Income and consumption

Households' income, distribution of income2012

The statistics is published with Income and wealth statistics for households.


About the statistics


Name and topic

Name: Households' income, distribution of income
Topic: Income and consumption

Responsible division

Division for Income and Wage Statistics

Definitions of the main concepts and variables

After-tax income is calulated as the sum of wages and salaries, income from self-employment, property income and transfers received minus total assessed taxes and negative transfers.

Income from work is the sum of employee income and net income from self-employment during the calendar year.

Property income is the sum of interest received, share dividends received, realised capital gains (or losses) and other income received during the calendar year.

Taxable transfers is the sum of pensions and benefits from the social security scheme, service pension, unemployment benefits and some minor taxable benefits.

Tax-free transfers consist of child allowance, dwelling support, student grants, social assistance, basic and attendance benefit and more.

Consumption unit
Income calculated per consumption unit can be used to compare households of different sizes and structures with each other. There are several different ways of calculating consumption units. In the income statistics we have used the 'modified' OECD scale (EU scale), where

the first adult of the household receives the weight 1
other adults receive the weight 0.5
children receive the weight 0.3.

 A household is regarded as all persons who live permanently in the same dwelling and having common housekeeping. The statistics include only persons in private households.

The main income earner is the person in the household who has the highest gross income of the income earners in the household. In those cases where there is no income earner in the household, the oldest person is the main income earner.


Standard classifications

Types of household are in conformance with standard classifications. 

Socio-economic standard

A person is economically active if his or her income from business activities and income from employment is greater than the minimum benefit from the National Insurance Scheme paid to old age and disabled pensioners.

The economically active population is divided into self-employed and employees. If income from self-employment is greater than income from employment, the person is classified as self-employed, and vice versa.

We have the following socio-economic groups:



Self-employed in agriculture, forestry and fishing

Self-employed in other industries.



Pensioners and National Insurance recipients

Other non-working

Administrative information

Regional level

National level, counties and municipalities.

Frequency and timeliness

Annually. During last quarter one year after the current income year.

International reporting

Income data is used in Eurostat's structural indicators on low income and income distribution. Micro data for selected years are also included in the database Luxembourg Income Study (LIS). Income data is also included in the Nordic publication "Social security in the Nordic countries" by the Nordic social committee, and in reports published by the OECD.


A full survey of Statistics Norway's income statistics is available under subject 05.01 at Statistics Norway's website.

Data files with individual income data that have gone through the linkage and statistics files are stored.


Background and purpose

The purpose of the statistics is to present income measurements as living standard indicators and data that measure the economic resources households have for saving and consumption. Additionally, the statistics presents general income trends and income distribution among different types of households.

The Income Distribution Survey was conducted annually from 1986 to 2004 based on a representative sample survey. Information on the household composition was collected from various Living Condition Surveys and Household Budget Surveys. Up until 1992, the income data was obtained in the form of paper forms from the local tax offices. In addition, tax-free transfers were obtained electronically from other government agencies. Beginning with the survey for the 1993 income year, it was possible to obtain all income data from the personal tax return in electronic form. From 2005 we have also established household composition by using registers. This means that we are now able to produce a totally register-based household income statistics.

Users and applications

The main users are the Ministry of Finance, Ministry of Labour and Social Inclusion, Ministry of Children and Equality, Directorate for Health and Social Affairs, and research institutes in the areas of household economics, tax research and living conditions in general.

The tax model LOTTE is updated annually with data from the Income and Property Survey for households.

Coherence with other statistics

Data from the household income statistics are also used to construct Income indicators. http://www.ssb.no/english/subjects/05/01/inntind_en/

Data from the Tax Return is the basis for all of Statistics Norway's statistics on income for persons. The tax return statistics include data on types of taxable income, and is obtained for all persons residing in the country. The statistics was first available for the year 1993.

Legal authority

Statistics Act §§ 2-1 and 3-2.

EEA reference




All persons residing in Norway and resident in private households as of 31st December of the current income year.

Data sources and sampling

Income data are received by linking different administrative registers and statistical data sources for the whole population as of 31st of December of the income year. Income and biographical data are collected from the following sources:

Data from tax returns (wages and salaries, entrepreneurial income, pensions etc.)

The Tax Register (taxes)

End of the Year Certificate Register (unemployment benefit, various tax-free transfers)

Norwegian Labour and Welfare Organisation (family allowances, basic and additional amounts, cash benefit etc.)

Ministry of Labour and Social Inclusion (social assistance)

State Educational Loan Fund (loans to students, scholarships)

State Housing Bank (dwelling support)

Education statistics from Statistics Norway (highest level of completed education etc.)

Family statistics from Statistics Norway (family type etc.)

FD-Trygd, Statistics Norway's event database (maternity benefit and sickness benefit)

Collection of data, editing and estimations

Data are collected from various administrative registers. 

Consistency controls are undertaken by comparing information from different sources.

The population of the Income Distribution Survey (1986-2004) was weighted by the use of a calibration program. This method of estimation permits the population to show the same aggregates familiar from the register statistics (for the population) for selected variables. This applies to the different personal incomes and net wealth.

The totally register-based income statistics as of 2004 is a total census. Households are derived at after performing certain adjustments to the formal households (formal adress according to the Central Population Register). These adjustments include omitting people living in institutions and removing students, that no longer reside with their parents, into single person households. Surveys suggest that less than 10 per cent of the students in Norway actually live at home. In addition, other administrative sources are used to identify more cohabitating couples that belong to the same household.


The use of collected data will be in accordance with the standards of the Statistics Act. The information are kept in a responsible way.

Comparability over time and space

The Income Distribution Survey has gone through several significant changes up through the years. This is due in part to changes in the analysis unit (1982) and in part to changes in the income concept as a result of changes in the tax system and access to new income components from registers.

Accuracy and reliability

Sources of error and uncertainty

Data from the Tax Returns may contain errors made by the individual taxpayer that fills out the form. A number of the errors are discovered and corrected by the Tax Offices. Errors that do not have any practical significance for the Tax Return are often not corrected by the Tax Offices, causing discrepancies in the material. In particular, small amounts under the tax-free limit are frequently left uncorrected even though they are not filled out properly.

Some data collection and processing errors are unavoidable. These include coding errors, revision errors, data processing errors, etc. Comprehensive efforts have been made to minimize these errors, and we regard these types of errors to be relatively insignificant.

From and including the income year 2005, this statistics is a total census and will not be affected by variance and bias. For previous years with survey based statistics the following is of relevance:

All sample surveys are subject to a certain amount of uncertainty. In general; the fewer observations the more uncertain the results. Results based on less than 20 observations are therefore not published.

Groups based on relatively few observations will be very strongly influenced by extreme observations, i.e. observations that deviate greatly from the average. In this statistics, extreme observations in most cases are included, but an attempt has been made to reduce the effect of such observations by adjustments (reduction) of the household weights.

Bias can occur when the distribution between certain groups in the population is not the same as the corresponding distribution in the total population. Sample bias of this type can occur through non-response. Most of the data for the Income Distribution Survey was obtained from administrative registers. Non-response is not a problem for this part of the material. The household composition was based on interviews, where there will always be non-response. Non-response is adjusted by replacing household data with data on family composition from registers.