Index of production for services

Name: Index of production for services

Topic: Wholesale and retail trade and service activities

Division for Business Cycle Statistics

No geographical breakdown available. National level only

Frequency: Monthly.

Timeliness: The statistics are published around the 55 days after the end of the measurement period (month). All three months of the quarter will be revised around 85 days after the end of the quarter.

The statistics are reported to Eurostat at the time of publication in Norway.

Collected and revised data are stored securely by Statistics Norway in compliance with applicable legislation on data processing.

Statistics Norway can grant access to the source data (de-identified or anonymised microdata) on which the statistics are based, for researchers and public authorities for the purposes of preparing statistical results and analyses. Access can be granted upon application and subject to conditions. Refer to the details about this at Access to data from Statistics Norway.

The system for assuring the quality of Norwegian official statistics is based on quality requirements in the Statistics Act and in the European Statistics Code of Practice.The annual report on the quality of official statistics assesses compliance with the quality requirements for all official statistics as a whole.

The National programme for official statistics sets the framework for the areas Statistics Norway and other public authorities produce statistics on. The programme defines and outlines official statistics.

Further information about the system for quality in official statistics can be found at ssb.no

The aim of the Index of production for services is to describe the volume development within market-oriented service industries. The statistics must meet the requirements of European Parliament and Council Regulation (EU) 2019/2152 of 27 November 2019 on European business statistics.

The statistics covers the main business areas H (except H49 and H50), I, J, M (except M701, M72 and M75) and N as defined in the Standard Industrial Classification 2007 (SIC2007). The statistics will later be expanded to also cover H49, H50 and the main business area L.

The Index of production for services was first published in March 2025 with figures from and including the statistical period January 2019.

The production index is produced by deflating Turnover index for service activities by Producer price indices for services or the Consumer price index. Value added at factor cost from the Business statistics is used as weights.

The reference year for the index is 2021, i.e., 2021=100.

Primary users of the statistics are public sector agencies (Central Bank of Norway, Departments, etc.), private sector agencies and organisations within the industries. The statistic is used to analyse and monitor the development of the economy. At Statistics Norway the statistics is used by the Division for National accounts and research and analysis activity.

No external users have access to statistics before they are released at 8 a.m. on ssb.no after at least three months’ advance notice in the release calendar. This is one of the most important principles in Statistics Norway for ensuring the equal treatment of users.

The Index of production for services is calculated by deflating the Turnover index for service activities by Producer price indices for services or the Consumer price index. Value added from annual Business statistics is used as weights.

European Parliament and Council Regulation (EU) 2019/2152 of 27 November 2019 on European business statistics (EBS) ensures conceptual consistency across the different business statistics and between countries.

The statistics are developed, produced and disseminated pursuant to Act no. 32 of 21 June 2019 relating to official statistics and Statistics Norway (the Statistics Act).

The statistics are part of the national program for official statistics, main area Wholesale and retail trade and service activities, sub-area Service activities.

European Parliament and Council Regulation (EU) 2019/2152 of 27 November 2019 on European Business Statistics (EBS).

Monthly statistics are available from January 2019.

The population is defined by the The Central Register of Establishments and Enterprises (CRE) and covers all market-oriented Kind-of activity units (KAUs) within the service industries H (except H49 and H50), I, J, M (except M701, M72 and M75) and N as defined in the Standard Industrial Classification 2007 (SIC2007).

The Index of production for services is calculated by deflating the Turnover index for service activities by Producer price indices for services or the Consumer price index. Value added from annual Business statistics is used as weights.

Collection of data

The Statistics are calculated with input data from the statistics Turnover index for service activities, Producer price indices for services, Consumer price index and annual Business statistics. Hence, no direct data collection is carried out for the Index of production for services.

Editing

Editing is defined here as checking, examining and amending data. The Index of production for services is calculated by using already edited input data from other statistics.

Calculation

The Index of production for services is calculated by deflating the Turnover index for service activities by Producer price indices for services or Consumer price index. Value added from annual Business statistics is used as weights.

Pretreatment of the deflators from Producer price indices for services

For most service industries the Index of production for services is produced by deflating the Turnover index for service activities by Producer price indices for services.

The use of Producer price indices for services as input in monthly statistics production entails two challenges. Firstly, the input indices are published quarterly and hence needs to be disaggregated to monthly series, and second, they are published later than the Index of production for services for the same measurement period.

To meet the requirements of periodisation and timeliness, pretreatment of the Producer price indices is necessary. The pretreatment is carried out In two steps: forecasting and temporal disaggregation.

For the service industries 49.1, 49.3, 50.1, 55.1, 56.1, 79.1 and 79.9, the monthly Consumer price index is used as deflator. For these service industries, no pretreatments are necessary.

• Forecasting the Producer price indices for services

Forecasting of the Producer price indices for services is done by using an ARIMA-model in the programming language SAS.

The method for breaking up the figures from quarterly to monthly series described in the next step requires two quarters of the Producer price indices for services.

• Temporal disaggregation of the Producer price indices for services

The method used for breaking up the quarterly Producer price indices into monthly figures is linear interpolation with re-scaling, as recommended by Eurostat. The methods follows the three steps below:

1. First, the value of the the middle month of the quarter is set preliminary equal to the empirical value of the quarterly series.
2. Then preliminary values of the first and last month of the quarter are calculated by distributing the values from the mid-month of one quarter to the mid-month of the subsequent quarter equally. We now have monthly series in line with the quarterly series, but the averages of the monthly data does not correspond to the empirical quarterly data that were the starting point of the operation.
3. The final monthly values, where the average value of the three months in the quarter corresponds to the empirical quarterly value, are calculated by re-scaling or correcting the series. This is done by choosing values for all three months in the quarter that satisfies the three conditions below.

1. The average of the three months in the quarter is equal to the empirical quarterly series
2. The development from first and second month of the quarter is equal to the development in the preliminary values for the first and second month of the quarter
3. The development from second and third months of the quarter is equal to the development in the preliminary values for the second and third months of the quarter

Deflation and weighting

The deflation of Turnover indices by suitable price indices are done at three-digit NACE level (Group), according to the Classification of Standard Industrial Classification.

The indices at three-digit NACE level are weighted up to the published levels; two-digit NACE (Divisions), Sections and a total for market-oriented service industries by using value added from the annual Business statistics as weights. The weighting makes sure that changes in the relative importance of the service industries are taken into account. The weights are updated annually.

Preliminary and Principal figures

Since the Producer price indices for services used as input for most service industries does not meet the requirements for periodisation and timeliness for direct use as input in the calculation of monthly Index of production for services, it is necessary to publish preliminary figures which later are revised.

Preliminary indices are published about 55 days after the end of the month.

Principal figures for all three months of a quarter are published about 85 days after the end of the quarter.

Calculation of short-term indices

Short-term production indices are calculated by deflating short-term indices from the Turnover index for service activities by short-term indices from Producer price indices for services or Consumer price index at three digit NACE (NACE Group level).

The value of the short-term index for turnover and price shows the development of the series from January the same year to the statistics month. For the statistics month of January, the short-term index shows the development from January the previous year. An unadjusted short-term index of 105 means a five percent increase compared to January.

Chain-linking

Unadjusted short-term indices are chained to the long-term index (base 2021). This is done since the bases of the short-term indices and the weights changes once a year, and to evaluate the results of the index calculation over time.

See "About seasonal adjustment" at the end of "About the statistics".

Employees of Statistics Norway have a duty of confidentiality.

Statistics Norway does not publish figures if there is a risk of the respondent’s contribution being identified. This means that, as a general rule, figures are not published if fewer than three units form the basis of a cell in a table or if the contribution of one or two respondents constitutes a very large part of the cell total.

Statistics Norway can make exceptions to the general rule if deemed necessary to meet the requirements of the EEA agreement, if the respondent is a public authority, if the respondent has consented to this, or when the information disclosed is openly accessible to the public.

More information can be found on Statistics Norway’s website under Methods in official statistics, in the ‘Confidentiality’ section.

The Index of production for services was first published in March 2025 with start period of January 2019.

The reference year for the index is 2021, i.e., 2021=100.

The sample selection is defined from The Central Register of Establishments and Enterprises (CRE) and contains enterprises with underlying establishments within section H-J and M-N according to Standard Industrial Classification 2007 (SIC 2007).

The reference year for the index is 2021, i.e., 2021=100.

The quality of the index is dependent on the quality of the input data. The Index of production for services is calculated using input data from the statistics Turnover index for service activities, Producer price indices for services, Consumer price index and annual Business statistics.

Measurement errors due to errors in reported figures and processing errors due to incorrect treatment of reported figures are attempted avoided by using control systems specially adapted to each statistic.

Respondents are contacted in case of suspected errors in reported figures detected by automatic or manual controls.

The results are based on information from sample selections, with a certain degree of uncertainty. As in all sample-based surveys, biases in the net sample may occur related to the size and distribution of the non-response group. The response rate for OIT and TPPI is both between 95 and 100 per cent. Businesses that do not respond are warned and eventually imposed an enforcement fine.

Sampling errors may occur because of errors in the information by which the sample is stratified.

In addition to this, it is also uncertainty related to the methods of pre-treatment of the quarterly Producer price indices for services.

A revision is a planned change to published figures, for example when releasing final figures as a follow-up to published preliminary figures. See also Statistics Norway’s principles for revisions.

Preliminary figures for the Index of production for services is published about 55 days after the end of the month. Principal figures for all three months of a quarter are published about 85 days after the end of the quarter. The revisions are necessary because the quarterly Producer price indices for services used as input for most service industries does not meet the requirements for periodisation and timeliness for direct use as input in the calculation of the monthly Index of production for services.

Revisions in previously published seasonally adjusted figures can take place when new observations (or revised previous observations) are included in the basis of calculation. The scope of the revision is usually greatest in the most relevant part (last 1–2 years) of seasonally adjusted time series. A corresponding revision in trends is also typical, particularly at the end of the time series. The extent of the revision of trends and seasonally adjusted figures is partly determined by the revision policy, see Section 4 of the European Statistical System (ESS) Guidelines on Seasonal Adjustment on the Eurostat website. For more information on the revision of seasonally adjusted figures, see the ‘About seasonal adjustment’ section in the relevant statistics.

For monthly and quarterly figures, there are often significant seasonal variations which make it difficult to directly interpret the development from period to period. To facilitate the interpretation of such time series, many number series are seasonally adjusted using X-12-ARIMA or other seasonal adjustment tools.

For more general information about seasonal adjustment and the terms associated with it, see General information about seasonal adjustment (pdf).

Due to seasonal variations, the volume of production will vary from month to month. In the holiday months of June, July and August, for example, the volume of production in hotel and tourism industries will be high compared to other months of the year.

The index series are also corrected for the number of working days, variable public holidays and leap years. The Easter holidays and other moving holidays are examples of effects that make it difficult to compare from one month to the next. To be able to analyse the underlying development in the Index of production for services, it is therefore adjusted for these conditions.

Seasonally adjusted series

The seasonally adjusted series are published at 2-digit industry level, main industry areas and a total for market-oriented service industries.

Pre-treatment routines/schemes

A detailed pre-treatment is done. This means that the tools are based on special adjusted models and not based on standard options in the seasonal adjustment tools.

Calendar adjustment

Calendar adjustments are performed 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).

Methods for trading/working day adjustment

The series are corrected using RegARIMA modeling: The effect of working days is estimated by correcting for then length of each month when one also takes into account the occurrence of leap years. The regressor used is given by the number of working days. Within RegARIMA modeling, the effect of the working days is estimated, and an ARIMA structure is obtained for the residuals.

Correction for moving holidays

Correction for moving holidays is done by counting these days as Sundays.

National and EU/Euro area calendars

In the seasonal adjustment of the Index of production for services, a calendar based on Norwegian public holidays is used.

Treatment of outliers

Extreme values, also called outliers, are abnormal values ​​in the series.

Extreme values ​​are automatically identified in the seasonal adjustment tool and are removed before seasonal adjustment is carried out. The extreme values ​​are subsequently included in the seasonally adjusted figures. The seasonal adjustment during the corona crisis has been done in such a way that a level shift has been introduced in March and April 2020 and these months are not included in the basis for the calculations of the seasonal pattern. Technically, in the seasonal adjustment routine, this is done by specifying March and April 2020 as extreme values.

Model selection

Pre-treatment requires choosing an ARIMA model, as well as deciding whether the data should be log-transformed or not.

Model selection is primarily automatic, but in some cases, models are selected manually. A log transformation of unadjusted (raw) data is performed for pre-treatment of the series in the production index.

After the automatic model selection, the model parameters are held constant throughout the year.

Decomposition scheme

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.

For decomposition of the index a multiplicative decomposition is in use.

Choice of seasonal adjustment approach

X-13-ARIMA

Consistency between raw and seasonally adjusted data

In some series, consistency between raw and seasonally adjusted series is imposed.

For the production index for services, no constraints are applied.

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.

For the Index of production for services, there is no consistency imposed.

Direct versus indirect approach

Direct seasonal adjustment is performed if all the 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.

In seasonal adjustment of the Index of production for services, a direct method is used, where raw data is aggregated, and the components and aggregates are seasonally adjusted directly using the same approach and software. Inconsistencies across the aggregation structure are not removed.

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.

Seasonally adjusted data are revised between two consecutive official releases of the release calendar.

Concurrent versus current adjustment

The model, filters, outliers and regression parameters are re-identified and re-estimated continuously as new or revised data become available.

Horizon for published revisions

The seasonal adjusted figures for the whole time series can be revised when new observations are available.

When changing the method, the entire time series can be recalculated and updated.

Evaluation of seasonally adjustment data

Continuous/periodical evaluation using standard measures proposed by different seasonal adjustment tools.

Quality measures for seasonal adjustment

To analyse the time series, a limited range of diagnostics and graphics are used by the seasonal adjustment tool.

A monthly graphical and detailed empirical analysis is available.

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.

Data availability

Unadjusted figures (original series or raw data), calendar adjusted, seasonally adjusted and smoothed seasonally adjusted figures are available.

Press releases

In addition to unadjusted figures (raw data), the following series are released: calendar adjusted, seasonally adjusted and smoothed seasonally adjusted figures.

Dokumentasjon av sesongjustering i SSB

ESS-Guidelines on seasonal adjustment

Notat 2008/58 Nye US Census-baserte metoder for ukedageffekter for norske data

Notat 2001/54 Sesongjustering av tidsserier. Spektralanalyse og filtrering

Notat 2001/02 Innføring i tidsserier. Sesongjustering og X-12-ARIMA

EUROSTAT: Handbook on Seasonal Adjustment 2018 edition