 per cent compared with June 2012.
The estimated all retailing seasonally adjusted sales value index increased by 3.1 per cent in July 2012 compared with July 2011 and increased by 0.8 per cent compared with June 2012.
Annual implied store price inflation slowed to 0.2 per cent (how store price inflation is estimated can be found in section 3 of the background notes). The annual Consumer Price Index (CPI) increased to 2.6 per cent in July.
Figure 1 shows the seasonally adjusted index level for all retailing sales volumes and values. Also shown is the index level for implied store price inflation. Sales values can be viewed as how much was spent on the goods sold by the retail sector; this includes for example clothes, food, and petrol.
An increase in sales values is due to an increase in the prices of goods sold, an increase in the amount bought or a combination of both. To estimate the amount of goods bought, commonly referred to as volume, the impact of price changes are removed from the value series to estimate the volume.
We can see from figure 1, that from January 2007 implied store price inflation has been rising and follows a similar path to all retailing sales values; this suggests that the increase in sales values since this date is mainly a consequence of rising prices. The volume series in figure 1 has been relatively flat since January 2008.
Figures 2 and 3 show the seasonally adjusted index levels for sales volumes and values and implied store price inflation for the non-specialised stores sector and all retailing since January 2010.
We can see from figure 3 that since January 2010 store price inflation for all retailing has risen and follows broadly a similar path to sales values. This indicates that the increase in sales values over the last two and a half years is mainly a consequence of rising prices.
In contrast, we can see from figure 2 that sales values and volumes for non-specialised stores have followed similar paths since January 2010 with store price inflation relatively flat over this period. This indicates that the increased spending within this sector is mainly due to a rise in the amount of goods bought. This is supported by feedback from retailers that suggest the increase in sales volumes has mainly been a result of on-going promotions and discounting.
The July trading period covered two days of the Olympic Games; 27 and 28 July. Feedback from retailers suggests that there has been no impact on sales from the Games in this trading period.
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 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||0.9||0.4||2.9||1.2|
|Predominantly non-food stores|
|Textile, clothing and footwear stores||12.3||-0.1||0.0||0.5||0.1|
|Household goods stores||8.8||2.0||0.2||1.5||0.1|
In the four week period of July 2012 the total non-seasonally adjusted value of spending in the retail sector was estimated to be £26.8 billion. This compares with the revised figure of £33.1 billion in the five weeks of June 2012 and £26.1 billion in the four weeks of July 2011.
This equates to an average weekly spend of £6.7 billion in July 2012, £6.6 billion in June 2012 and £6.5 billion in July 2011.
Average weekly Internet sales values (non-seasonally adjusted) in July 2012 were estimated to be £505.1 million, which is an increase of 14.2 per cent when compared with July 2011.
Internet sales were estimated to account for 8.5 per cent of all retail spending excluding automotive fuel.
The non-store retailing sector had the largest proportion of Internet sales in July 2012 accounting for 63.3 per cent of all spending in this sector, up from 60.7 per cent in July 2011. The food sector had the lowest proportion of Internet sales accounting for 2.4 per cent, down from 2.5 per cent a year earlier.
Internet sales measure how much has been 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||23.5||2.7|
|Household goods stores||8.2||11.0||0.9|
Predominantly food stores sales volumes in July 2012 increased by 0.9 per cent when compared with July 2011. Over the same period the value of sales increased by 2.9 per cent. Average prices are estimated to have increased to 1.9 per cent in the year to July 2012. This is the lowest since February 2010 (1.4 per cent).
In July 2012 the estimated average weekly sales were £2.8 billion; of this, 2.4 per cent of sales (£66.5 million) were made via the Internet.
Predominantly non-food stores sales volumes in July 2012 increased by 4.0 per cent when compared with July 2011. Over the same period the value of sales increased by 3.4 per cent. Average prices are estimated to have decreased by 0.5 per cent in the year to July 2012.
In July 2012 the estimated average weekly sales were £2.8 billion; of this, 7.4 per cent of sales (£205.7 million) were made via the Internet.
Non-specialised stores sales volumes in July 2012 increased by 9.6 per cent when compared with July 2011. Over the same period the value of sales increased by 8.2 per cent. Average prices are estimated to have decreased by 1.3 per cent in the year to July 2012.
In July 2012 the estimated average weekly sales were £0.5 billion; of this, 7.7 per cent of sales (£39.5 million) were made via the Internet.
Textile, clothing and footwear stores sales volumes in July 2012 decreased by 0.1 per cent when compared with July 2011. Over the same period the value of sales increased by 0.5 per cent. Average prices are estimated to have increased by 0.4 per cent in the year to July 2012.
In July 2012 the estimated average weekly sales were £0.8 billion; of this, 9.0 per cent of sales (£73.2 million) were made via the Internet.
Household goods stores sales volumes increased by 2.0 per cent in July 2012 when compared with July 2011. Over the same period the value of sales increased by 1.5 per cent. Average prices are estimated to have decreased by 0.2 per cent in the year to July 2012.
In July 2012 the estimated average weekly sales were £0.6 billion; of this, 5.5 per cent of sales (£31.5 million) were made via the Internet.
Other stores sales volumes increased by 6.1 per cent in July 2012 when compared with July 2011. This was the highest increase since January 2011 (11.2 per cent). Over the same period sales values increased by 4.8 per cent in July 2012 when compared with July 2011. This was the highest increase since January 2011 (11.6 per cent). Average prices are estimated to have fallen by 1.1 per cent in the year to July 2012.
In July 2012 the estimated average weekly sales were £0.9 billion; of this, 7.2 per cent of sales (£61.5 million) were made via the Internet.
Non-store retailing sales volumes increased by 15.2 per cent in July 2012 when compared with July 2011. Over the same period sales values increased by 13.9 per cent when compared with July 2011. Average prices are estimated to have decreased by 1.2 per cent in the year to July 2012.
In July 2012 the estimated average weekly sales were £0.4 billion; of this, 63.3 per cent of sales (£232.8 million) were made via the Internet.
Predominantly automotive fuel stores sales volumes decreased by 1.7 per cent in July 2012 when compared with July 2011. Over the same period sales values decreased by 2.5 per cent in July 2012 when compared with July 2011. Average prices are estimated to have decreased by 1.3 per cent in the year to July 2012.
In July 2012 the 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 2.3 per cent between July 2011 and July 2012.
|Number of employees||Weights (%)||Growth since July 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 July 2011 and July 2012. The table contains information only from businesses that reported in July 2011 and July 2012. 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+ 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
There are no planned improvements to retail sales estimates next month.
No changes were introduced this month.
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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. © Crown copyright 2012.
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 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. U se 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 July 2012 was 1 July 2012 to 28 July 2012, compared with 3 July 2011 to 30 July 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 Report (114 Kb Pdf) for the RSI is available.
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||0.9||-0.23||0.35|
|Latest month compared with previous month||0.3||-0.10||0.44|
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