1. Main points

  • Continuing a sustained period of year-on-year growth, the volume of retail sales in May 2015 are estimated to have increased by 4.6% compared with May 2014. This was the 26th consecutive month of year-on-year growth, the longest period of sustained growth since May 2008 when there were 31 periods of growth

  • The underlying pattern in the data, as suggested by the 3 month on 3 month movement in the quantity bought, continued to show growth for the 27th consecutive month, increasing by 0.6%. This is the longest period of sustained growth since consistent records began in June 1996

  • On the month, the quantity bought in the retail industry increased by 0.2% compared with April 2015. There was growth in predominantly food stores, other non-food stores, household goods stores and petrol stations

  • Average store prices (including petrol stations) fell by 2.7% in May 2015 compared with May 2014. This is the 11th consecutive month of year-on-year price falls. The largest contribution once again came from petrol stations which fell by 10.2%, the 21st consecutive month of year-on-year falling prices in this store type

  • In May 2015, the amount spent in the retail industry increased by 1.8% compared with May 2014 and by 0.2% compared with April 2015. Non-seasonally adjusted data show that the average weekly spend in the retail industry was £7.1 billion compared with £6.9 billion in April 2015 and £7.0 billion in May 2014

  • The value of sales made online in May 2015 decreased by 2.1% compared with April 2015 and accounted for 12.0% of all retail sales. Online sales increased by 7.4% compared with May 2014

  • Revisions in this release were caused by the incorporation of late data. The earliest revisions point for current price, non-seasonally adjusted data was May 2014. More information on revisions can be found in the background notes

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2. Additional information

This bulletin presents estimates of the quantity bought (volume) and amount spent (value) in the retail industry for the period 3 May 2015 to 30 May 2015. 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 and those with annual turnover of greater than £60 million who employ 10 to 99 people.

The quality of the estimate of retail sales

Retail sales estimates are produced from the monthly business survey – RSI. The timeliness of these retail sales estimates, which are published just 3 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. Results are revised for the previous 13 published periods. More information about the data content for this release can be found in the background notes.

Revisions are an inevitable consequence of the trade-off between timeliness and accuracy. The response rate in May 2015 was 60.2% of questionnaires, accounting for 93.4% of registered turnover in the retail industry. Therefore the estimate is subject to revisions as more data become available.

All estimates, by definition, are subject to statistical uncertainty and for the retail sales index we publish the standard error associated with the non-seasonally adjusted estimates of year-on-year and month-on-month growth in the quantity bought as a measure of accuracy. More information on these standard errors can be found in the background notes of this bulletin and in the quality tables (164.5 Kb Excel sheet) of this release.

It should be noted that we are continually working on methodological changes to improve the accuracy of the retail sales estimates; progress on these can be found on the ONS continuous improvement page on our website.

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

  • non-seasonally adjusted and seasonally adjusted volume and value indexes by industry

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

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3. Main figures

At a glance

In May 2015, the quantity bought in the retail industry (volume) increased by 4.6% compared with May 2014. The amount spent (value) increased by 1.8%. In May 2015, non-seasonally adjusted data show that the prices of goods sold in the retail industry (as measured by the implied price deflator) decreased by 2.7%. More information on how the implied price deflator is calculated can be found in section 3 of the background notes.

Amount spent in the retail industry

In the 4 week reporting period during May 2015, the amount spent in the retail industry was £28.3 billion (non-seasonally adjusted). This compares with £27.8 billion in the 4 week reporting period for April 2015 and £27.8 billion in the 4 week reporting period for May 2014.

This equates to an average weekly spend of £7.1 billion in May 2015, £6.9 billion in April 2015 and £7.0 billion in May 2014.

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4. Economic context

Figure 1 shows how the yearly growth in the 3 month average of retail sales volumes was affected by the downturn, and highlights the strong growth since 2013.

Three distinct periods emerge from Figure 1. In the years preceding the downturn, growth in retail sales volumes was strong. Between May 2006 and May 2008, the volume of sales increased by 6.3%, or at an average annual rate of 3.1%. Growth in Consumer Price Inflation (CPI), was consistently lower than in average weekly earnings over this period, meaning real earnings grew, which possibly increased the purchasing power of consumers.

However, between May 2008 and May 2013, the volume of retail sales remained broadly flat, fluctuating between periods of contraction and expansion, and as a result roughly the same volume of sales was recorded at the beginning and end of the period. This weakness is partly explained by the economic climate over this period. Growth in average weekly earnings was consistently lower than inflation, which implies that earnings fell in real terms. Real household disposable income, which includes the effect of taxes and benefits, was also broadly flat over this period. However, the value of retail sales continued to grow, increasing by 10.7% over the period, reflecting rising prices between these dates.

The third period shown in Figure 1 starts in 2013, when growth in volume terms began to increase notably, despite weak growth in disposable income and average weekly earnings continuing to grow at a slower rate than CPI. The volume of retail sales in May 2015 was 8.3% higher than it was in May 2013; corresponding to an average annual growth rate of 4.1%, substantially faster than in the years preceding the downturn. Possible explanations for the strong growth in sales despite weak earnings growth were discussed in the April 2015 retail sales release, which looked at the difference between CPI and retail store prices.

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5. Contributions to growth

The retail industry is divided into 4 retail sectors:

  • predominantly food stores (for example, supermarkets, specialist food stores and sales of alcoholic drinks and tobacco)

  • predominantly non-food stores (for example, non-specialised stores, such as department stores, textiles, clothing and footwear, household goods and other stores)

  • non-store retailing (for example, mail order, catalogues and market stalls)

  • stores selling automotive fuel (petrol stations)

In May 2015, for every pound spent in the retail industry:

  • 41 pence was spent in food stores

  • 42 pence in non-food stores

  • 7 pence in non-store retailing

  • 10 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 May 2015 and May 2014.

In May 2015, all 4 main retail sectors saw an increase in the quantity bought (volume). The largest contribution came from the non-food stores sector.

In May 2015, 3 out of the 4 main sectors (food stores, non-store retailing and non-food stores) contributed to the increase in amount spent (value). The largest contribution came from the non-food stores sector.

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6. Sector summary

Main points:

  • in May 2015, all store types showed increases in the quantity bought compared with May 2014

  • all store types except petrol stations showed increases in the amount spent year-on-year

  • in May 2015, all store types saw falls in average store price compared with May 2014

More information on how average store prices are calculated can be found in the quick guide to retail sales (117.1 Kb Pdf) or in the background notes.

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7. Focus on predominantly food stores

In predominantly food stores in May 2015 compared with May 2014:

  • the quantity bought increased by 2.6%

  • the amount spent increased by 1.0%

  • average store price decreased by 1.6%

Compared with April 2015:

  • the quantity bought increased by 0.6%

  • the amount spent increased by 0.9%

  • average store price increased by 0.1%

Figure 4 shows the longer-term picture for the quantity bought, amount spent and average price in food stores. The amount spent has increased at a strong, but consistent rate from 2005 to early 2013 and after this time has stayed relatively flat. As the amount spent is a combination of the quantity bought and price of goods, if average store prices fall then unless there is an increase in the quantity bought, the amount spent will fall.

In recent months, the quantity bought in the food sector has increased and while average store prices have fallen, the amount spent has stayed at this flat level due to this increase in the quantity bought. While the month-on-month and year-on-year increase in the quantity bought is not unusual, the level is now at it’s highest since April 2011, however, this was distorted by the Royal Wedding and extra bank holiday.

Feedback from supermarkets, which make up a large proportion of food retailers, suggests that increased sales of alcohol due to in-store promotions boosted sales in May 2015. Within the food sector, off licences and tobacconists saw a year-on-year increase of 27.7%, the highest on record.

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8. 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

  • 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.

Main points:

  • average weekly spending online in May 2015 was £791.3 million; this was an increase of 7.4% compared with May 2014 and this was the lowest year-on-year increase since November 2012

  • the amount spent online accounted for 12.0% of all retail spending, excluding automotive fuel, compared with 11.5% in May 2014

  • the increase of 0.8% in textile, clothing and footwear stores was the lowest year-on-year increase since records began in January 2008

Table 3 shows the year-on-year growth rates for total internet sales by sector and the proportion of sales made online in each retail sector.

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9. 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 10 to 49 employees saw the largest growth in the amount spent, comparing May 2015 with May 2014. Businesses with 100 and over employees experienced growth of 2.6%.

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 May 2014 and May 2015. The table contains information only from businesses that reported in May 2014 and May 2015. 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 and over employees and 10 to 99 employees with annual turnover of more than £60 million. “Small and medium” businesses are defined as 0 to 99 employees.

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10. International data

The only international estimate of retail sales available for May 2015 was published by the US Census Bureau on 11 June 2015. In its advanced retail sales estimates for May 2015, the amount spent in the US retail industry, including motor vehicles and parts and food services, increased by 1.2% from the previous month and by 2.7% compared with May 2014. Total sales for the 3 months to May 2015 were up 2.1% from the same period a year ago.

The latest estimates from Eurostat for April 2015 of the volume of retail trade across the European Union increased by 0.7% in the euro area (EA19) and by 0.6% in the EU28 when compared with March 2015. Compared with April 2014, the retail sales index increased by 2.2% in the EA19 and by 2.6% 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.

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11 .Background notes

  1. Future improvements

    We are currently updating the RSI workplan for the next 12 months, if you have any feedback on improvements we could make to RSI please e-mail comments to retail.sales.enquiries@ons.gsi.gov.uk.

    We will be implementing new commodity weights in the retail sales data for June 2015, published on 23 July 2015.

  2. Relevant links

    A subset of the retail sales dataset will be published on our Data Explorer page today. Please note the link will not work until the data are published.

    Overview of internet retail sales in 2014

    Has 2014 been a good year for retailers

    Revisions to the Retail Sales Index 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

    Comparability of RSI Sales and External Indicators

    RSI Workplan (87.3 Kb Pdf)

    Why is the retail sales revisions policy different from the National Accounts revisions policy?

    RSI Quality and Methodology Information paper

    BRC Sales Monitor May 2015

    National Accounts Workplan

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

    Impact of quarterly employment question on the monthly survey response

    Investigating the effect of quarterly collection of employee jobs data on the estimated standard error of change for total turnover on the Monthly Business Survey

    Government Statistical Service (GSS) uncertainty guidance

  3. Understanding the data

    1. Quick Guide to the Retail Sales Index

    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% 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), consistent with the international NACE Rev 2 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 2 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

    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.

    In a recent survey users found the Retail Sales Index statistics important to their work. It was found crucial for financial modelling of sectors and recognised as a timely indicator for the economy. It has been used as a comparative tool with BRC and other market sources to boost context. Practically, it has been utilised as a comparative tool for business performance and the ability to access internet retail sales has been particularly beneficial to some. On a non-industry level, the RSI was perceived as important for informing political opinions or simply for curiosity by individuals who were not necessarily utilising it as a reference for work purposes.

    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.

  4. Methods

    • Information on retail sales methodology is available on our website

    1. Composition of the data

    Estimates in RSI are based on financial data collected through the monthly Retail Sales Inquiry. Response rates at the time of publication are included for the current month, and the 3 months prior. The response rates for those historical periods are updated to reflect the current level of response, incorporating data from late returns. 2 response rates are included, with 1 percentage for the amount of turnover returned, and the other percentage for the amount of questionnaire forms. Historical response rates are available in the quality information reference table.

    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 January 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-13-ARIMA-SEATS. 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 3 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 January and the fall in February)
    • 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 January each year and a fall in the following February, but these are not evident in the seasonally adjusted index. This peak in January 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 May 2015 was 3 May 2015 to 30 May 2015, compared with 4 May 2014 to 31 May 2014 in the previous year. Table 6 shows the differences between the calendar and seasonally adjusted estimates.

  5. Quality

    1. Basic quality information

    • The standard reporting periods can change over time due to the movement of the calendar. Every 5 or 6 years the standard reporting periods are brought back into line by adding an extra week. For example, January is typically a 4 week standard period but January 1986, 1991, 1996, 2002, 2008 and 2014 were all 5 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 3 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 40.9%, predominantly non-food stores 42.0%, non-store retailing 7.0% and automotive fuel 10.1%

    2. Standard error

    • Standard errors 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 of year-on-year movement for 'All Retailing' is 1.0%. It has remained at 1.0% since March 2015. It was lower at 0.9% from June 2014 onwards with the only other decrease in May 2014, at 0.8%. Before this period, the year-on-year movements mostly remained at 0.9% with the only other fluctuations occurring in August 2013 and September 2013, where there was a standard error of 1.0%
    • Table 7 shows the year-on-year movement for the non-seasonally adjusted chained volume measure alongside the standard error, across the published sector breakdowns for May 2014 and May 2015. The differences between May 2014 and May 2015 highlight that the standard error has increased the most in ‘Non-store retailing’ and ‘Automotive fuel’. The greatest decreases are for ‘Household goods stores’ and ‘Textiles, clothing and footwear stores’

    3. Summary quality report

    The RSI Quality and Methodology Information paper 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. Table 8 shows summary information on the size and direction of the revisions made to the volume data covering a 5 year period. Note that changes in definition and classification mean that the revision analysis is not conceptually the same over time.

  6. Accessing data

    The complete run of data in the tables of this statistical bulletin is available to view and download in electronic format using our 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 at www.ons.gov.uk/ons/datasets-and-tables/index.html

    Alternatively, for low-cost tailored data call 0845 601 3034 or email info@ons.gsi.gov.uk

  7. 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

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Contact details for this Statistical bulletin

Kate Davies
Telephone: +44 (0)1633 455602