Statistics Norway

Division for Social Welfare Statistics

PO BOX 2633 St. Hanshaugen, NO_0131 Oslo, Noway

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

HY050:Includes the following components: child allowance, maternity benefits (daily cash benefit for working mothers and lump sum benefit for non-working mothers), cash-for-care benefit, child support for singe parents (education and childcare) and transitional benefit to single parents. Deviation from the SILC concept:The current register data covers only roughly 50% of the total amount paid out in daily cash maternity benefit. The remaining amount is included in PY010 (Gross employee cash or near cash income).

HY070:Includes dwelling support in cash received by renters and owner-occupiers.Deviation from the SILC concept:The benefit from renting a subsidised dwelling is not included in the income concept.

HY080:Includes alimonies and paid maintenance from former spouse (or advance payment from the government). Information on regular private cash support received by children living in separate households (e.g. students) is collected from the interview.

HY120: Included in HY140: Total tax on income.

PY010: Defined as the sum of all wages and salaries including overtime, holiday pay, tips and bonuses. Deviations from the SILC concept: payments to foster parents (included in wages, cannot be separated from wages), severance and termination pay (included in wages, cannot be separated from wages) and sickness benefits that are not directly paid out to the employee (i.e. compensation from the Social Security Scheme to the employer). With the exception of sickness benefits these deviations are expected to be of a minor importance.

PY030: Defined as paid in employers' national insurance contribution per person. Deviation from the SILC concept: Because of the allowance scheme which is per company (and every company has employees in the various zones and age groups) it is virtually impossible to calculate the payroll tax directly per person. Therefore, the calculation is done by companies where we have taken into account the allowance scheme, zones, age, sector and individual exceptions industries.

PY050: Entrepreneurial income is collected net in register data. Gross cash losses thus appear as negative amounts. Deviation from the SILC concept:It has not been possible to identify – and thus deduct from self-employment income – interest paid on business loans.

PY070: The tax-assessed benefit from consuming own goods (estimated by the tax authorities) is included in gross cash income from self-employment (PY050). The variable PY070 is not included in Norwegian data because the value of own goods for own consumption is assumed to be ignorable. Data from the Norwegian HBS in 2006 shows that consumption of own goods is estimated to be only 0,13 percent of the total consumption in the households. In total, the value of own goods for own consumption is less than 400 NKr (appr 50 euro) on average per household.

PY090: Deviation from the SILC concept: No information available on benefits (in-kind) related to vocational training.

PY100: Include old-age pension from the social security system and occupational pensions. Deviation from the SILC concept: It was not possible to split the different types of occupational pensions into different functions, e.g. old-age, disability or survivor’s pension. In stead all types of occupational pensions have been included under the old-age function.

PY110: Includes survivor’s pension from the National Insurance Scheme. In addition several minor income items have been included that are received mainly by survivors, e.g. tax-free wage income and holiday pay earned by the deceased. Deviation from the SILC concept: Not possible to include funeral grants in the income concept. This benefit is transferred directly to the firm of undertakers.

PY120:Includes sickness benefits paid by the National Insurance Scheme directly to the employee (i.e. after day 16 of sickness). Deviation from the SILC concept: The current register data covers only roughly 50% of the total amount paid out in daily cash sickness benefit. The remaining amount (compensation to the employer) is included in PY010 (Gross employee cash or near cash income).

PY130: Include disability pension from the National Insurance Scheme, basic and attendance benefit and rehabilitation benefits. Deviation from the SILC concept: Early retirement benefit is included in occupational pension, i.e. old-age function.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

Detailed information concerning sampling frame, sampling design, sampling units, sampling size, weightings and mode of data collection can be found in this section. Such information is mainly used for the computation of the accuracy measures.

The sampling frame is a copy of the central population register called BEREG. This register i daily updated with information from local population register offices.

The sample units are persons aged 16 years or more registered in the central population register (inhabitants).

Concerning the SILC instrument, three different sample size definitions can be applied:

- the actual sample size which is the number of sampling units selected in the sample

- the achieved sample size which is the number of observed sampling units (household or individual) with an accepted interview

- the effective sample size which is defined as the achieved sample size divided by the design effect with regards to the at-risk-of poverty rate indicator

Given that the effective sample size has been already treated in the section dealing with sampling errors, in this section the attention focuses mainly on the achieved sample size.

Sample size and allocation criteria

The selected sample size set to meet demands for minimum effective sample size of both the cross-sectional and the longitudinal survey over time is 8 500 persons at the start of the EU-SILC project in 2003, each representing one separate household.

In 2003 8 500 persons constituted a proportion p ≈ 0,0024 of the total population (inhabitants aged 16 years or more). This proportion is meant to be identical each year of the survey, and thus the size of the gross sample will change according to changes in the population.

In 2012 we redesigned our sample design, aiming to go from a 8 year panel to a 4 year panel. The following 3 years were a transitional period where the rotational groups had uneven sizes. In 2017 the sample consisted of 4 even rotational groups. 

The 2018 sample consists of 11 716 persons 16 years and over. During the field period, 323 of these proved to be non-eligible (either dead, living in an institution or emigrated), thus giving a gross sample of 11 393 persons. We succeeded in interviewing 5 981 of these (net sample), a response rate of 52.5 percent. 

In all households interviewed there were 11 633 persons aged 16 years or more. The minimum sample size set by Eurostat for the cross sectional components was 3 750 households and 6 250 persons. The effective sample size is: Net sample / design effect for equivalent income. The design effect for equivalent income is estimated to be 1.039. In the Norwegian 2018 survey this gives an achieved effective sample size of 6 420 households and 12 518 persons.

Data collection is conducted once a year, during the first 4-6 month of the year.

Renewal of sample: Rotational groups 

Up until 2012 each selected respondent (sample unit) was part of the sample in eight years, in the Norwegian design. Each year 1/8 of the sample was replaced.

In 2012, we changed the sampling design from eight years to a four-year panel, and as a result of this change to the sample size increases.

Each year one group rotates out and a new rotation group being retracted. The sample is drawn as a random sample in one step. The number of new to be deducted each year is calculated on the total gross sample - the remaining three quarters of the sample .

In the transition between the old sampling plan and the new (2012-2014) the total sample consisted of rotating groups of different sizes. In 20167 the sample had four rotational groups of equal size.

For the total sample shall preserve its cross sectional characteristic from year to year, the sample must also be supplemented. 16 -year-olds are drawn each year so that the number of 16 year olds in the sample corresponds to the proportion p of the population. The same applies to the recently immigrated. The supplemented into the sample will not be in the sample for four consecutive years, but from one to three years.

New entries in 2017 are coded with DB075 = 1

Mode of data collection

A description of the mode of data collection used in your country. Please mention if you use mixed mode of data collection.

The mean interview duration

The mean interview duration per household is calculated as the sum of the duration of all household interviews plus the sum of the duration of all personal interviews, divided by the number of household questionnaires completed. Only households accepted for the database have to be considered.

Average interview duration = 36 min

Sample distribution over time

To make the data collection effective, and to ensure a highest possible response rate among the new respondents in the sample, the sample was divided into four periodical groups with different start of the interviewing but similar end of interviewing.

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 See annex Estimation and inputation for the Norwegian details

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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The concept of accuracy refers to the precision of estimates computed from a sample rather than from the entire population. Accuracy depends on sample size, sampling design effects and structure of the population under study. In addition to that, sampling errors and non sampling errors need to be taken into account. Sampling error refers to the variability that occurs at random because of the use of a sample rather than a census and non-sampling errors are errors that occur in all phases of the data collection and production process.

* please report only the number of x months

EU-SILC is a complex survey involving different sampling design in different countries. In order to harmonize and make sampling errors comparable among countries, Eurostat (with the substantial methodological support of Net-SILC2) has chosen to apply the "linearization" technique coupled with the “ultimate cluster” approach for variance estimation.

Linearization is a technique based on the use of linear approximation to reduce non-linear statistics to a linear form, justified by asymptotic properties of the estimator. This technique can encompass a wide variety of indicators, including EU-SILC indicators. The "ultimate cluster" approach is a simplification consisting in calculating the variance taking into account only variation among Primary Sampling Unit (PSU) totals. This method requires first stage sampling fractions to be small which is nearly always the case. This method allows a great flexibility and simplifies the calculations of variances. It can also be generalized to calculate variance of the differences of one year to another .

The main hypothesis on which the calculations are based is that the "at risk of poverty" threshold is fixed. According to the characteristics and availability of data for different countries we have used different variables to specify strata and cluster information. In particular, countries have been split into 3 groups:

1) BE, BG, CZ, IE, EL, ES, FR, IT, LV, HU, NL, PL, PT, RO, SI, UK and HR whose sampling design could be assimilated to a two-stage stratified type we used DB050 (primary strata) for strata specification and DB060 (Primary Sampling Unit) for cluster specification;

2) DK, DE, EE, CY, LT, LU, AT, SK, FI, CH whose sampling design could be assimilated to a one stage stratified type we used DB050 for strata specification and DB030 (household ID) for cluster specification;

3) MT, SE, IS, NO, whose sampling design could be assimilated to a simple random sampling, we used DB030 for cluster specification and no strata.

Non-sampling errors are basically of 4 types:

• Coverage errors: errors due to divergences existing between the target population and the sampling frame.
• Measurement errors: errors that occur at the time of data collection. There are a number of sources for these errors such as the survey instrument, the information system, the interviewer and the mode of collection
• Processing errors: errors in post-data-collection processes such as data entry, keying, editing and weighting
• Non-response errors: errors due to an unsuccessful attempt to obtain the desired information from an eligible unit. Two main types of non-response errors are considered:

1. – Unit non-response: refers to absence of information of the whole units (households and/or persons) selected into the sample

1. – Item non-response: refers to the situation where a sample unit has been successfully enumerated, but not all required information has been obtained

Coverage errors include over-coverage, under-coverage and misclassification:

• Over-coverage: relates either to wrongly classified units that are in fact out of scope, or to units that do not exist in practice
• Under-coverage: refers to units not included in the sampling frame
• Misclassification: refers to incorrect classification of units that belong to the target population

The sampling frame is a copy of the central population register called BEREG. This register is daily updated with information from local population register offices.

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Non-response errors are errors due to an unsuccessful attempt to obtain the desired information from an eligible unit. Two main types of non-response errors are considered:

1) Unit non-response which refers to the absence of information of the whole units (households and/or persons) selected into the sample. According the Commission Regulation 28/2004:

• Household non-response rates (NRh) is computed as follows:

NRh=(1-(Ra * Rh)) * 100

Where Ra is the address contact rate defined as:

Ra= Number of address successfully contacted/Number of valid addresses selected

and Rh is the proportion of complete household interviews accepted for the database

Rh=Number of household interviews completed and accepted for database/Number of eligible households at contacted addresses

• Individual non-response rates (NRp) will be computed as follows:

NRp=(1-(Rp)) * 100

Where Rp is the proportion of complete personal interviews within the households accepted for the database

Rp= Number of personal interview completed/Number of eligible individuals in the households whose interviews were completed and accepted for the database

• Overall individual non-response rates (*NRp) will be computed as follows:

*NRp=(1-(Ra * Rh * Rp)) * 100

For those Members States where a sample of persons rather than a sample of households (addresses) was selected, the individual non-response rates will be calculated for ‘the selected respondent’, for all individuals aged 16 years or older and for the non-selected respondent.

2) Item non-response which refers to the situation where a sample unit has been successfully enumerated, but not all the required information has been obtained.

* All the formulas are defined in the Commission Regulation 28/2004, Annex II

A* = Total sample; B = * New sub-sample

The computation of item non-response is essential to fulfil the precision requirements concerning publication as stated in the Commission Regulation No 1982/2003. Item non-response rate is provided for the main income variables both at household and personal level. See annex Item non response for the numbers

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According to the Regulation (EC) No 1177/2003 of the European Parliament and of the Council concerning EU-SILC: "Comparability of data between Member States shall be a fundamental objective and shall be pursued through the development of methodological studies from the outset of EU-SILC data collection, carried out in close collaboration between the Member States and Eurostat".

Although the best way for keeping the comparability of data is to apply the same methods and definitions of variables, small departures of the definitions given by Eurostat are allowed in EU-SILC. In this way, the mentioned Regulation in its article 16th says: "Small departures from common definitions, such as those relating to private household definition and income reference period, shall be allowed, provided they affect comparability only marginally. The impact of comparability shall be reported in the quality reports."

The coherence of two or more statistical outputs refers to the degree to which the statistical processes, by which they were generated, used the same concepts and harmonised methods. A comparison with external sources for all income target variables and the number of persons who receive income from each ‘income component’ will be provided, where the Member States concerned consider such external data to be sufficiently reliable.

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In 2003, it was conducted an analysis in which one compared SILC data with the national income registry. For 2003 there are only minor differences in the amount of total income and disposable (after-tax) income based on national definitions and the corresponding figures based on SILC definitions. As is shown in table 1, the difference amounted to about 5 billion NOK (or ca 0.5 per cent) for both income concepts.  

The main explanation for the difference between the two income definitions is that the national definition comprises some income items that are not part of the SILC income definition. This is for example the case for certain fringe benefits other than company cars (e.g. free newspapers and telephone, low-interest loans, private insurance paid by employers etc.). I addition the SILC definition does not include capital gains, while this is the case in the national definition. In 2003 this income item amounted to a negative value of roughly 2 billion NOK in Norway. Finally, the national definition includes payments from a private pension scheme. Although this item is collected in SILC (PY080G), it is not included in the definition of income.

Table 1 Total gross income and disposable income. Billion NOK. 2003

¹ In the national definition this income concept refers to 'After-tax income'. 

In addition there are differences between national practice and SILC in income definitions at the component level, although these differences have almost no impact on total gross income and disposable income. In the definition of employee income (wages and salaries) the national definition for example includes sickness benefit and maternity allowance, while in the SILC definition these components are considered part of transfers. For self-employment income sickness benefit is again included in the national definition, but not in the SILC definition (transfer). In addition several types of pensions are specified in the SILC income concept (e.g. old-age pension, disability pension and survivor’s pension), while in the national definition these programmes are all part of ‘Social security benefits’.  

Table 2 Comparison of income components. The national definition and EU-SILC. Billion NOK. 2003

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National questionnaire is available in Circa BC at: https://circabc.europa.eu/

Please select EU SILC section and then select the folder called  “06 National Questionnaire” in the library list.