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Statistical bulletin: Retail Sales, September 2014 This product is designated as National Statistics

Released: 23 October 2014 Download PDF

Key Points

  • The quantity bought in the retail industry in September 2014 was estimated to have decreased by 0.3% compared with August 2014. However, it increased by 2.7% compared with September 2013 making this the 18th consecutive month of year-on-year growth. This is the longest period of sustained year-on-year growth since May 2008, when there were 31 periods of growth.
  • The underlying pattern continues to show growth with the rolling three-month on three-month growth rate increasing by 0.3%. However, this was the slowest growth seen in this measure throughout 2014.
  • Textile, clothing and footwear sales provided the greatest source of down wards pressure, decreasing by 7.8% compared with August 2014, and by 4.1% compared with September 2013. Feedback from retailers suggested the fall was a result of unseasonably warm weather meaning consumers have delayed purchases of autumn and winter clothing.
  • In September 2014, the amount spent in the retail industry decreased by 0.6% compared with August 2014. However, it increased by 1.3% compared with September 2013. Non-seasonally adjusted data show that the average weekly spend in the retail industry in September 2014 was £6.9 billion compared with £6.8 billion in September 2013 and £6.9 billion in August 2014.
  • Average store prices (including petrol stations) fell by 1.4% in September 2014 compared with September 2013. This was the largest fall since July 2009. The largest contribution to this fall came from petrol stations, down by 5.4%. Prices at food stores fell by 0.3%, the largest fall since December 2004 when it also fell by 0.3%.
  • The proportion of online sales were unchanged in September 2014 compared with August 2014 at 11.4%. Online sales increased by 10.1% compared with September 2013.
  • Revisions to this period were primarily caused by re-referencing the indices to 2011 =100 to align with the National Accounts estimates. There were also revisions where late data was incorporated. More information on revisions can be found in the background notes.

Additional Information

This bulletin presents estimates of the quantity bought (volume) and amount spent (value) in the retail industry for the period 31 August 2014 to 4 October 2014. Unless otherwise stated, the estimates in this release are seasonally adjusted.

Users are reminded that the figures contained in this release are estimates based on a monthly survey of 5,000 retailers, including all large retailers employing 100 people or more. The timeliness of these retail sales estimates, which are published just three weeks after the end of each month, makes them an important early economic indicator. The industry as a whole is used as an indicator of how the wider economy is performing, and the strength of consumer spending.

For different ways to access the data see the reference tables section on the ONS website. These include:

  • Non-seasonally adjusted and seasonally adjusted volume and value indexes by industry, and

  • Year-on-year and month-on-month growth rates by industry.

Key Figures

Table 1: All Retailing, September 2014 (seasonally adjusted percentage change)

      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)  1.3 1.9 -0.6 0.1
Quantity bought (Volume) 2.7 2.9 -0.3 0.3
Value excluding automotive fuel 2.2 2.9 -0.6 0.2
Volume excluding automotive fuel 3.1 3.5 -0.3 0.4

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At a Glance

In September 2014, the quantity bought in the retail industry (volume) increased by 2.7% compared with September 2013. The amount spent (value) increased by 1.3%. In September 2014, non-seasonally adjusted data show that the prices of goods sold in the retail industry (as measured by the implied price deflator) decreased by 1.4%. More information on how the implied price deflator is calculated can be found in section 3 of the background notes.

Economic Context

To enable a comparison of change, Figure 1 shows the quantity of goods bought in the retail industry (all retailing sales volumes) and the amount spent (all retailing sales values), as indices referenced to 2011.

Figure 1: All retailing seasonally adjusted sales volume and values

Figure 1: All retailing seasonally adjusted sales volume and values
Source: Monthly Business Survey - Retail Sales Inquiry - Office for National Statistics

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Prior to the 2008/09 downturn, both the quantity and the value of retail sales grew steadily. Between January 2005 and January 2008, retail sales were supported by growing real household incomes. As average weekly earnings (AWE) increased more rapidly than the Consumer Prices Index (CPI) households consumed more retail goods, the quantity of retail sales (including fuel) grew by 7.3% over this period. At the same time the value of retail sales increased by 11.5%, reflecting price increases over this period.

Between January 2008 and January 2013 (the area shaded in grey), the volume of retail sales was broadly flat while the value of retail sales continued to grow, increasing by 12.1%. The difference reflects the extent to which prices grew following the onset of the economic downturn – the CPI increased by 17.9% over this period – as well as the squeeze felt on household real earnings.

Further analysis of recent trends in real wages and potential explanations can be found in ‘An Examination of Falling Real Wages, 2010 to 2013’, published 31 January 2014.

However, since the start of 2013, growth in volume terms increased noticeably. The volume of retail sales is now 6.2% higher than in January 2013.  This is an average of 0.3% per month.

At the same time, the volume of retail sales continued to outstrip increases in value terms, with growth increasing to 2.7% and 1.3% in the year to September 2014 respectively. The CPI growth rate also continued its downward trend and stood at 1.2% in September 2014. This was the slowest rate since September 2009, highlighting the weakening of overall price pressure in the UK economy.

Contributions to Growth

The retail industry is divided into four retail sectors:

  • Predominantly food stores (e.g. supermarkets, specialist food stores and sales of alcoholic drinks and tobacco),

  • Predominantly non-food stores (e.g. non-specialised stores, such as department stores, textiles, clothing and footwear, household goods and other stores),

  • Non-store retailing (e.g. mail order, catalogues and market stalls), and

  • Stores selling automotive fuel (petrol stations).

In September 2014, for every pound spent in the retail industry:

  • 42 pence was spent in food stores,

  • 41 pence in non-food stores,

  • 6 pence in non-store retailing, and

  • 11 pence in stores selling automotive fuel.

Using these as weights, along with the year-on-year growth rates, we can calculate how each sector contributed to the total year-on-year growth in the quantity bought.

Figures 2 and 3 show the contribution of each sector to the quantity bought (volume) and amount spent (value) in the retail industry between September 2013 and September 2014.

Figure 2: Contributions to year-on-year volume growth from the four main retail sectors (September 2014 compared with September 2013)

Figure 2: Contributions to year-on-year volume growth from the four main retail sectors (September 2014 compared with September 2013)
Source: Monthly Business Survey - Retail Sales Inquiry - Office for National Statistics

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In September 2014, three out of the four main retail sectors (non-store retailing, food stores and non-food stores) saw an increase in the quantity bought (volume). The largest contribution came from the non-food stores sector.

Figure 3: Contributions to year-on-year value growth fom the four main retail sectors (September 2014 compared with September 2013)

Figure 3: Contributions to year-on-year value growth fom the four main retail sectors (September 2014 compared with September 2013)
Source: Monthly Business Survey - Retail Sales Inquiry - Office for National Statistics

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In September 2014, three out of the four main sectors (non-store retailing, food stores and non-food stores) contributed to the increase in amount spent (value). The largest contributions came from non-food stores and non-store retailing sectors.

Sector Summary

Key Points:

  • In September 2014, all store types except textile, clothing and footwear stores and petrol stations showed increases in the quantity bought and amount spent year-on-year.

  • The quantity bought in textile, clothing and footwear stores fell by 4.1%, the largest year-on-year fall since April 2012.

  • All store types, except textile, clothing and footwear stores (which showed no change) saw falls in average store price in September 2014 compared with September 2013.  The largest contribution came from petrol stations.

  • More information on the performance of supermarkets can be found in the ONS short story UK supermakets spending stalls.

Table 2: Sector Summary, September 2014

Percentage change over 12 months
  Quantity bought (volume)  Amount spent (value)  Average store price  Average weekly sales (£ billion)
Predominantly food stores¹ 0.8 0.5 -0.3 2.8
Predominantly non-food stores² 3.2 2.0 -1.2 2.9
Non-specialised stores³ 8.1 6.6 -1.5 0.6
Textile, clothing and footwear stores -4.1 -4.0 0.0 0.9
Household goods stores 6.5 5.4 -1.0 0.6
Other stores 4.9 2.8 -2.0 0.9
Non-store retailing 16.5 14.8 -1.4 0.4
Fuel stores -1.0 -6.4 -5.4 0.7
Total 2.7 1.3 -1.4 6.9

Table notes:

  1. Supermarkets, specialist food stores and sales of alcoholic drinks and tobacco.
  2. Non-specialised stores, textile, clothing and footwear, household goods and other stores.
  3. Department stores.

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More information on how average store prices are calculated can be found in the quick guide to retail sales or in the background notes.

Analysis of textile, clothing and footwear stores

Textiles, clothing and footwear stores showed falls in both the quantity bought (4.1%) and amount spent (4.0%) between September 2013 and September 2014. These were the largest year-on-year falls since April 2012, when there were falls of 6.4% and 4.5% respectively. As shown in figure 4, the April 2012 year-on-year growth rates were somewhat affected by the high level in April 2011 where both the amount spent and quantity bought rose due to better than expected weather and an extra bank holiday because of the royal wedding.

Figure 4: Textile, clothing and footwear stores seasonally adjusted sales volumes, values and store price inflation

Figure 4: Textile, clothing and footwear stores seasonally adjusted sales volumes, values and store price inflation
Source: Monthly Business Survey - Retail Sales Inquiry - Office for National Statistics

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Across the three store types that make up this sector there were mixed results. Table 3 shows:

  • the different store types,

  • their respective weights in retail sales,

  • year-on-year seasonally adjusted growth rates, and

  • store price inflation (implied deflator, non-seasonally adjusted).

Table 3: Summary of the textile, clothing and footwear retail industry

Year-on-year growth rate
Store type Weight in RSI Volume (%) Value (%) Store price inflation  (implied price deflator)
Textile 0.2 22.3 20.7 -1.3
Clothing 10.7 -3.7 -3.7 0.1
Footwear 1.3 -10.3 -9.9 0.3
Total 12.2 -4.1 -4.0 0.0

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It is clear that clothing is the dominating store type in this sector. Any movements in this sector will therefore be strongly influenced by clothing stores.

Clothing

The longer term time series for clothing is shown in Figure 5.

Figure 5: Clothing stores seasonally adjusted sales volumes, values and store price inflation

Figure 5: Clothing stores seasonally adjusted sales volumes, values and store price inflation
Source: Monthly Business Survey - Retail Sales Inquiry - Office for National Statistics

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Throughout the period shown, the amount spent in the clothing sector continued to rise. However, the quantity bought shows a different pattern. In the early part of the series the quantity bought rose steadily between 2010 and 2012. It became almost constant at a level around 100 index points with the exception of December 2010 and April 2011. From early 2013, the quantity bought has started to rise with stronger growth in more recent months than seen previously.

In September 2014, both the amount spent and quantity bought fell by 3.7%. This is the largest year-on-year fall in both series since April 2011. At first glance, it seems that the fall has been caused by a rise in the rate of store price inflation in clothing stores. However, this rise in price was simply caused by the completion of end of season sales. While the price change may have had some impact, feedback from retailers suggests that the reason behind the fall in the amount spent and quantity bought was the unseasonably warm weather in September.  This meant consumers delayed buying autumn and winter clothing.

International Data

The only international estimate of retail sales available for September 2014 was published by the US Census Bureau on 15 September. In its advanced retail sales estimates for September 2014, the amount spent in the US retail industry, including motor vehicles and parts and food services increased by 4.3% compared with September 2013 and decreased by 0.3% compared with August 2014. Total sales for the three months to September 2014 were up 4.5% from the same period a year ago.

The latest estimates from Eurostat for August 2014 of the volume of retail trade across Europe showed an increase of 1.2% in both the euro area (EA18) and by 1.4% in the EU28 when compared with July 2014. Compared with July 2013, the retail sales index increased by 1.9% in the EA18 and by 2.5% in the EU28. It should be noted that an accurate comparison cannot be made as Eurostat data are calculated on a 2010 = 100 basis, while GB data are now calculated on a 2011 = 100 basis.

Distribution Analysis

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). It shows that businesses with 40-99 employees saw the largest growth in the amount spent comparing September 2014 with September 2013. Businesses with 10-39 employees experienced growth of 1.6%.

Table 4: Changes in reported retail sales values between September 2013 and September 2014 standard reporting periods (by size of business)

Number of employees Weights (%) Growth since September 2013 (%)
100+ 78.7 1.1
40-99 2.5 17.5
10-39 6.5 1.6
0-9 12.3 0.5
 

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More information on the performance of the retail industry by store type and size can be found in the reference table, Business Analysis (25.5 Kb Excel sheet) . This shows the extent to which individual businesses reported actual changes in their sales between September 2013 and September 2014. The table contains information only from businesses that reported in September 2013 and September 2014. Cells with values less than 10 are suppressed for some classification categories; this is denoted by c. Note that ‘large’ businesses are defined as those with 100+ employees and 10–99 employees with annual turnover of more than £60 million. ‘Small and medium’ businesses is defined as 0–99 employees.

Amount Spent in the Retail Industry

In the September 2014 five-week reporting period, the amount spent in the retail industry was £34.3 billion (non-seasonally adjusted). This compares with £27.4 billion in the four-week reporting period for August 2014 and £33.9 billion in the five-week reporting period for September 2013.

This equates to an average weekly spend of £6.9 billion in September 2014, £6.9 billion in August 2014 and £6.8 billion in September 2013.

Internet Sales in Detail

Seasonally adjusted Internet sales data are provided within this release. These seasonally adjusted estimates are published in the RSI internet tables and include:

  • a seasonally adjusted value index, and

  • year-on-year and month-on-month growth rates.

Internet sales are estimates of how much was spent online through retailers across all store types in Great Britain. The reference year is 2011=100.

Key Points:

  • Average weekly spending online in September 2014 was £731.8 million. This was an increase of 10.1% compared with September 2013.

  • The amount spent online accounted for 11.4% of all retail spending excluding automotive fuel, compared with 10.6% in September 2013.

  • The online spend in department stores increased by 7.0% compared with September 2013. This is the lowest year-on-year increase since November 2010 (6.3%).

Table 5 shows the year-on-year growth rates for total Internet sales by sector and the proportion of sales made online in each retail sector.

Table 5: Summary of Internet Statistics for September 2014 (seasonally adjusted)

Category Value Seasonally Adjusted Year-on-year growth (%)  Value Seasonally Adjusted Proportion of total sales made online (%)
All retailing 10.1 11.4
All food 13.4 3.9
All non-food 4.5 8.9
  Department stores 7.0 10.1
  Textile, clothing & footwear stores 10.4 12.4
  Household goods stores 10.3 5.7
  Other stores -7.9 6.9
Non-store retailing 13.5 68.1

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Background notes

  1. Future Improvements

    ONS will be implementing an updated version of the seasonal adjustment software called X-13-ARIMA-SEATS. The new version is in line with international best practice and is a change from the currently used version X-12-ARIMA. In practice, this will result in improved quality of outputs for seasonally adjusted estimates. Published estimates are still subject to the relevant revision policies, so users may not see revisions to historical estimates. Estimates for October 2014 are published on 20 November 2014 and will be processed using this updated software.

  2. What’s New

    Estimates in this release have incorporated the rebasing and re-referencing of the indices to 2011 = 100 to align with the National Accounts outputs.

    ONS has published an article on supermarket sales today.

  3. Relevant Links

    Revisions to the Retail Sales Index (100 Kb Pdf) details why revisions to the non-seasonally adjusted and seasonally adjusted data can occur. Revisions triangles can be found under section 5 Quality in the background notes.

    International Measures of Retail Sales

    Disclosure control policy (337 Kb Word document)

    Comparability of RSI Sales and External Indicators (95.5 Kb Pdf)

    RSI Workplan (135.9 Kb Pdf)

    Why is the retail sales revisions policy different from the National Accounts revisions policy? (53.9 Kb Pdf)

    RSI Quality and Methodology Information paper (245.6 Kb Pdf)

    BRC Sales Monitor September 2014 
     
    National Accounts Workplan (410 Kb Powerpoint presentation)

    14 ways ONS statistics help you understand the economy - A closer look at the circular flow of income

  4. Understanding the data

    1. Quick Guide to the Retail Sales Index (117.1 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 industry in terms of turnover.

    • The RSI covers sales only from businesses classified as retailers according to the Standard Industrial Classification 2007 (SIC 2007), an internationally consistent classification of industries. The retail industry 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 industry 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 cafes. 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 Internet sales. The total turnover will include Internet sales. The separation of the Internet sales figure allows an estimate relating to Internet sales to be calculated.

    3. Definitions and explanations 

    • The value or current price series records the growth of the value of sales ‘through the till’ before any adjustment for the effects of price changes.

    • The volume or constant price series are created 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 components 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 dividing the non-seasonally adjusted value and volume data to leave a price relative. In general, this implied price deflator should be quite close to the retail component of the CPI. More information on the implied price deflator can be found in the Quick Guide to Retail Sales (117.1 Kb Pdf) .

    4. Use of the data

    The value and volume measures of retail sales estimates are widely used in private and public sector organisations, both domestically and internationally. For example, private sector institutions such as investment banks, the retail industry itself and retail groups use the data to inform decisions on the current economic performance of the retail industry. These organisations are most interested in a long-term view of the retail sector, taken from the year-on-year growth rates. Public sector institutions use the data to help inform decision and policy making.  They tend to be most interested in a snapshot view of the retail industry, which is taken from the month-on-month growth rates.

    The Retail Sales Index feeds into estimates of gross domestic product (GDP) in two ways. Firstly it feeds into the services industries when GDP is measured from the output approach. Secondly it is a data source used to measure household final consumption expenditure which feeds into GDP estimates when measured from the expenditure approach.

    The data feed into the first (or preliminary) estimate of GDP, the second estimate of GDP and the third estimate which is published in the Quarterly National Accounts.

  5. Methods

    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.

    Table 6: Overall Response Rates

    Overall response rates (%)
    Year Period Turnover Questionnaire
    2014 September 93.4 59.6
    August 98.6 75.8
    July 98.6 79.2
      June 98.8 78.6

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    2. Seasonal adjustment

    Seasonally adjusted estimates are derived by estimating and removing calendar effects (for example, Easter moving between March and May) 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 estimate the amount of money taken through the tills of retailers; these are non-seasonally adjusted data. These data consist 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 is the peak in December and the fall in January)

    • irregular or ‘noise’, for example deeper falls within the non-seasonally adjusted series due to bad 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.  It leaves a seasonally adjusted time series made up of the trend and irregular components.

    In the non-seasonally adjusted RSI 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.  This means 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 come from the differences in reporting periods. The reporting period for August 2014 was 31 August 2014 to 4 October 2014, compared with 25 August 2013 to 28 September 2013 in the previous year. Table 7 shows the differences between the calendar and seasonally adjusted estimates.

    Table 7: Retail Sales, Calendar Effects

    Year-on-year percentage change
      Value Volume
    Calendar adjusted 1.6 2.7
    Seasonally adjusted 1.3 2.7

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  6. Quality

    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, 2008 and 2014 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 users should focus on the seasonally adjusted estimates as these have the systematic calendar-related component removed. Due to the volatility of the monthly data, growth rates should be 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 in the all retailing series. Based on SIC 2007 data, total retail sales consists of: predominantly food stores 41.5%, predominantly non-food stores 41.3%, non-store retailing 5.7% and automotive fuel 11.5%.

    2. Standard errors

    Standard errors of non-seasonally adjusted chained volume index movements have been developed for RSI.  These determine the spread of possible movements and are a means of assessing the accuracy of the non-seasonally adjusted month-on-month and year-on-year estimates of all retail sales volumes. The lower the standard error, the more confident we can be that the estimate is close to the true value for the retail population.

    • The standard error for year-on-year growth in all retail sales (non-seasonally adjusted) volumes is 0.9%. This means that the year-on-year growth rate for all retail sales volumes (non-seasonally adjusted) falls within the range 2.7 ± 1.8 percentage points, with a probability of 95%.

    • The standard error for month-on-month growth in all retail sales (non-seasonally adjusted) volumes is 0.5%. This means that the month-on-month growth rate for all retail sales volumes (non-seasonally adjusted) falls within the range -0.1 ± 1.0 percentage points, with a probability of 95%.

    The papers ‘ Measuring the accuracy of the Retail Sales Index (1.04 Mb Pdf) ’, and ‘ Updated accuracy measures for the Retail Sales Index (29.6 Kb Pdf) ’ report on the calculation of standard errors for month-on-month and year-on-year growth rates in the RSI.  They also provide an overview of standard errors and how they can be interpreted.

    3. Summary quality report

    The RSI Quality and Methodology Information paper (245.6 Kb Pdf) describes in detail the intended uses of the statistics in this bulletin, their general quality and the methods used to produce them.

    4. Revisions 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 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.

    Table 8: All Retailing, Volume Seasonally Adjusted, Revisions Triangles Summary Statistics, September 2014

    Volume seasonally adjusted

    Revisions between first publication and estimates twelve months later (percentage points)
      Growth in latest period (%) 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 0.3 -0.27 0.36
    Latest month compared with previous month -0.3 -0.13 0.40

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    A spreadsheet giving these estimates and the calculations behind the averages in the table is available in the data section of this publication.

  7. Pre-release Access

    A list is available of the organisations given pre-publication access to the contents of this bulletin.

  8. Accessing data

    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 info@ons.gsi.gov.uk

  9. Next publication: Thursday 20 November 2014

    Issued by: Office for National Statistics, Government Buildings, Cardiff Road, Newport NP10 8XG

    Media contact:

    Tel Media Relations Office 0845 604 1858

    Emergency on-call 07867 906553

    Email   media.relations@ons.gsi.gov.uk

    Statistical contact:

    Tel: Kate Davies +44 (0)1633 455602

    Email  retail.sales.enquiries@ons.gsi.gov.uk

    Contact us:

    Tel: 0845 601 3034

    Email info@ons.gsi.gov.uk

    Website www.ons.gov.uk

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  10. 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: media.relations@ons.gsi.gov.uk

Statistical contacts

Name Phone Department Email
Kate Davies +44 (0)1633 455602 ONS retail.sales.enquiries@ons.gsi.gov.uk
Get all the tables for this publication in the data section of this publication .
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