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The scope of the statistics is broadened from covering only NACE division 47 Retail trade, except of motor vehicles and motorcycles to also covering NACE division 45 Wholesale and retail trade and repair of motor vehicles and motorcycles and NACE division 46 Wholesale trade, except of motor vehicles and motorcycles. Thus, the new statistics covers the whole section G Wholesale and retail trade; repair of motor vehicles and motorcycles. In this first release value indices are published for 45 and 46, but in the coming months also volume indices and seasonally adjusted figures will be published for these divisions.
Index of wholesale and retail sales
Updated: September 28, 2021
Next update: October 28, 2021
About the statistics
The index of wholesale and retail trade describes the development in value and volume in the wholesale and retail trade sector - section G in SIC 2007. Wholesale is companies selling goods to other companies, while retailers are companies selling goods to private households. Previously published seasonally-adjusted figures may be revised when figures are added for a new month in the series.
Turnover includes sales income from goods and services, transport and emulsion cost which is invoiced to the customer, as well as rents, commission fees and royalties. Financial revenues and value added taxes are not included.
Name: Index of wholesale and retail sales
Topic: Wholesale and retail trade and service activities
Division for Business Cycle Statistics
No geographical breakdown available. National level only.
Monthly. The statistics are normally published between the 26th and 30th day of the following month.
The statistics are reported to Eurostat at the time of publication in Norway.
Primary data and compiled statistics are stored electronically in SAS files.
The objective of the Index of wholesale and retail trade is to describe the value and volume development in the wholesale and retail trade sector. The wholesale and retail trade sector consists of wholesale and retail trade and repair of motor vehicles and motorcycles, wholesale trade, except of motor vehicles and motorcycles and retail trade, except of motor vehicles and motorcycles. Wholesale is companies selling new and/or used goods to other companies, while retail trade is companies selling new and/or used goods to private households. Retail sales is executed from either a fixed or moveable sales outlet, a market place or via the Internet or mail order. Examples of retail sales are the sale of food, beverages, clothing, shoes, domestic electrical appliances, furniture, building equipment and so on.
The Index of wholesale and retail trade is the main component in the calculation of household consumption. The index have been published since 1936 and was until april 2021 named Index of retail sales. From april 2021 the index was broadened to also include sector 45 wholesale and retail sale and repair of motor vehicles and motorcycles and sector 46 wholesale, except of motor vehicles and motorcycles.
From November 1999, the sample of retail and wholesale companies has been supplemented gradually with turnover figures for chain stores reported directly by head offices. As a consequence, figures for newly established and closed down units for the above-mentioned stores are also more up to date.
Users include public and private sector agencies and organisations. Statistics Norway's national accounts statistics rely on timely production of the index of wholesale and retail trade. Other users include Statistics Norway's research department.
No external users have access to the statistics and analyses before they are published and accessible simultaneously for all users on ssb.no at 8 am. Prior to this, a minimum of three months' advance notice is given in the Statistics Release Calendar. This is one of Statistics Norway’s key principles for ensuring that all users are treated equally.
The index of household consumption of goods is published at the same time as the Index of wholesale and retail trade. The former is more extensive than the latter, which can lead to different developments in the two indices.
For calculating the volume indices of the Index of wholesale and retail trade the consumer price index is used for sector 45 wholesale and retail trade and repair of motor vehicles and motorcycles and sector 47 retail trade, except of motor vehicles and motorcycles while the price index of first-hand domestic sales is used for sector 46 wholesale, except of motor vehicles and motorcycles.
Changes in turnover are later compared with bimonthly wholesale and retail sales statistics which are based on the VAT register.
Regulation (EU) 2019/2152 of the European Parliament and of the Council of 27 November 2019 on European business statistics (EBS)
All establishments in the sector G, which consists of sector 45 wholesale and retail trade and repair of motor vehicles and motorcycles, sector 46 wholesale, except of motor vehicles and motorcycles (46.1 wholesale on a fee or contract basis is excluded) and sector 47 retail trade, except of motor vehicles and motorcycles (SIC2007: G.).
Monthly statistical surveys (simplified questionnaire), Statistics Norway's annual survey of wholesale and retail trade establishments (detailed questionnaire), the VAT register and Statistics Norway's Register of Establishments and Enterprises.
A sample of about 18 100 units is selected from the population of wholesale and retail trade establishments in the VAT register. This includes a sub-sample of 15 100 chain departments/stores with direct reporting from head office.
3 000 units is selected from other existing establishments, i.e. independent companies/shops and the remaining chain departments/stores not yet included in the sample above. This population is stratified according to size in terms of number of employees. The sample is adjusted as necessary to ensure a reasonably even geographical coverage and to incorporate available new information from the annual survey of wholesale and retail trade establishments and the bimonthly updated VAT register. In the latter case, the adjustments focus on diverging trends between turnover as measured by the sample and turnover as measured by a survey of the VAT register. In 1997, the sample was adjusted to take into account the variation of strata variances. The sample is rotated annually based on the second term of the turnover statistics. Establishments are retained in the sample for a maximum of four years unless they are part of a full coverage stratum.
Questionnaires are submitted electronically in the Altinn portal. If the respondents need help in filling in the questionnaire, Statistics Norway can be contacted by telephone. The establishments normally receive the questionnaire before the expiry of the survey month. The deadline is the 12th day of the following month. Failure to respond is subject to fines.
Prior to the statistical compilation, arithmetic and logical checks are carried out. This procedure also includes comparing the results with other data sources, mainly the wholesale and retail trade statistics.
Results broken down by sector and stratum are compared with data for the previous period and the corresponding period in the previous year. If the discrepancy is considerable, the respondent is consulted.
A ratio estimator is applied to each stratum to inflate sample data to population level. The ratio estimator uses turnover figures from the VAT register as auxiliary variables.
The establishments are divided into identical units and newly established units. These concepts are defined in Notater 93/17 Detaljomsetningsindeksen (in Norwegian only).
Newly established units are enterprises that have been registered in the Central Register of Establishments and Enterprises after the last rotation of the sample. The turnover of these enterprises is based on estimates as this information is not available. The estimates are based on information about newly established units in the same period in the previous year. The average turnover per establishment is calculated for newly established units in the same period in the previous year. On this basis the turnover for all recent establishments for the period in question is aggregated. The estimates for newly established units are made on stratum and sector level.
Volume indices at four-digit sector level are calculated by deflating value indices directly by means of the consumer price index for sector 45 and 47 and the price index of first-hand domestic sales for sector 46. At two and three-digit sector level the volume indices are calculated as a weighted sum of the volume indices at the four-digit sector level using value shares in the reference year as weight.
The index is adjusted for seasonal variations applying the X12ARIMA method with non-fixed seasonal effects and multiplicative model. As a supplement to seasonal variations, the new model takes into account the effect of weekdays, fixed holidays as 1 st and 17 th May, Easter, Pentecost, Ascension Day and 1 st New Year's Day. 24th to 26th of December are considered as seasonal variations with a method developed by Statistics Norway.
Refers to the separate tab "About seasonal adjustment" on statistics website.
The Index of wholesale and retail trade has been published since 1936. In April 2021 the name changed from Index of retail sales, since the index was broadened to also include sector 45 wholesale and retail trade and repair of motor vehicles and motorcycles and sector 46 wholesale, except of motor vehicles and motorcycles.
A new version of Norwegian industry classification (SIC2007) has been implemented from January 2009. The toal index, as well as three-digit sector levels, has been recalculated back to 2000 according to SIC2007.
In January 2003, Statistics Norway altered the calculation method for the price index used to deflate the retail trade sector. At this time the price index was only used to deflate the retail trade sector 47, except of motor vehicles and motorcycles, but is from 2021 also used to deflate sector 45 wholesale and retail trade and repair of motor vehicles and motorcycles. The new method is based on the price development of product groups from the consumer price index, as well as on sector-wise product allocation. The product allocation comes from a survey with that particular focus. The current method used to calculate this price index is using the same methods used to calculate the deflator of the retail sales component in the index of household consumption of goods. Volume figures have been calculated back to August 1999 using the current deflator.
The volume indices at four-digit sector level are calculated by deflating value indices using the aid of the consumer price index for sector 45 and 47, and the price index of first-hand domestic sales for sector 46. From January 2002, volume indices at two and three-digit sector level are calculated as a weighted sum of the volume indices at four-digit sector level with value shares in the reference year as weight. In the past, volume indices at the two and three-digit sector level were calculated using immediate deflation of value indices.
In compliance with Eurostat regulations the reference year was changed to 2015=100 when indices for January 2018 were published. Prior to this the reference year of the retail sales index was 2010=100.
Measurement errors (the respondent supplies erroneous data) and processing errors (wrong interpretation of figures and letters during) may occur.
Three types of errors are common:
- The respondent does not supply turnover figures for the establishment, but for a part of the establishment or the enterprise that the establishment is part of.
- The respondent does not report data for the correct time period (calendar month).
- Figures are in the wrong unit of measurement (usually in NOK instead of NOK 1 000).
Reminders are sent to enterprises that fail to respond in time. Failure to respond is subject to fines. These enterprises are treated in the same way as enterprises that are not included in the sample. This means that the change in turnover applied to these enterprises is the average percentage change that is applied to their stratum. Non-respondents normally constitute about 3 per cent of the total sample at the time of publication.
The results are uncertain as they are based on information from a sample of enterprises. The sample is updated once a year. Sample errors may also occur as a result of errors in the information that the sample is stratified according to.
Montly and quarterly time series are often characterised by considerable seasonal variations, which might complicate their interpretation. Such time series are therefore subjected to a process of seasonal adjustment in order to remove the effects of these seasonal fluctuations. Once data have been adjusted for seasonal effects by X-12-ARIMA or some other seasonal adjustment tool, a clearer picture of the time series emerges.
For more information on seasonal adjustment: metadata on methods: seasonal adjustment
Due to our shopping habits The Index of wholesale and retail trade will vary from month to month. For instance the month of December shows higher sale than the rest of the months. This combined with the influence of how the Easter holiday varies between March and April and also the influence of movable public holidays make a comparison from one month to the next difficult. To adjust for these circumstances the Index of wholesale and retail trade is adjusted for seasonal variations, so the underlying development of the index can be analyzed.
Seasonally adjusted series
The Index of wholesale and retail trade is published at the three-digit sector level, and constitutes 10 seasonally adjusted series. There is only for the sector 47 Retail trade, except of motor vehicles and motorcycles there is seasonally adjusted series. There will be seasonally adjusted series also for the sector 45 Wholesale and retail trade and repair of motor vehicles and motorcycles and sector 46 Wholesale, except of motor vehicles and motorcycles at a later time, when there is enough data to also seasonally adjust these series.
Running a detailed pre-treatment. This means using models which are specially adapted for the pre-treatment of the raw data for a given series.
Performing calendar adjustments on all series showing significant and plausible calendar effects within a statistically robust approach, such as regression or RegARIMA (a regression model with an ARIMA structure for the residuals). The regression variables for the calendar adjustment are adapted to reflect the working days, public holidays and so forth specific to Norway.
Methods for trading/working day adjustment
RegARIMA correction – in this case, the effect of trading days is estimated in a RegArima framework. The effect of trading days can be estimated by using a correction for the length of the month or leap year, regressing the series on the number of working days, etc. In this case, the residuals will have an ARIMA structure.
For 1st of January , 1st of May and 17th of May the correction of working days has been modified so that these days are regarded as a Sunday.
Correction for moving holidays
Correction based on an estimation of the duration of the moving holidays effects, specifically adjusted to Norwegian circumstances.
National and EU/euro area calendars
A calendar based on Norwegian holidays is used.
Treatment of outliers
Outliers are detected automatically by the seasonal adjustment tool. The outliers are removed before seasonal adjustment is carried out, and then reintroduced into the seasonally adjusted data.
Pre-treatment requires choosing an ARIMA model, as well as deciding whether the data should be log-transformed or not.
Automatic model selection by established routines in the seasonal adjustment tool.
The decomposition scheme specifies how the various components – basically trend-cycle, seasonal and irregular – combine to form the original series. The most frequently used decomposition schemes are the multiplicative, additive or log additive.
Manual decomposition scheme selection after graphical inspection of the series.
Choice of seasonal adjustment approach
Consistency between raw and seasonally adjusted data
Do not apply any constraint.
Consistency between aggregate/definition of seasonally adjusted data
In some series, consistency between seasonally adjusted totals and the original series is imposed. For some series there is also a special relationship between the different series, e.g. GDP which equals production minus intermediate consumption.
Do not apply any constraint.
Direct versus indirect approach
Direct seasonal adjustment is performed if all time series, including aggregates, are seasonally adjusted on an individual basis. Indirect seasonal adjustment is performed if the seasonally adjusted estimate for a time series is derived by combining the estimates for two or more directly adjusted series.
Indirect approach where the seasonal adjustment of components occurs using the same approach and software, and then totals are derived by aggregation of the seasonally adjusted components.
Horizon for estimating the model and the correction factors
When performing seasonal adjustment of a time series, it is possible to choose the period to be used in estimating the model and the correction factors. Correction factors are the factors used in the pre-treatment and seasonal adjustment of the series.
The whole time series is used to estimate the model and the correction factors
General revision policy
Seasonally adjusted data may change due to a revision of the unadjusted (raw) data or the addition of new data. Such changes are called revisions, and there are several ways to deal with the problem of revisions when publishing the seasonally adjusted statistics.
Both raw and seasonally adjusted data are revised between two consecutive official releases of the release calendar.
Raw data is not revised.
Concurrent versus current adjustment
Partial concurrent adjustment: the model is identified and estimated yearly, while filters, outliers and regression parameters are re-identified and estimated continuously as new or revised data become available.
Factors concerning the Easter holyday are estimated yearly.
Horizon for published revisions
The entire time series is revised in the event of a re-estimation of the seasonal factors.
Evaluation of seasonally adjustment data
Evaluation of quality based only on graphical inspection and descriptive statistics.
A model where the various quality indicators will be evaluated continuous/periodically in the future.
Quality measures for seasonal adjustment
For most of the series, a selected set of diagnostics and graphical facilities for bulk treatment of data is used.
Seasonal adjustment of short time series
All series are sufficiently long to perform an optimal seasonal adjustment.
Treatment of problematic series
None of the published series are viewed as problematic.
Raw data, pre-treated data and seasonally adjusted series are available.
All metadata information associated with an individual time series is available.
In addition to raw data, at least one of the following series is released: Seasonally plus working day adjusted.
- Notat 2009/27 Dokumentasjon av sesongjustering i SSB
- ESS-Guidelines on seasonal adjustment
- US census: X-12-ARIMA-manual
- Nye US Census-baserte metoder for ukedageffekter for norske data
- Notat 2007/43 Ny metode for påskekorrigering for norske data
- Notat 2001/54 Sesongjustering av tidsserier, Spektralanalyse og filtrering
- Notat 2001/02 Innføring i tidsserier, Sesongjustering og X-12-ARIMA