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For any question on data and metadata, please contact: Eurostat user support |
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1.1. Contact organisation | Office for National Statistics (ONS) |
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1.2. Contact organisation unit | Retail Sales |
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1.5. Contact mail address | Government Buildings |
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2.1. Metadata last certified | 27/11/2018 | ||
2.2. Metadata last posted | 27/11/2018 | ||
2.3. Metadata last update | 27/11/2018 |
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3.1. Data description | ||||||
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3.2. Classification system | ||||||
NACE Rev. 2. |
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3.3. Coverage - sector | ||||||
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3.4. Statistical concepts and definitions | ||||||
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3.5. Statistical unit | ||||||
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3.6. Statistical population | ||||||
The survey measures value and volume of retail sales in Great Britain. |
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3.7. Reference area | ||||||
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3.8. Coverage - Time | ||||||
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3.9. Base period | ||||||
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Indices (2016=100). Growth rates in % |
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6.1. Institutional Mandate - legal acts and other agreements | ||||||
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6.2. Institutional Mandate - data sharing | ||||||
Eurostat Scottish Government receive quarterly regional data. |
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7.1. Confidentiality - policy | |||
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7.2. Confidentiality - data treatment | |||
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8.1. Release calendar | ||||||
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8.2. Release calendar access | ||||||
Open to all on Publication Hub website- www.gov.uk/government/statistics/announcements. |
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8.3. Release policy - user access | ||||||
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Monthly |
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10.1. Dissemination format - News release | ||||
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10.2. Dissemination format - Publications | ||||
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10.3. Dissemination format - online database | ||||
The retail sales summary outlines the key messages within each month’s data. This includes the key drivers for movements within particular sectors for both value and volume indices. The Retail Sales Statistical Bulletin presents the key messages within the data, analysis of raw data including analysis by size of business, a detailed sector summary focusing on the four main aggregates: predominantly food, predominantly non-food, non-store retailing and automotive fuel. |
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10.4. Dissemination format - microdata access | ||||
Virtual microdata laboratory- https://www.ons.gov.uk/aboutus/whatwedo/paidservices/virtualmicrodatalaboratoryvml |
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10.5. Dissemination format - other | ||||
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10.6. Documentation on methodology | ||||
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10.7. Quality management - documentation | ||||
https://www.ons.gov.uk/businessindustryandtrade/retailindustry/methodologies/retailsalesindexrsiqmi For information regarding conditions of access to data, please refer to the links below: |
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11.1. Quality assurance | |||
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11.2. Quality management - assessment | |||
Guidelines for measuring statistical quality: https://www.ons.gov.uk/businessindustryandtrade/retailindustry/methodologies/retailsalesindexrsiqmi
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12.1. Relevance - User Needs | |||
To meet our user needs, the Retail Sales branch is part of the Short-Term Output Indicators Stakeholder Group (STOISG). Key stakeholders and the Office for National Statistics (ONS) meet every three months to discuss published data, planned and ongoing developments and statistical communication. |
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12.2. Relevance - User Satisfaction | |||
12.3. Completeness | |||
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13.1. Accuracy - overall | ||||
A report on RSI standard errors and response rates titled Improving quality information for the Retail Sales Index was published in January 2015. The report shows that the median year-on-year standard error is estimated at 0.9% and the month-on-month standard error is estimated at 0.5%. The RSI is first published using a 61% response rate, this equates with approximately 88% of sampled turnover. The sample of 5,000 from a population of nearly 200,000 may seem small but together these 5,000 retailers cover approximately 95% of all retailing turnover captured on the IDBR. |
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13.2. Sampling error | ||||
Retail Sales quality tables are produced each month and include confidence intervals, response rates and standard errors in varying forms-https://www.ons.gov.uk/businessindustryandtrade/retailindustry/datasets/retailsalesqualitytables Sampling error occurs because a sample, rather than the entire population, is surveyed. It is the difference between the true value for the population and the estimated value. One way of measuring this difference is through standard errors. |
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13.3. Non-sampling error | ||||
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14.1. Timeliness | ||||
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14.2. Punctuality | ||||
For more details on related releases, the release calendar is available online from the GOV.UK website and provides 12 months’ advance notice of release dates. If there are any changes to the pre-announced release schedule, public attention will be drawn to the change and the reasons for the change will be explained fully at the same time, as set out in the Code of Practice for Official Statistics. |
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15.1. Comparability - geographical | ||||
ONS follow the A (ideal) method for the compilation of these statistics to as described by the Short Term Statistics Regulation - no other European country follows this method. |
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15.2. Comparability - over time | ||||
Comparable time series are available going back to 1988 for the following headline aggregates and their sub-sector series: • All retailing excluding automotive fuel; • Predominantly food stores; • Predominantly non-food stores; and • Non-store retailing. For the following aggregates, comparable time series are available going back to 1996: • All retailing including automotive fuel; and • Automotive fuel. |
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15.3. Coherence - cross domain | ||||
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15.4. Coherence - internal | ||||
Not available. |
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The cost of producing these retail variable is £531,000. The compliance cost or burden is £230,000 |
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17.1. Data revision - policy | |||
Retail Sales non-seasonally adjusted data is revised as needed. This typically occurs due to late data returns, updated respondent information, replacing adjustments with actual data, and reclassifications of respondents to the appropriate category either within or out of retail. Changes are not made to any non-seasonally adjusted data prior to 2001. Revisions to non-seasonally adjusted data will directly impact on the seasonally adjusted estimates. Revisions and sampling variations are a consequence of the trade-off between timeliness and accuracy. All estimates are subject to statistical error which refers to the uncertainty inherent in any process or calculation that uses sampling, estimation or modelling. Estimates for the most recent month are provisional and subject to revision because of: • late responses to the Monthly Business Survey - Retail Sales Index; • revisions to seasonal adjustment factors which are re-estimated every month and reviewed annually; • changes from the annual seasonal adjustment review; and • annual updating of the business register that forms the basis for the sample for the RSI (usually occurring in January) and • other methodological improvements. Policy regarding revisions to Retail sales are available in the monthly release on the website. https://www.ons.gov.uk/methodology/methodologytopicsandstatisticalconcepts/revisions |
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17.2. Data revision - practice | |||
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18.1. Source data | ||||||||||||
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18.2. Frequency of data collection | ||||||||||||
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18.3. Data collection | ||||||||||||
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18.4. Data validation | ||||||||||||
Intra-dataset checks Returned data are passed through a series of validation checks which includes an automatic selective editing procedure. The selective editing approach means that the editing process should be more efficient and effective since it will only edit potential errors that have a significant impact on final outputs. Selective editing is an internationally recognised method that uses a data based approach to assess the influence of business estimates on the aggregate outputs. Under selective editing key variables on the questionnaire are defined and scores derived for these. The scores compare the value provided on the questionnaire with expected values, where the expected values are generally estimated using past data or other available information related to the variable, for example, from administrative sources. The scores from ‘key’ variables are then combined to derive a score for every questionnaire. This derived, single score for the business’s return is then tested against a methodologically set threshold. If the score is higher than the defined threshold then the questionnaire will fail and be flagged for manual editing. Thresholds have been derived and set to ensure minimum bias is introduced from not editing values that may have been edited under the previous edit all returns system. Thus selective editing does result in an adverse impact on output quality. In order to ensure that all errors are captured, before questionnaires pass through selective editing they are subjected to automatic editing and then a number of user defined checks. For example, these will include checks to detect changes to reporting periods and implausible returns such as turnover being less than zero. This is queried by the editing & validation (E&V) team and can also be queried by the results & prosessing (RAP) team. The respondent may be contacted to verify whether the movement is genuine. This is recorded and retained on the database for future reference when analysing the index. In turn, data are analysed at a macro level to determine the contributing factors to the movement in the value index and its published categories. Together, this micro and macro approach to editing identifies outliers and anomalies within the returned data. |
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18.5. Data compilation | ||||||||||||
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18.6. Adjustment | ||||||||||||
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Not available. |
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