Structural business statistics (sbs)

National Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: Statistics Norway

Time Dimension: 2015-A0

Data Provider: NO1

Data Flow: SBS_ESMS_A


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)
 



For any question on data and metadata, please contact: EUROPEAN STATISTICAL DATA SUPPORT

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1. Contact Top
1.1. Contact organisation

Statistics Norway

1.2. Contact organisation unit

Annex I: Transport, tourism and ICT statistics

Annex II: Division for Manufacturing and R&D statistics

Annex III: Division for Construction and Service

Annex IV: Division for Construction and Service

1.5. Contact mail address

Statistisk sentralbyrå
Postboks 1400 Rasta
NO-2225 Kongsvinger


2. Metadata update Top
2.1. Metadata last certified 07/04/2017
2.2. Metadata last posted 07/04/2017
2.3. Metadata last update 16/04/2019


3. Statistical presentation Top
3.1. Data description

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors).

SBS covers all activities of the non-financial business economy with the exception of agricultural activities and personal services. Limited information is available on banking, insurance and pension funds.

 Main characteristics (variables) of the SBS data category:

  • Business demographic variables (e.g. Number of enterprises)
  • "Output related" variables (e.g. Turnover, Value added)
  • "Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments)
3.2. Classification system

Statistical Classification of Economic Activities in the European Community (NACE): NACE Rev.1 was used until 2001, NACE Rev. 1.1 since 2002, and NACE Rev 2 is used from 2008 onwards. Key data were double reported in NACE Rev.1.1 and NACE Rev.2 for 2008. From 2009 onwards, only NACE Rev.2 data are available.

The regional breakdown of the EU Member States is based on the Nomenclature of Territorial Units for Statistics (NUTS). Detailed information about the consecutive NUTS Regulations can be found at Eurostat's website

The product breakdown is based on the Classification of Products by Activity (CPA) as stated in the Regulation establishing CPA 2008 and its amending  Commission Regulation (EU) No 1209/2014  (from reference year 2015 onwards)

3.3. Coverage - sector

The SBS coverage was limited to Sections C to K of NACE Rev.1.1 until 2007. Starting from the reference year 2008 data is available for Sections B to N and Division S95 of NACE Rev.2. With 2013 as the first reference year information is published on NACE codes K6411, K6419 and K65 and its breakdown.

3.4. Statistical concepts and definitions

The statistical characteristics are defined in Annex I of Commission Regulation (EC) No 250/2009

3.5. Statistical unit

Statistical units used for compiling the SBS series are in conformity with the definitions in Regulation No 696/93 (enterprise, local KAUs).

3.6. Statistical population

The Norwegian Register of Establishments and Enterprises is used for defining population for SBS. The registry comprises information about enterprises and local KAUs with respective NACE-codes, and is updated continually.  Active enterpises with the folowing NACE's Rev.2 are included in the target populasion: 41, 42, 43, 49, 50, 51, 52, 53, 58, 59, 60, 61, 62, 63, 05, 07, 08, 09.9, 10-29, 30, 31, 32, 33, 55, 56, 79, 09, 101, 09. 109, 36, 37, 38, 39, 68.1, 68.209, 69, 68.3, 70.2, 71, 72, 73, 74, 75, 77, 78, 80, 81,101, 81.2, 81.3, 82, 95, 45, 46, 47.

Enterprises with turnover more than NOK 300.000 define the target population.

Branches of foreign enterprises operating in the reporting country are included in the target population. They participate in the sample survey and they are required to report data as all the other domistic enterprises do. On the other side, the results from abroad activities of enterprises of reporting countries are excluded.

3.7. Reference area

Norway

3.8. Coverage - Time

Length of time series: 1999-2015

3.9. Base period

Not applicable.


4. Unit of measure Top
  • Number of enterprises and number of local units are expressed in units.
  • Monetary data are expressed in millions of €.
  • Employment variables are expressed in units.
  • Per head values are expressed in thousands of € per head.

Ratios are expressed in percentages.


5. Reference Period Top

2015


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

Year 1995 was the first year for the implementation of the Council Regulation No 58/97 (SBS Regulation).

The Council Regulation No 58/97 has been amended three times: by Council Regulation No 410/98, Commission Regulation No 1614/2002 and European Parliament and Council Regulation No 2056/2002. As a new amendment of the basic Regulation it was decided to recast the Regulation No 58/97 in order to obtain a new "clean" legal text. The European Parliament and Council Regulation No 295/2008 was adopted on 14/02/2008 and the provisions of this Regulation are applicable from the reference year 2008. Regulation No 295/2008 has been amended by Commission Regulation (EU) No 446/2014.

6.2. Institutional Mandate - data sharing

Not applicable.


7. Confidentiality Top
7.1. Confidentiality - policy

Legislation is developed to avoid misuse of data on statistical units, e.g. Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164).

7.2. Confidentiality - data treatment

Statistics Norway marks confidential data by using the flags listed below. We have the obligation to point out all secondary confidential cells as well as the data which is primary confidential at higher levels of aggregation of the activity or size class according to the national confidentiality rules.

Reason for confidentiality

 

Unit = enterprise or local kind-of-activity unit

Flag

-Less than three units

A

-One unit dominates the data

B

-Two units dominate the data

C

-Secondary confidential flag is applied to protect data flagged with A, B, C, F or H

D

-Data is confidential in application of the p%-rule

F

-Data which is not published at the national level as it is considered to be sensitive , or to protect data which is not required by Regulation (EC) No 295/2008 (manually unsafe data)

H

It is important to use the correct confidentiality flags to protect entities' sensitive data. The dominance percentage of the largest or the two largest units should be presented to ensure sufficient protection. Statistics Norway uses flag B when one unit has more than 90 per cent of the production value within the same economic activity. Flag C is used when two units have 95 per cent of the production value within the same economic activity.

 

Measures to reduce the number of confidential cells:

Technically we choose always a secondary confidentiality that is efficient by covering two primary confidentialities at the same time, as illustrated in the example below. Red figures are primary confidential, yellow ones are secondary confidential.

The economic activity B05 includes too few enterprises, and one company dominates the whole activity. To illustrate the importance of this activity in Norway, the Statistics Norway got the permission from the company to disseminate data in order to avoid using of confidentiality.

Economic activity

Size class

01

03

04

05

06

07

L68

38085

4826

189

50

23

2

L68.1

5044

553

26

2

1

 

L68.2

30928

3580

81

19

6

 

L68.3

2113

693

82

29

16

2


8. Release policy Top
8.1. Release calendar

Release dates are publicy accessible on Statistics Norway's webpage.

8.2. Release calendar access

https://www.ssb.no/en/kalender

8.3. Release policy - user access

Statistics Norway provides any information which is not available in the published publications and in the published on-line databases to the public authorities and a limited set of registered main users as well as to everyone with a specific request.


9. Frequency of dissemination Top

Annual


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

None.

10.2. Dissemination format - Publications

Regular web-publications in Norwegian and English:

http://www.ssb.no/en/sti

http://www.ssb.no/en/stvar

http://www.ssb.no/en/stinfokom

http://www.ssb.no/en/stranslag

http://www.ssb.no/en/stvareh

http://www.ssb.no/en/sthotell

http://www.ssb.no/en/stefu

http://www.ssb.no/en/stbygganl

10.3. Dissemination format - online database

The frequency of disseminating SBS results in the national on-line database: two times a year (preliminary and final dissiminations).

https://www.ssb.no/en/statbank/

10.4. Dissemination format - microdata access

None.

10.5. Dissemination format - other

None.

10.6. Documentation on methodology

"About the statistics":

http://www.ssb.no/en/sti

http://www.ssb.no/en/stvar

http://www.ssb.no/en/stinfokom

http://www.ssb.no/en/stranslag

http://www.ssb.no/en/stvareh

http://www.ssb.no/en/sthotell

http://www.ssb.no/en/stefu

http://www.ssb.no/en/stbygganl

10.7. Quality management - documentation

None.


11. Quality management Top
11.1. Quality assurance

The systemic quality reviews based on the guidelines for European statistics "Code of practice". The purpose is to contribute to quality assurance and improve of production processes.

11.2. Quality management - assessment

12. Relevance - high.

13. Accuracy -high.

14. Timeliness and punctuality -high.

15. Coherence and comparability -high.


12. Relevance Top
12.1. Relevance - User Needs

Internal users:

both public and private sector agencies/organisations. Statistics are used by the government, political parties, civil servants, financial companies, opinion-polling firms, social researchers, media etc.
Within Statistics Norway, the statistics are primarily used in National accounts statistics and research.

 External users: Eurostat.

The data sent to Eurostat and published at the national level vary from annex to annex, and the main difference resides in the number of variables and definition used for gross investment.  Both the acquisition of capital and the sale of used capital stocks are considered when assessing the gross investments at the national level, while the acquisition of capital only is considered in the data sent to Eurostat.

12.2. Relevance - User Satisfaction

None.

12.3. Completeness

The economic activities H5122 and M701 are not available as there are no activities within these structural economic areas in Norway.

The economic activity N783 has been included in the economic activity N782 because there are few enterprises within the activity N783.

Gross investment in existing buildings and structures (V15130) is a part of the gross investment in construction and alteration of buildings (V15140).


13. Accuracy Top
13.1. Accuracy - overall

High overall accuracy level.

The results are normally final after 4 months from the first release.

13.2. Sampling error

Methodology used: sample survey combined with administrative information.

Coefficients of Variation.

The population consists of all enterprises in industry divisions which have registered activity in the reference year of 2015.

The method used to calculate variance by Statistics Norway is known as "Nearest Neighbour variance Estimation: NNVE".

NNVE is used at each 5 digit Nace level aiming to allocate values for non-sample units whose data are not available in the administrative sources. This method has some well-functioning characteristics. First, it is a hot deck method in the sense that non-sample values are substituted by the relative values of the same sample-variables (donors) by using the ratio turnover/ number of person employed. The imputed values are actually occurring values, not constructed ones.

The population is divided into two parts: the sample part and non-sample one. The calculation of the sampling variance for the requested variables concern exclusively the non-sample part. The variance within each stratum is calculated as the square of the number of times a unit is used as a donor times the variance, meanwhile the variances for the variables in this model are approximated by assuming that values for variables that are not covered by statistical forms or administrative information, are estimated by a ratio model based only on turnover.

The Number of enterprises (11 11 0), Number of employees (16 13 0), Gross investment in tangible goods (15 11 0) and Turnover (12 11 0) are not estimated since a full census is applied. Accordingly, the variances for the mentioned variables are zero.

Model estimations of the coefficients of variation have been done for the following two variables: 12 15 0 (Value added) and 13 31 0 (Labour costs). As it is not possible to survey every business in the population, variance of the estimated population total is estimated by a ratio model where turnover is used as auxiliary variable for these characteristics. For this purpose weights based on turnover which is available for all the units in the population are used to represent the effect of stratified sampling.

13.3. Non-sampling error

Description of estimation methods.

In SBS non-respondent enterprises are treated in the same way as enterprises outside the sample. In some cases the general trading statements have to be constructed. For instance, the annual accounts are available on the internet, or the percentage values from last year are used to allocate the values in the general trading statements.

The measures taken or envisaged for minimising the unit non-response:

In structural business statistics enterprises are forced to answer and return the survey questionnaire form by the legal authorities (Statistics Act Sections 2-2 and 2-3) and the legal documents (Council Regulation no. 58/97 of 20 December 1996):

"The King may by regulation or resolution impose upon any person an obligation to provide the information which is necessary for the production of official statistics in so far as any legally prescribed obligation of secrecy is no obstacle thereto. A deadline may be set for the provision of information and stipulations may be made regarding the form in which the information shall be given. The obligation to provide information is breached when the information required is not given before the expiry of the deadline". Statistics Act of 1989 - §2-2

The body which has laid down the obligation to provide information may impose compulsory fines payable to the state upon such person as breaches this obligation. The imposition of compulsory fines shall be grounds for enforcing payment. Such compulsory fines may be collected by distrait. In special cases compulsory fines that have been incurred may be waived wholly or in part. The King[2] may issue more detailed provisions concerning such compulsory fines.

When the State Agency for the Recovery of Fines has been instructed to collect a compulsory fine as mentioned in the first paragraph, it can do so by garnishing wages and other similar payments pursuant to the rules in Section 2-7 of the Creditors Security Act. The Agency may also enforce payment of the fine by establishing an attachment charge in respect of the claim, provided the claim can be given legal protection by being registered in a register or notified to a third party, cf. Chapter 5 of the Mortgage Act, and the attachment proceedings can be conducted on the premises of the Agency according to the first paragraph of Section 7-9 of the Act relating to the Enforcement of Claims. Statistics Act of 1989 - §2-3

In addition, Statistics Norway has constructive communication with significant enterprises trough meetings, phone calls and email conversations regarding the quality of data transmitted.

Weighted unit non-response rate:

Only the set of main sample units is taken into the calculations of non-response. If the enterprise doesn't deliver:

1) the questionnaire form

2) the data from the Directorate of Taxes' General Trading Statements

the unit is to be considered as a "non-response" unit .

Since statistics related to the variables "Number of enterprises" (11 11 0), "Turnover" (12 11 0), "Gross investment" (15 11 0) and "Number of persons employed" (16 11 0) are available for the entire population, the value of non-response for these variables is zero by definition.

Calculations of the non-response rates for the variables "Value added" (12 15 0) and "Labour costs" (13 31 0) are determined by the gross main samples and the net main sample by groups at three digit level:

Non-response rate:

= Round (1000 * (1- (numerator/denominator)))

Non-response:

= Denominator - Numerator

Sample: = All enterprises included in the main sample as defined in Section II.1.1

Denominato1:

= Gross main sample

Numerator:

= Net main sample

Net main sample:

= The net main sample as presented in the final population

Unit:

= Enterprise as defined by the "Central Register of Establishments and Enterprises".

How do you evaluate the recorded unit non-response rate in the overall context? Very low.

 

The possible bias resulting from non-response or from the estimation method:

Sample bias may arise when the sample doesn't give a representative picture of the population. Stratification is used in the structural business statistics to reduce that possibility. Non-responses that are not randomly distributed can still make the sample biased. Post-stratification is used to adjust any inconsistencies arising due to non-responses.

How do you assess the impact of imperfection of the relevant business register on the quality of the key statistics? Low.

The methods used to detect the out-of scope units: out-of-scope units are establishments which have Nace digit level outside a distinct Nace-section (Structure of SIC2007). The Norwegian Register of Establishments  and SAS EG software are good tools  to detect those units.


14. Timeliness and punctuality Top
14.1. Timeliness

Data-collection: 01/2016

Post-collection phase: 10/2016

Dissemination: 04/2017

14.2. Punctuality

No delay.


15. Coherence and comparability Top
15.1. Comparability - geographical

The same statistical concepts are applied in the entire national territory.

15.2. Comparability - over time

The difference between length of time series and the length of comparable time series stems from transition to NACE Rev.2.0. However, the Statistics Norway, at the initiative of Eurostat, has already accomplished the transmission of NACE Rev.2 data for reference years 2005-2007, to make series more comparable.

1999-2007 (old NACE rev. 1.1),

 2008-2015 (new NACE rev. 2.0)

15.3. Coherence - cross domain

Number of enterprises in the business register:

Business register is subject to constant updating. It is therefore considered as a reliable source for all produced statistics.

Production value of Prodcom:

Prodcom defines production value as the value of own production, while the Structural Business Statistics defines production value as turnover corrected for alteration in the stock of manufactured goods, work in progress and goods for resale. In addition, the Structural Business Statistics includes revenues that are not directly attached to ordinary industrial production.

Value added of National accounts:

There are some differences in the way value added is calculated in SBS and in the National accounts.

National accounts re-examines some items used in the calculation of production and operating costs in SBS. Own production is included in total production in National accounts, while some operating costs in SBS are considered as investment in National accounts assessment. Moreover, National accounts assesses a part of labour costs in the calculatiopn of value added.

Evolution of turnover and persons employed from short term statistics:

The inconsistencies in terms of persons employed in Structural Business Statistics and in short term statistics are revealed by the way the sample survey is compiled. The number of persons employed is based on a full census and obtained through administrative sources in Structural Business Statistics, while by interviews or surveys in the short term statistics.

Business services (CPA)-turnover in Annex VIII versus Annex I:

The definition of turnover in Annex I and Annex VIII is the same.

15.4. Coherence - internal

The aggregates are not always consistent with their main sub-aggregates (e.g. the total for different NACE, NUTS, CPA) due to roundings.


16. Cost and Burden Top

Time needed to fill out the questionnaire is estimated to be around 30 minutes in average per enterprise.


17. Data revision Top
17.1. Data revision - policy

Annex I-IV:

Wrong interpretation of the questions and miscalculations are the main reasons for revision. Revision is to be made if non-correction has a significant impact on the data at a 2-digit level.

17.2. Data revision - practice

The data sources for the preliminary and final statistics are the same. However, only three variables (the number of enterprises, turnover and the number of persons employed) are published for enterprises for preliminary data, while a set of other variables for both enterprises and local KAUs is published for final data. The published preliminary variables are also subject to revision after preliminary dissimination.

Data revision practice includes both micro- and macro revision.

The data collected are to be thoroughly revised at the micro level in the sample for multi-local KAUs enterprises. Consistency controls are performed between items against the results from the previous year, against production statistics, against the Central Register of Establishments and Enterprises, against the Standard Industry Form and against the annual reports.

Revision at macro level is applied to a greater degree in final data. 


18. Statistical processing Top
18.1. Source data

Sample survey combined with administrative information.

Type of sample design: stratified.

The survey is carried out by a sample.

Stratification criteria: activity and employment size class. The enterprise must have ordinary activity and be registered before the first of October in the reference year. The same criteria concern the belonging local KAUs.All multi LKAU enterprises and large sized single enterprises with 100 or more persons employed are surveyed exhaustively. The enterprises below that threshold are surveyed by means of a stratified sample according to size class.

Selection schemes (sampling rates):

In the framework of the recent re-examination of the survey plans for structural business statistics, Statistics Norway has as of the statistical year 2011, applied a new survey plan where the sample size is reduced considerably by 40 per cent. The new survey plan is conducted with the objective of reducing exclusively the number of small enterprises from the stratified samples, while the sampling variance of estimate sub-population parameters stays low as in the old survey plan. Optimization of the participation of the small enterprises, especially enterprises with individual proprietorship where the owner is working alone (one-man enterprise), can be also perceived as a part of efforts to minimise the respondent burden.

The population consists of all non-financial enterprises in the relevant industry divisions registered as operative in the reference year. The population is divided into subpopulations, called strata, after criteria like industrial classification and number of employees. In some of the strata, all enterprises are always included in the sample. From the remaining strata, a representative selection of enterprises is drawn. All enterprises in this sample are asked to report a full set of Trading Statements and to complete a questionnaire.

The new sample scheme provides a size-consolidated sample which includes to a greater degree large size businesses, classified in high employment size, and to a lesser degree small size businesses, classified in lower employment size. The sample method ensures thus that businesses with the largest contribution to an industry are not omitted.

It also ensures that the respondent burden on small businesses is minimized. All multi LKAU enterprises and large sized single enterprises still have full coverage. All enterprises with more than 50 employed, the first 5 enterprises with the largest annual turnover in each economic activity are selected with respect to the optimized sampling method. Businesses can be manually added to the sample after the sample selection if they are important for its industry.

The data from the survey is combined with the additional information from the various registers and the structural survey of Statistics Norway to form the basis for the estimation of the financial structures of the different industries.

Once the population is stratified, a main sample, a supplementary sample, and a nonsample, which constitute the population, are obtained for each NACE at different digit-levels.

Any possible threshold values:

Enterprises with investment value greater or equal to NOK 10 million are included in the population, even though they might not have turnover or employment. Otherwise, each enterprise must have either employment or turnover in order to be included in population.

The effective sample size:

The effective sample size for each NACE section is as follows:

NACE Number of enterprises in the sample
B 194
C 1764
E 129
F 1275
G 3487
H 1416
I 783
J 750
L 548
M 994
N 863
95S 66

 

 

 

The used administrative sources:

  • VOF - The Central Register of Establishment and Enterprises of Statistics Norway
  • NO - Directorate of Taxes' General Trading Statements
  • A-ordning
  • The VAT-Register

 

The Central Register of Establishments and Enterprises of Statistics Norway (VoF) is used as the basis for sampling, revision, and production of SBS statistics.

NO - "Directorate of Taxes' General Trading Statements" are forms containing the enterprises' profit and loss account and balance sheet.

The VAT-Register - Enterprises are required to send VAT returns to the county tax assessment office six times a year. Business enterprises with an annual turnover of less than NOK 1 million may apply to submit VAT returns annually. The turnover for those enterprises which don't submit General Trading Statements (NOs) is obtained from the VAT-Register.

The a-ordning is a coordinated service used by employers to report information about income and employees to NAV (the Norwegian Labour and Welfare Administration), Statistics Norway and the Norwegian Tax Administration. The service is digital. The information is submitted electronically, either via the employer's payroll system or via a service in Altinn. The Norwegian Tax Administration administers the scheme on behalf of the other public agencies. The a-ordning entered into force on 1 January 2015. The aim was to simplify and coordinate the reporting of information by employers by replacing five forms with a single a-melding.

From 2015, the Structural Business Statistics are based on a new data basis for wage earners (A-ordning).

New data source for NACE Rev.2 06 and 49.5

From the reference year of 2015, the figures for NACE Rev.2 06 "Extraction of crude petroleum and natural gas" and 49.5 "Transport via pipeline" in the SBS are based on a new data source. This resulted in a break in the time series between 2014 and 2015. The new data sourced from the annual statistics Extraction and related services, which also is the main data source for the National Accounts (NA). The population covers all approved operators and license owners on the Norwegian continental shelf, including fields, terminals and offices, in addition to businesses in NACE 49.500 and pipelines registered as separate units in the business register. The data collection is a complete census, and the population is based on information from the Norwegian Petroleum Directorate (NPD) and the Ministry of Petroleum and Energy (MPE) in addition to central principles for population management. Previously, the issue of inconsistent figures between SBS and NA was caused by use of different data sources. The advantage of new data source is that the figures between SBS, the annual statistics and NA are more consistent now. Furthermore, the definition of economic variables is more consistent between EUROSTAT and NA due to the change of data source.

New data source for NACE Rev.2 35.1

From the reference year of 2015, the figures for NACE Rev.2 35.1, "Electric power generation, transmission and distribution" in the SBS are compiled using a new data source. The change of data source results in a break in the time series between 2014 and 2015. The new data source is the same source used for producing of the annually monetary statistics for the "Electricity". The population covers enterprises that have a license for electricity generation, transmission and distribution in addition to trade of electricity. The annually monetary statistics for "Electricity" is the main source for the compilation of NACE 35.1 in the National Accounts, and by changing to the same data source also for SBS there will be better consistency between National Accounts and SBS. The change in the data source for the SBS-figures for NACE Rev.2 35.1 came as a result of a project in Statistics Norway concluding that the same data source used for the annually monetary statistics for electricity and the National accounts also could be used for assembling most of the variables that Eurostat requires in the transmission of SBS.

The extent to which the administrative source are used:

data source, basic data for some characteristics

data source for imputation in case of non-response

data source for imputation, for strata not covered by the survey

data source for 'mass imputation': (imputation of units not selected in the sample)

data source for calibration (calage sur marge) to optimize inference from survey results.

 

What kind of administrative data do you access?

-micro data

-aggregated data: for the entire population (global data).

How do you assess the frequency to which the used administrative data sources are updated?

Very good.

Are the administrative data subject to several revisions with (increasing) degree of completeness? Yes.

Which is the relation between the reporting unit for the survey/administrative data and the enterprise? Reporting unit = enterprise.

 

 

Frame:

The sample is drawn from The Central Register of Establishments and Enterprises of Statistics Norway (VoF) for the survey.

What is the variable used for identifying principal and secondary activities?

Number of employees and/or turnover are regarded as the important criterium for determining principal activity for a reporting unit. The priority given to criteria is as follows:

  1. Value added (if information is given).
  2. Number of employees (if no information on value added).
  3. Turnover (if no information on value added or number of employees).

What is the method used for identifying activities?

Top-down.

Enterprises shall be classified according to the unit's principal activity. The Regulation associated with the NACE Rev.2.0 states that the identification of a principal activity is necessary to allocate a unit to a particular NACE Rev.2.0 heading. Further it says that the "principal activity" is identified by the "top-down" method in terms of the activity that contributes most to the total value added of the entity under consideration.

The algorithm used to determine principal activity for a unit (local, enterprise etc.) in "VoF" takes account of the hierarchical nature of NACE Rev.2.0. The simplest way to describe this method is shown by an example. Consider the following fictitious enterprise: from the Annual Structural Business Survey we know that the enterprise carries out activities of a mixed character corresponding to the following NACE classes.

EXAMPLE:

Stage 1: A reporting unit may carry out the following activities

Local KAUs

SECTION

DIVISION

SUBCLASS

NUMBER OF EMPLOYEES

A

C

28

28.290

13

B

C

26

26.400

3

C

C

26

26.520

15

D

C

33

33.200

8

E

G

45

45.190

7

F

G

45

45.300

28

G

M

74

74.900

13

ENTERPRISE

   

26.520

87

The principal activity is determined by the number of employees as follows:

Stage 2: Identify the largest section

Sum Section C 39

Sum Section G 35

Sum Section M 13

Stage 3: Identify the largest division

Sum Division 26 18

Sum Division 28 13

Sum Division 33 8

Stage 4: Identify the largest subclass

Subclass 26.520 15

The largest subclass is 26.520, and we allocate this activity code to the reporting unit. The enterprise has now a principal activity with the activity code 26.520.

Please comment on the frequency of updating the unit's principal activity (stability rules).

The updating of unit's principal activity occurs seldom. In some cases an enterprise might have wrong classification. In that case the unit's Nace is subject to correction.

Please comment on the frequency of updating the business register in your NSI:

The business register is updated twice a month.

The frequency with which the sample is updated: a new sample is drawn every year.

18.2. Frequency of data collection

Annual data collection

18.3. Data collection

The type of questionnaires used:

From 2015,  a new way of gathering data for the SBS has been introduced. The submitting of electronic questionnaires is to be done through "Altinn" - the Norwegian  Internet portal which is used for reporting of data to public authorities.

There are some built-in quality/consistency checks in the electronic questionnaires exc. soft/hard checks.

The enterprises which did not reply within the deadline are reminded to fill the questionnaires by post, if not - the sanctions are applied.

For administrative sources, the direct method to access the data bases is applied.

18.4. Data validation

Validation rules applied before the data are transmitted to Eurostat:

We check if variables which are to be delivered from Statistics Norway are in accordance with standards specified by Eurostat.

Singles series validation chesks are run with the help of EDIT validation tool. Inter-series checks are performed as well.

18.5. Data compilation

For the enterprises in the sample which have submitted an income statement ("NO") and questionnaire, no variables are estimated. For enterprises not in the sample, but for which income statements (NOs) are obtained, only variables from the questionnaire are estimated. For the remaining enterprises, all variables except turnover and employment are estimated on the basis of figures from the sample. For units which do not report employment to the register, but have salary figures or sales figures that indicate employment, the employment rate is calculated.

Turnover and employment are considered as known variables for all enterprises and are therefore used as a basis for computing missing variables. Previously an industry mean based on sample units was used to estimate missing data for non-sample units (ratio estimates). As of the statistical year 2011, the method is based on finding a sample unit similar to the non-sample unit to be estimated, based on a set of criteria, and using the sample-unit to estimate the missing values (nearest neighbour estimation). The nearest neighbour criterion is industry combined with the turnover/employment ratio, in that order.

18.6. Adjustment

Statistics Norway uses the annual report from the previous year to adjust the eventual differences between the reference period and the calendar year for SBS.


19. Comment Top

None.


Related metadata Top


Annexes Top