Lowest growth in earnings in the 2000s
Labour market and earnings
lonnansatt, Earnings of all employees, occupational groups, public sector, private sectorEarnings and labour costs, Labour market and earnings
The statistics provide earnings of all empoyees. The monthly earnings increased by 1.6 per cent from September 2015 to September 2016.

Earnings of all employees


Next update

Key figures

1.6 %

wage increase from 2015 to 2016

Average monthly earnings of all employees, by sector and sex
Monthly earnings
20152016Percentage change
Sum all sectors42 60043 3001.6
Males45 60046 2001.3
Females38 90039 8002.3
Private sector and public enterprises43 20043 8001.4
Males45 70046 2001.1
Females38 30039 1002.1
Local government38 60039 5002.3
Males40 80041 5001.7
Females37 90038 8002.4
Central government45 70046 5001.8
Males49 70050 3001.2
Females43 00043 8001.9

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Table 1 
Average monthly earnings of all employees, by occupational group

Average monthly earnings of all employees, by occupational group
Monthly earnings
20152016Percentage change
All occupations42 60043 3001.6
Managers62 80063 8001.6
Managing directors and chief executives72 50073 9001.9
Professionals48 80049 6001.6
Technicians and associate professionals47 30047 9001.3
Clerical support workers35 90036 6001.9
Service and sales workers31 70032 4002.2
Skilled agricultural, forestry and fishery workers30 70031 7003.3
Craft and related trades workers35 70036 3001.7
Plant and machine operators and assemblers36 60037 2001.6
Elementary occupations30 30030 9002.0

Table 2 
Average monthly earnings of all employees, by section

Average monthly earnings of all employees, by section
Monthly earnings
20152016Percentage change
All industries42 60043 3001.6
Agriculture, forestry and fishing33 60034 6003.0
Mining and quarrying68 00069 2001.8
Manufacturing43 80044 4001.4
Electricity, gas and steam54 60055 6001.8
Water supply, sewerage, waste39 40040 3002.3
Construction39 80041 0003.0
Wholesale and retail trade: repair of motor vehicles and motorcycles37 90038 9002.6
Transportation and storage42 90043 2000.7
Accommodation and food service activities29 10029 7002.1
Information and communication54 90056 3002.6
Financial and insurance activities60 10062 1003.3
Real estate activities50 60051 5001.8
Professional, scientific and technical activities53 40053 8000.7
Administrative and support service activities36 10036 9002.2
Public administration and defence45 30046 1001.8
Education42 00042 9002.1
Human health and social work activities38 90039 6001.8
Arts, entertainment and recreation37 00037 8002.2
Other service activities39 10040 1002.6

About the statistics

The purpose of the statistics is to provide an overview of wage levels and wage changes for all employees. The source of the statistics is A-ordningen.


Definitions of the main concepts and variables

In the statistics, wages and salaries refer only to cash payments from employer to employee for work rendered. The statistics hence do not include payment in kind, insurance or non-taxable expense allowances and the like.

Monthly earnings

Monthly earnings are the main term in Statistics Norway’s wage statistics. Monthly earnings cover basic salaries, variable additional allowances and bonuses. Overtime pay is not included in monthly earnings.

Basic salaries

Basic salaries are the actual payment at the time of the census and are often described as salary by scale or regular basic wage. Qualification/skill allowance and other regular personal allowances are included in this type of wage. The wage or salary may be payment by the hour, week, fortnight or month.

Variable additional allowances

As a rule, variable additional allowances are associated with special duties or working hours and the figures given are a calculated average per month for the period 1 January to the time of the census. Variable additional allowances cover allowances for working evenings and nights, call-out allowance, shift allowance, dirty conditions allowance, offshore allowance and other allowances that occur irregularly.


This item includes allowances that are usually not connected with specific duties and where the payments occur irregularly with respect to the period in which they are earned or to which they apply. Other examples of types of payments under this item are profit sharing, production allowance and gratuities. The figures given for bonuses are a calculated average per month for the period 1 January to the time of the census. This is done because the types of payments covered here are often paid out at irregular intervals and because the earning period is not necessarily the same as the period in which the payment was made.

Payment for overtime work

Payment for overtime work covers the sum of cash compensation for work done beyond contractual working hours, which is then compensated with a supplement to the basic wage or salary. Overtime compensation is a calculated average per month over the period 1 January to the time of the census. This type of payment is not included in monthly earnings, but figures are given for overtime compensation when the statistics are released.

Annual wage 

In the time series from 1997 to 2015, annual wages are calculated as follows:


Annual wages assume that wages are paid for 12 months and include the three main elements of the monthly wage concept; agreed monthly salary, bonuses and irregular additions. Overtime pay is related to work outside the mainstream working hours, and is not included in the wage concept. The same applies to fringe benefits, holiday pay additions, severance pay and payment in arrears.

The calculation of annual wages is based on the following sources of information:

1. Two years of annual wage statistics

2.The quarterly wage index. This is established for the entire private sector with the exception of aquaculture and the financial industry. In the public sector, it only applies to the health authorities.

3.Institutional information (information on results from the wage settlement or other factors that affect wage levels during the year in which the annual salary is calculated). This is used for industries and regions for which no quarterly wage index is available (see paragraph 2).

Annual wage in an industry is equal to the sum of the agreed monthly wage for each
month during the year, plus the sum of the average bonus and
variable additional per month. Developments on the agreed
wages during the year are determined by the wage index, while addition and
bonuses remain unchanged every month throughout the year.
More information on calculating annual wage: Documentation calculation system for annual wage.

Full-time and part-time

From 2015, full-time employees are defined as employees with a 100% position. Anyone with less than a 100% position is classed as a part-time employee. By combining information about the workload and the number of hours in a full-time position, the contractual working hours per week are calculated for each employee. The definition of a full-time position will thus suggest that the contractual working hours per week are between 28 and more than 40 hours based on a rotation/shift arrangement. The weekly contractual working hours of the majority of full-time employees are 37.5.

Full-time equivalents

In the statistics, employees who work less than 100% are defined as part-time employees. In order to compare salaries between full-time and part-time employees, the wages of part-time employees are converted to the equivalent for full-time work. This is done using the percentage of each part-time employee’s position as a conversion factor. Monthly wages per full-time equivalent for part-time employees can then be merged with the monthly salary of full-time employees so that the average monthly earnings for all employees can be calculated.

Contractual working

Contractual working hours are defined as contractual working hours per week, excluding meal breaks. No deductions are made for absences due to holiday, illness, leave or such like. For workers whose working hours vary from week to week, the average working hours per week for a year or last month are reported.

Age and sex

The national identity number indicates age and sex.

Standard classifications

Industrial classification

A key component of the wage statistics is classification by industry in accordance with the Standard Industrial Classification SN07 (NACE Rev. 2), which is the Norwegian version of the international Standard Industrial Classification (SIC94).

For more information about the Standard Industrial Classification:



Sector encoded by institutional sector classification as follows:
Sector 6100: Central government
Sector 6500: Municipal and county administration
Other: Private sector and public enterprises
Region: Following the business council number. grouping follows
current county and municipal lists

Classification of occupation

The occupational classification is in accordance with Standard Classification of Occupations (STYRK-08), which is based on ISCO 08 (COM).

Education classification

Education levels are obtained from the National Education Database (NUDB). The classification is by the length of education according to the Standard for Educational Classification. There are grouped by length of education in accordance Norwegian Standard Classification of Education (C617).

From 2011 it is in NUDB including results from survey on education completed abroad. This survey led to the proportion unknown in BHU was reduced from about 43 percent to 20 percent.

More information about the Standard Education Classification can be found at http://www.ssb.no/english/subjects/04/90/


Administrative information

Name and topic

Name: Earnings of all employees
Topic: Labour market and earnings

Next release

Responsible division

Division for Income and Wage Statistics

Regional level

County and the whole country.

Frequency and timeliness

Annual with September as reference month.

The statistics are published in February the following year.

International reporting

Reporting to Eurostat every 4 years acc. Council Regulation (EC) no. 530/1999 of 9 March 1999. Reporting is performed within 18 months after the end of the census year.


Raw data files with wage data put through link and estimation programs are stored.


Background and purpose

The purpose of the statistics is to provide an overview of wage levels and wage changes for all employees irrespective of industry or working hours.

The purpose of the statistics is to provide an overview of wage levels and wage changes for all employees independent of industry or working hours. The statistics were established in 1997 based on sample sirveys in the private sector and from registers in the public sector.

The time series for earnings of all employees has two breaks in 2008 and 2015.

1997-2008: The wage statistics were based on an older Standard Industrial Classification (SN2002)

2008-2015:  In 2009 Statistics Norway introduced a new version of the Norwegian industry classification (SN2007). The wage statistics in 2008 were revised according to the new version of the Norwegian industry classification.

In 2015 the wage statistics were based on a new data source A-ordningen, but for in order to mage them comparab  with the wage statistics in 2014 wage statistics they were based on a sample of enterprises.

From 2015 the wage statistics will be based on a census and on a common reporting system known as A-ordningen. In 2015 this reporting was coordinated with the reporting of earnings and personnel data to the Tax Administration and Statistics Norway.

You can find more information about the new reporting at www.altinn.no/en/a-ordningen.

There is also a break in the time series related to the occupation information in the new series being based on a New occupation standard in according with the Standard Classification of Occupations-08 (STYRK-08). Employers have reported those employed according to the former occupation standard STYRK-98. Statistics Norway has subsequently converted from the previous to the current standard.

You can find more information about the break under "Production".

Users and applications

Major users are the Technical Reporting Committee on the Income Settlements, research and official studies institutes, employee and employer organisations, Eurostat, the media, trade and the business sector and private persons. The statistics are used in Statistics Norway’s Labour Accounts and in quarterly wage indices.

Equal treatment of users

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 inthe Statistics Release Calendar. This is one of Statistics Norway’s key principles for ensuring that all users are treated equally.

Coherence with other statistics

The annual wage statistics and the quarterly wage statistics are
closely related, and are based on the same data source. Register based employment statistics
also use the same data from A-ordningen.

See https://www.ssb.no/arbeid-og-lonn/statistikker/regsys/aar  

Legal authority

Statistics Act Sections §  3-2 (Administrative registers).

EEA reference

Council Regulation (EC) no. 530/1999 of 9 March 1999 Concerning Structural Statistics for Wages and Labour Costs.

Commission Regulation (EC) no 1738/2005 of 21 October 2005 and no 698/2006 of 5. May 2006 and

no.698/2006 of 5 May 2006.



The wage statistics in Statistics Norway are built around the European regulations for measuring wages, in addition to protecting national needs related to factors such as wage negotiations. 

The main objective of wage statistics is primarily to describe wage changes for characteristics that are not directly related to the individual, but to the characteristics individuals bring to the labor market and that are linked to the employment.

The reporting unit in the wage statistics is enterprises.
The population of employees is collected from enterprises in all industry sections except paid housework and international bodies and organisations in accordance with the Standard for Industrial Classification (SN2007).

Each enterprise comprises one or more businesses, which are grouped by industry association. The analysis unit in the statistics is employee per business. An employee (individual) can have more than one job in different businesses, whilst employment within the same business is aggregated into one.The employment figure will therefore exceed the number of employees (individuals) in the population.

The population in the wage statistics is closely related to who actually receives wages in a given period. What qualifies as a wage is a determining factor for understanding the population.The definition of wages is remuneration for work performed, and differs from, for example, the national accounts and wage totals statistics.

The statistics do not include fringe benefits, insurance, tax-free expenditure allowances or such like. Remuneration also includes amounts paid for the job/position to which they belong. It follows that remuneration for directors' fees, fees for other boards/committees and functioning well.

Beyond this, there is no limit related to the characteristics of the employee (working hours, main job/ part-time position, resident/non-resident, age, occupation, temporary or similar). The self-employed are not included.

 The population is defined using the variables available in the A-ordningen, and the principles are as follows:

  1. Employees working in the reference week in the reference month (calculated as employed)

  2. In addition, they must have received a fixed salary or hourly wage during the reference month

Reference Week is the week that contains the 16th, which is the 3. week in September.

Practical challenges are largely related to determining what kind of wage payment the employee has received in the reference month, and evaluating the salary in relation to information about the employment.

Data sources and sampling

 As from 2015, the wage statistics will be based on a full census from the new A-ordningen (https://www.altinn.no/a-ordningen/). A-ordningen is a coordinated reporting of wage and employment information to the Tax Administration, NAV and Statistics Norway.

Data is collected electronically from the Tax Administration Shared Services Agency (Etatenes fellesforvaltning, EFF).

All employers who have paid wages, cash benefits or fringe benefits must submit an A-ordningen report each month. The data thus covers all employees in all enterprises covered by the wage statistics.

Up to the end of 2014, the data was collected electronically from a sample of businesses in the private sector and from registers in the public sector.

Collection of data, editing and estimations

As from 2015, the wage statistics will be based on data reported in the A-ordningen. Statistics Norway receives data monthly from Tax Administration Shared Services Agency (Etatenes fellesforvaltning, EFF). which administers A-ordningen on behalf of  Tax Administration, Norwegian Labour and Welfare Administration (NAV) and Statistics Norway.

Information collected includes monthly earnings, basic salaries, bonuses and payment for overtime work.

Various controls are undertaken:

  • Business rules in the receipt of data from the Tax Administration Shared Services Agency (Etatenes fellesforvaltning, EFF).
  • In Statistics Norway’s production system for wages and employment

 Business rule controls in the receipt of data from EFF:

A number of rules of business (controls) are being run to uncover errors/omissions in the submitted information, after a-meldingen is received by EFF.errors/omissions in the submitted information. Small to medium-sized legal entities with a declaration obligation receive feedback almost instantly (within a minute), while larger legal entities have to wait slightly longer. The feedback from EFF includes all discrepancies identified, indicating where in the submitted information the discrepancies appear and what business rule has been breached

Business rules and errors that can occur are documented at the homepages of A-ordningen:


 Controls in Statistics Norway's Production system:

A number of controls and automatic measures are performed during the production. The purpose is to safeguard the quality of the data for statistical purposes. We distinguish between three types of Controls:

 a)       Automatic controls and measures

b)      Reports (monitoring)

c)       Manual controls

In addition to this, controls and checks are being carried out throughout the year, regardless of publication.

Controls aimed at uncovering errors and omissions that should be corrected are mostly related to employment. Many of the controls are designed to identify errors and missing values in reported hours in full-time and part-time positions, combined with other identifiers such as type of employment, working time arrangements and payment arrangements, including:

  • The number of hours, full time, is missing.
  • The number of hours, full time, likely to be incorrectly reported
  • The number of hours, full time, deviates from the reported working time arrangements
  • The number of hours, full time, is extremely high or low
  • The percentage of the position is missing

Many cases of registered employment are removed (not considered active) during production because no wage is registered for that case in the reference month. This could apply to seasonal workers who have not performed any work in the reference month (and therefore not been paid), and where no employment termination date has been reported (incorrectly), or in cases where individuals have mistakenly been reported with active employment (e.g. temporary staff who have not worked during the given period).

The controlling and editing of wage statistics take place in several stages, and most operations are automated with respect to both the control and the subsequent correction.

Upon receipt of data from A-ordningen, a number of key variables are controlled, both at micro and macro levels.

Obvious errors and omissions in the reporting trigger the imputation of values ​​using statistical methods. The scope of this is about 5% of the total employment. Imputation may be from an earlier period, or from similar (comparable) employment.

Wage statistics do not take into account the outcome of wage negotiations, but measure the change in wages as they have been paid at the time of Reporting.

Structural changes in industry have an impact on the statistics. How many and which groups of employees that enter or leave the labour market, how many people change their working hours and how many people change jobs between industries will all affect the wage Development.

Seasonal adjustment

Not relevant


According to Statistics Act Section 2-6, figures shall not be published in such a way that they may be traced to a particular respondent.

Comparability over time and space

The statistics in the current form were produced for the first time in 2003, and are comparable from 1997.

There are two breaks in the time series in the wage statistics for all employees in 2009 and 2015.

1997-2008: The wage statistics were based on the old Standard Industrial Classification (SN2002) and are located as terminated series in StatBank.


In 2009, a new Norwegian Standard Industrial Classification (SN2007) was adopted. The figures for 2008 were converted in line with the new standard. The 2015 figures were based on information from the A-ordningen, but in order to make them comparable with 2014 figures were compiled on the basis of a sample of enterprises.

2015-: From 2015, the statistics are based on a census from the A-ordningen. New time series were therefore also established in StatBank, with 2015 as the start year.

There is also a break in the series related to the fact that occupational information in the new series is based on a new profession standard according to the Standard Classification of Occupations-08 (STYRK-08). Employers have reported those employed according to the former vocational standard STYRK-98. Statistics Norway has subsequently made a conversion, a change, from the prior to the current standard.

The content of the wage terms the same in all years of the statistics

Accuracy and reliability

Sources of error and uncertainty

The increasing use of electronic reporting of wage statistics in recent years has helped to reduce the number of reporting errors (see 3.1).

Measurement errors

Measurement errors will be related to differences in the definitions of the wage components in the original wage statistics.

Processing errors

The possibility of processing errors occurring is connected to the use of the data material from the original wage statistics. The data material is primarily collected to establish wage statistics for the respective industries (see 3.2).


None. Non-response in the individual wage statistics is between 2.5 and 5 per cent. This may have some influence on the statistics.

Partial non-response

None. But non-response in the original data material may be of importance.

Non-response in several of the items collected by form and used in the wage statistics can normally be logically calculated on the basis of other information given on the form or imputed from earlier years.

Sampling errors are errors that may arise in areas subject to sampling. Only the statistics for central government, municipalities and publicly maintained schools are based on censuses.

Observations may also be rejected on the basis of insufficient information and / or incorrect values. By obvious error reporting will be imputed using statistical methods.

Registry errors can occur in connection to the Business and Enterprise Register (VOF). Error in registry for information about the industry and / or sector may cause the businesses to be positioned incorrectly. Errors or distortions in the registration in the National Education Database (NUDB) will also lead to errors in the statistics.

Beginning with 2015, data underlying the statistics based on information from A-ordningen. Observations can also here be rejected on the basis of insufficient information and / or incorrect values in variables.


All sample-based surveys will be burdened with a certain uncertainty. Generally, the results are less certain the fewer the observations they are based on. Uncertainty also depends on wage dispersion and rate of coverage for the various variables in the population from which the sample is drawn.


This statistics has no sample bias of its own. However, the respective statistics this statistics are based on may be the subjects of sample bias, which arise when the distribution on some variables in different parts of the sample is not the same as the corresponding distribution in the population.

Sample bias in the individual statistics will be of less importance for this statistics due to the considerable quantity of data it is based on.

Frame errors

Incorrect industry codes and/or employment data in The central register of Establishments and Enterprises (CRE) during the selection of the sample may result in the establishments being placed in the wrong industry or selection stratum. Incorrect registrations in the register of the Population’s Highest Level of Education may also cause errors in the statistics.

Model assumption errors

The wage statistics for all employees are based on a re-weighting of several wage statistics and the underlying assumptions for this weighting are a source of model error. To be considered is how appropriate the employment figures from national accounts are for this purpose and the quality and demands that these figures rely on. One model assumption is that the sample from the respective wage statistics reflects the distribution of full-time and part-time employees in the population.


Not relevant


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