Turnover and volume of sales index

National Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Statistics Sweden


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
 



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1. Contact Top
1.1. Contact organisation

Statistics Sweden

1.2. Contact organisation unit

Unit for Innovation, Business sector production and Research

1.5. Contact mail address

Statistiska centralbyrån

Johan Nyström

Solna strandväg 86

SOLNA


2. Metadata update Top
2.1. Metadata last certified 15/06/2023
2.2. Metadata last posted 15/06/2023
2.3. Metadata last update 15/06/2023


3. Statistical presentation Top
3.1. Data description

Name of indicator/source: Retail trade turnover index (or Retail Sales Index) - In Swedish: Detaljhandelsindex. Other services turnover index.

Main purpose is to be a part of an indicator on private consumption.

3.2. Classification system

NACE Rev. 2.

3.3. Coverage - sector

Activities covered: NACE Rev. 2 Division G45, G46 and G47.

Size classes covered: The frame is constructed using a cutoff where units over the cutoff together include 90-95 % (depending on industry sector) of the yearly turnover.

3.4. Statistical concepts and definitions

Retail trade turnover is not defined according to the regulation. In the Swedish retail trade turnover is defined as Turnover incl VAT excl export. For G45 and G46 net turnover (excl VAT) is collected.

Planned changes in information collected: No planned changes.

Accounting conventions: The reference period is calendar month.

3.5. Statistical unit

Reporting unit: The reporting unit is the enterprise with some exceptions (where enterprise groups may report).

Observation unit (s): The observation unit is the enterprise with some exceptions (where enterprise groups may report).

3.6. Statistical population

The population: Retail trade NACE Rev.2 Division 47.

3.7. Reference area

Geographical area covered: All regions of Sweden are covered.

3.8. Coverage - Time

Date of first use as a source: Since 1948. Before 1963 Swedish Social Government was responsible for retail trade statistics.

3.9. Base period

Base (reference) year: 2015


4. Unit of measure Top

Data is gathered in absolute values which are then calculated into indices. Indices are presented on the webpage, absolute values are not. The final result is an index with reference year equal to 100.


5. Reference Period Top

The reference period is calendar month.


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

Legal basis: Official statistics in Sweden are governed by the Official Statistics Act of 2001 (SFS 2001:99) and Ordinance SFS 2001:100. The legal basis under which data is collected is specified in SFS 2015:4. 

Obligation on units to provide data: The units are obliged to provide data.

Planned changes in legal basis, obligation to respond and frame used: No planned changes.

6.2. Institutional Mandate - data sharing

Data is sent to Eurostat. 


7. Confidentiality Top
7.1. Confidentiality - policy

Dissemination of terms and conditions under which official statistics are produced, including confidentiality of individual responses:

The data that has been transmitted to Eurostat is not confidential on that level. Information is disseminated to different users such as National Accounts, Ministry of Finance, National institute of economic research, business and trade organisations, enterprises and scientists. Data is available in Sweden’s statistical databases and on the website. All of this is for free. Data on requests can cost depending on size and time of work with the data. Special arrangement for international users means that data and documentation can be in English.

Submitted information is protected according to Chapter 24 Section 8 of the Public Access to Information and Secrecy Act (2009:400). 

Statistics Sweden have policies in place in order to minimize the risk of disclosure and/or damage dealt to respondents in the survey.

The main rule is that groups with less than three enterprises are always treated as confidential. However that criteria may be weak in certain situations. Therefore Statistics Sweden have developed a program that estimates the probability of disclosure in each of the reporting groups. Based on the estimated probability of disclosure the potential damage of such an exposure is assessed by the statisticians involved in the production.

7.2. Confidentiality - data treatment

If data is under risk of disclosure, the first measure is cell suppression. If the risk of disclosure continues to recur in a certain cell, the second measure is aggregation of two or more similar cells.

Data are only published down to an activity level at which it is not confidential. Confidential data are transmitted to Eurostat but marked as "confidential".


8. Release policy Top
8.1. Release calendar

Release dates for the monthly statistical releases are determined one year in advance. The dates can be found on Statistics Sweden´s website, www.scb.se.

8.2. Release calendar access

Anyone can access the release calendar on Statistics Sweden´s website.

8.3. Release policy - user access

Simultaneous release to all interested parties: Data for Swedish retail trade statistics is released simultaneously to all interested parties.

No-one other than SCB have access to data before its released. Data is confidential until SCB has released the data.

Data is transmitted to Eurostat at the same time as it is published in Sweden each month. Data is in the format of sdmx and transmitted through Edamis.


9. Frequency of dissemination Top

Monthly


10. Accessibility and clarity Top
10.1. Dissemination format - News release

News release disseminated monthly on Statistics Sweden’s website. News releases contain gross, calendar or seasonally adjusted monthly and yearly growth rates.

Activity coverage in news release:

  • Total (47excl 47.3)
  • Mostly food, excl. state owned liquor stores (47.11+47.2 excl 47.25)
  • Mostly durables (47.19+47.4-47.9)
10.2. Dissemination format - Publications

Data is available in Statistics Sweden’s Statistical database and website.

Activity coverage in the Statistical database:

  • 45
  • 45.1
  • 45.1+45.3
  • 45.19
  • 45.2-45.4
  • 45.2
  • 45.3
  • 45.4
  • 46
  • 46.1
  • 46.2
  • 46.3
  • 46.4
  • 46.5
  • 46.6
  • 46.7
  • 46.9
  • 47ex47.25+47.3+47.73
  • 47exkl47.3
  • 47
  • 47.1
  • 47.11
  • 47.11+47.2
  • 47.11+.21-24+.26+.29
  • 47.19
  • 47.19+47.4-47.9
  • 47.2
  • 47.2exkl47.25
  • 47.3
  • 47.4
  • 47.4+47.54
  • 47.41-42+53+61-62+64
  • 47.43+52+54+59+63
  • 47.5
  • 47.51,.531-2,.593-4
  • 47.51+47.71-72
  • 47.52
  • 47.591-47.592
  • 47.6
  • 47.61-47.62
  • 47.641-47.642
  • 47.65
  • 47.7
  • 47.71
  • 47.71-47.72
  • 47.72
  • 47.73-47.75
  • 47.74+47.75
  • 47.761
  • 47.771
  • 47.772
  • 47.781
  • 47.789
  • 47.8; 47.99
10.3. Dissemination format - online database

Data is available in Statistics Sweden’s Statistical database and website.

Activity coverage in the Statistical database:

  • 45
  • 45.1
  • 45.1+45.3
  • 45.19
  • 45.2-45.4
  • 45.2
  • 45.3
  • 45.4
  • 46
  • 46.1
  • 46.2
  • 46.3
  • 46.4
  • 46.5
  • 46.6
  • 46.7
  • 46.9
  • 47ex47.25+47.3+47.73
  • 47exkl47.3
  • 47
  • 47.1
  • 47.11
  • 47.11+47.2
  • 47.11+.21-24+.26+.29
  • 47.19
  • 47.19+47.4-47.9
  • 47.2
  • 47.2exkl47.25
  • 47.3
  • 47.4
  • 47.4+47.54
  • 47.41-42+53+61-62+64
  • 47.43+52+54+59+63
  • 47.5
  • 47.51,.531-2,.593-4
  • 47.51+47.71-72
  • 47.52
  • 47.591-47.592
  • 47.6
  • 47.61-47.62
  • 47.641-47.642
  • 47.65
  • 47.7
  • 47.71
  • 47.71-47.72
  • 47.72
  • 47.73-47.75
  • 47.74+47.75
  • 47.761
  • 47.771
  • 47.772
  • 47.781
  • 47.789
  • 47.8; 47.99
10.4. Dissemination format - microdata access

Micro-data is not publicly released. Researchers may apply to Statistics Sweden to get access to de-identified micro-data for own processing purposes.

10.5. Dissemination format - other

Data are sent to Eurostat to be used in the compilation of european aggregates and to be released as national data.

10.6. Documentation on methodology

A description in Swedish of the survey is available on Statistic Sweden’s website and on request.

 

10.7. Quality management - documentation

Criterias for quality assessment in Swedish official statistics are the European Statistics Code of Practice. Criterias for quality assessment in swedish official statistics are found in the documentation Kvalitet för den officiella statistiken (A Handbook on Quality for Official Statistics of Sweden). The documentation can be found at Kvalitet för den officiella statistiken – en handbok, version 2:2 (scb.se)


11. Quality management Top
11.1. Quality assurance

In general, Statistics Sweden applies the European statistical Code of Practice.

Statistics Sweden uses the EFQM Excellence Model from the European Foundation for Quality Management as a framework for quality assurance.

11.2. Quality management - assessment

Overall Statistics Sweden has a high level of quality. The Index is highly relevant both as an input to quarterly national accounts and stand-alone. The level of accuracy is high. Comparability over time is somewhat affected by methodological changes to increase the accuracy. It is comparable with other statistical domains primarily the quarterly national accounts.


12. Relevance Top
12.1. Relevance - User Needs

Primary users and their needs are:

  • Trade organisations
  • National Accounts Department within Statistics Sweden: As input data in the quarterly national accounts compilation.
  • Ministry of Finance, governmental agencies and the national central bank: Input data into forecasts of the national accounts as well as analysis of the economic development.
  • Eurostat: Input data into analysis of the economy as well as the compilation of indicators and other statistics.
  • Banks and financial institutes: Input data in analysis and forecast of the economic development.

Secondaty users and their needs are:

  • Researchers and students: Input data in research and education.
  • Social actors: Analysis of the economic development.
  • Media: Publishing and release of data.
  • Enterprises/businesses: Analytical uses.
12.2. Relevance - User Satisfaction

Statistics Sweden has general satisfaction surveys but no specific survey for the short-term statistics.

Views and opinions of the users are collected through user councils with two to four meetings per year. The members of the council represents the users of the statistics which is funded by grants produced by Statistics Sweden. The council has an advisory role regarding questions concerning new statistics, development and improvement of existing statistics.

Statistics Sweden have regular meetings with main users.

12.3. Completeness

All EBS Manual requirments are fulfilled.


13. Accuracy Top
13.1. Accuracy - overall

There are a number of sources for inaccuracy in the Retail trade turnover index. This is an attempt to structure the possible sources for inaccuracy and to qualitatively describe the effects.

Coverage: The Retail trade turnover survey covers NACE Rev. 2 Division 47. The frame is constructed using a "frozen" version of the business register, so enterprises entering into the business register after this freezing moment is considered undercoverage, and enterprises exiting the frame after this moment are considered overcoverage.

Sampling: The sample method is stratified random sampling. Stratification variables are NACE Rev.2 activity and size of yearly turnover. The sample consists of eight size classes where size class 1-4 is sampled, 5-6 and 8-9 is censused. Size classes 1-4 consists of the smallest units and 5-6 of the largest. Size class 8 consists of complex units consisting of two or more legal units.  Size class 9 consists of various special cases.  Size classes are created using the Dalenius-Hodges rule. Sample size in each strata is determined using Neyman-allocation.

Nonsresponse: Nonresponse is handled by imputation methods for both item and object nonresponse. The imputation method consists of a list of ranked alternatives where the first alternative is used if it meets a set of criteria’s. If the first alternative is not possible due to failure to meet the criteria’s the next alternative is used and so on. The process is automated using the BANFF-system in SAS.

Measurement: As always there may be measurement errors with sampling. The statistics is cross-checked with sources such as VAT-data, in order to identify measurement errors and correct them. Questionnaire data for units in size class 1-4 is replaced with VAT-data on a quarterly basis for all units in the frame which decreased measurement errors. However the VAT-data also contain measurement errors and may have periodicity problems. But since each unit only represents itself the measurement errors are limited compared to a "normal" estimation.

Data processing: Turnover is deflated using Consumer Price Index. Errors and inconsistencies in this data source may affect accuracy of Retail trade turnover index.

Model assumptions: The frame is constructed using a cutoff where units over the cutoff together include 90-95 % (depending on industry sector) of the yearly turnover. The turnover for the units under the cutoff is assumed to have the same development in turnover as the units over the cutoff.

Data is revised, i.e. data changes after the first release.

13.2. Sampling error

The sample method is stratified random sampling. Stratification variables are NACE Rev.2 activity and size of yearly turnover. The sample consists of eight size classes where size class 1-4 is sampled, and 5-6 and 8-9 is censused. Size classes 1-4 consists of the smallest units and 5-6 of the largest. Size class 8 consists of complex units consisting of two or more legal units.  Size class 9 consists of various special cases.  Size classes are created using the Dalenius-Hodges rule. Sample size in each strata is determined using Neyman-allocation.

The Retail trade turnover survey is a probability sampling survey for first monthly estimates but a census on a quarterly basis. On a quarterly basis, data for units that are sampled using probability sampling is replaced by VAT-data for the part of the frame in size class 1-4. Data for censused size classes are never replace with VAT-data. First monthly estimates are based on survey data only, parts are then replaced.

Coefficient of variation for the first turnover estimates in G47 (%):

2022M01 0.49
2022M02 0.51
2022M03 0.5
2022M04 0.34
2022M05 0.38
2022M06 0.38
2022M07 0.45
2022M08 0.42
2022M09 0.4
2022M10 0.39
2022M11 0.42
2022M12 0.43
Average 2022 0.42
13.3. Non-sampling error

The Retail trade turnover survey Includes enterprises that have their main activity in Division 47 (NACE Rev. 2). The frame is constructed using a cutoff where units over the cutoff together include 90-95 percent (depending on industry sector) of the yearly turnover. The turnover for the units under the cutoff is assumed to have the same development in turnover as the units over the cutoff. The frame is constructed using a "frozen" version of the business register, so enterprises entering into the business register after this freezing moment is considered undercoverage, and enterprises exiting the frame after this moment are considered overcoverage.

The survey instrument is an electronic questionnaire. The questionnaire has been evaluated using cognitive interviews and expert evaluations in order to reduce the possibilities for non-sampling errors. However enterprises may mistakenly exclude VAT on total turnover and also mistakenly include export.

Nonresponses are handled by imputation methods. The imputation method consists of a list of ranked alternatives where the first alternative is used if it meets a set of criteria’s. If the first alternative is not possible due to failure to meet the criteria’s the next alternative is used and so on. The process is automated using the BANFF-system in SAS.

Turnover is deflated using Consumer Price Index. Errors and inconsistencies in this data source may affect accuracy.

Mean weighted unit response rate for total retail trade at first estimate of a reference period in 2022 was 84 percent. Turnover is used as weights.


14. Timeliness and punctuality Top
14.1. Timeliness

Retail trade statistics is published approximately 28 days after the end of the reference period.

Timetable (approx) of data collection:

T is the end of the reference period. 

T-1 Sending out questionnaires
T+1 First answer
T+15 Last day to submit the figures
T+16 Mail and e-mail reminder
T+20 Imputation, estimation and start of the checking of the data
T+26 End of checking of the data, last estimation
T+27 Data compilation, writing press release, updating tables and graphs etc.
T+28 Release of the preliminary results

14.2. Punctuality

 All releases have been done on time.


15. Coherence and comparability Top
15.1. Comparability - geographical

The methods and definitions is comparable with the European ones since the retail trade turnover statistics is produced according to the EBS Manual.

The same statistical concepts are applied in the entire Swedish national territory. No geographical discrepancies exist.

15.2. Comparability - over time

The retail trade turnover statistics has been produced since 1955. However there has been changes to NACE over the years which hampers comparability. The level of detail has also improved over the years.

In april 2015 Statistics changed the methodology mostly with respect to sampling and estimation. In order to avoid breaks, the time series were spliced together based on information from collecting and estimating statistics with both old and new method.

15.3. Coherence - cross domain

Dissemination of information that support statistical cross-checks and provide assurance of reasonableness: Comparisons can be made with the Swedish value added tax statistics.

Confrontation with other data sets: Ad-hoc confrontation with other statistical sources covering turnover (Value added tax register and Structural Business Statistics).

15.4. Coherence - internal

Yes the data is internally coherent. The difference between the retail trade turnover statistics and the VAT data is minor, specially for the major aggregates.


16. Cost and Burden Top

Statistics Sweden spend around 1500 hours/year producing the turnover for retail trade statistics.

The last investigation showed that respondents spend approxemently 15 minutes per month responding to the survey, which sums up to about 5700 hours/year.


17. Data revision Top
17.1. Data revision - policy

Routine revisions are made for two to four months prior to the current month depending on which month in the quarter the reference month is. The whole previous quarter is revised in connection with the publishing of the first and second month in a quarter. No calendar explicit for revisions exists. Revisions for previous periods are released at the same time as the release of a new period. Calendar adjusted and seasonally adjusted figures are always revised each month.

The same revision policy is applied nationally and in transmissions to Eurostat.

Retail trade turnover index is a chain-index, so no revisions occur due to regular base year changes (i.e. the rebasing that is carried out every fifth year due to STS requirements).

Major revisions may occur due to methodological changes. Methodological changes are announced in advance.

Non-scheduled revisions, i.e. unexpected revisions may occur due to errors discovered in the input data after results are considered definitive, if deemed necessary due to the magnitude of the error. Non-schedule revisions may also occur between normal releases if errors of a greater magnitude are discovered shortly after release.

Revisions analyses are carried out before data is released or sent to Eurostat.

No benchmarking is made.

17.2. Data revision - practice

Big and important revisions are announced when new data is released. Smaller revisions are not announced. Methodological changes are announced at the time of change. Sometimes the description is that the revisions have occurred but not a description of what the changes are.

Data in the questionnaire is collected for the last three periods which introduces revisions. Enterprises revising previously submitted data also introduces revisions.

Users are informed in advance of methodological and other changes which may lead to revisions. The information is included in the press release the month before the changes will come in to effect. Users are not informed in advance of the actual revisions.

No special revision calendar exists and revisions are published at the same time as figures for new months. The same revision policy is applied to data released nationally and transmitted to Eurostat.

No benchmarking is made. We do compare our data with VAT-statistics when reviewing data.

 

Mean Absolute Revision (MAR) and Mean Revision (MR):

Computed values for the last 36 monthly (Jan 2020 - Dec 2022) for total retail trade (NACE G47):

Growth rates for calendar/working day adjusted data series (YoY):

MAR = 0.34 , MR = -0.22


18. Statistical processing Top
18.1. Source data

Type of source - Statistical survey.

Frame on which the source is based - Swedish Business Register and Swedish value added tax register. All at Statistics Sweden.

Sample or census - Stratified sample survey. Includes enterprises that have their main activity in Division 47 (NACE Rev. 2).

Criteria for stratification - Activity and turnover are used for stratification.

Sample size in each strata is determined using Neyman-allocation. The two largest strata are censused and the four smallest one are sampled. Complex units i.d. Enterprises consisting of two or more legal units are always censused.

Threshold values and percentages - There are approximately 57 000 enterprises in the reference population. The survey includes approx 1400 enterprises for the year of 2022. Each activity in this survey is divided into size strata. The limits for the different size groups are based on annual turnover. Information on turnover is available for the whole population and collected from the value added tax register, but there is some time delay.

Frequency of updating the sample - The frame and sample population is updated in reference month april each year.

18.2. Frequency of data collection

Periodicity of data collection - All data is collected on a monthly basis. All data refers to the full reference period.

18.3. Data collection

Questionnaires used in the survey - In this survey one questionnaire is used. The enterprises (or units) provide turnover data for the required month and the turnover should be total turnover including value added tax and excluding exports.

Collected through random sampling survey. Most enterprises use an on-line questionnaire. New enterprises in the survey are contacted through regular mail with information and login information. Each month, after the end of the reference period, login information is sent to the enterprises through regular mail reminding them of the survey. A reminder is sent out around 15 days after the first contact. Important and/or larger enterprises are reminded especially if they have not yet responded at the end of the collection phase. During the production phase enterprises are contacted in order to get data from important and/or larger enterprises. Contact is primarily through phone and e-mail. The survey has a sanction system with a penalty for not responding.

Planned changes in national questionnaires - No planned changes.

18.4. Data validation

The online questionnaire contains a number of controls to check for incosistencies. The controls are soft and respondents are asked to correct or comment.

The data is then validated using a number of tools and checks:

  • Value set error - Checks for small enterprises with very large levels of turnover. It is fairly common that an enterprise responds in SEK rather then thousand SEK creating very large figures.
  • Accumulated turnover - Checks for enterprises that leaves an accumulated turnover. This is an uncommon problem.
  • Major enterprises - Checks major enterprises and their development compared to same month last year. Some enterprises are investigated more closely and also contacted to double check the figures.
  • Graphical data validation - Checks for outliers in a diagram.
  • Necessary outliers may occur
  • Development numbers - The development numbers are re-calculated using other formulas to see if there is something off. Same with price changes.

At the end of a validation cycle a meeting is held where the results of the different parts is presented. Any issues that haven't been solved yet is discussed at this meeting.

18.5. Data compilation

Missing observations from unit and item non-responses are dealt with by using automatic imputations carried out by the estimation programs.

The estimator is an Horvitz-Thompson type of estimator combined with VAT-information. Sampled enterprises are replaced with turnover based on VAT-data when quarterly turnover data is available. Censuses units are never replaced with turnover from VAT.

Turnover based on VAT does not only apply sample units in stratas that are sampled, but all units in the frame so the survey is a census on a quarterly basis.

The index method is a chained Laspeyre-index with weights updated each year using annual overlap.

The grossing up is based on the relation between the number of enterprises in the population and the number of responding enterprises in each activity and strata.

A program developed by Statistics Sweden fetches data from the internal databases and converts it to sdmx-file in order to transmit the data to Eurostat.

18.6. Adjustment

The turnover index is deflated using a consumer price index. For working day and seasonal adjustment: Software: Proc X12 in SAS 9.4 and ETS 12.1. Method: X-12-ARIMA.

The seasonal adjustment use an additive model.

We use a Partial Concorrent Revision principle for the seasonal adjustment. We make a revision every year and use it for the whole year until the next revision. Parameters are reestimated every time. The verification is checked in the annual revision.

We use a manual model. (20.6_10)

Decomposition method is supposed to be decided by each time series. They are all multiplicative so far.

A national calender is used and we adjust for moving holidays (e.g. Easter). We also adjust for leap year.

We use an automatic outlier detection with default critical values defined in X-12-ARIMA.

MSR: filter length chosen automatically by using the seasonality ratio of X-11-ARIMA/88.

There are no known breaks in the time series. Breaks in the original time series are linked using backcasting methods. 

Only direct SA is used. 

No extra measure is taken to achieve consistency, except coordination of ARIMA models between aggregates and their components.


19. Comment Top

Not available


Related metadata Top


Annexes Top