Dataset: Generations and Gender Survey Norway Wave 1


The Generations and Gender Survey (GGS) provides micro-level data with the aim of significantly improving the knowledge base for social science and policymaking in Europe and developed countries elsewhere.  
In Europe 2020, the European Union develops a strategy "to help us come out stronger from the crisis and turn the EU into a smart, sustainable and inclusive economy delivering high levels of employment, productivity and social cohesion". The economic crisis affects not only day-to-day decisions, but also fundamental choices at all stages of people's lives:  marriage and childbearing, the combination of employment and caring responsibilities for the young and the old, retirement, housing, and ageing well. The GGS has been developed to provide scientists with high-quality data to contribute scientifically grounded answers to these key policy questions. Survey content focuses on intergenerational and gender relations between people, expressed in care arrangements and the organization of paid and unpaid work. Key feature of the survey are:  
- Cross-national comparability. In each country data is collected on the basis of a common international questionnaire and guidelines about the methodology. Data processing includes central harmonization of national datasets.  
- A broad age range. It includes respondents between the ages of 18 and 80.
- A longitudinal design. It has a panel design, collecting information on the same persons at three-year intervals.  
- A large sample size. It has an average of 9,000 respondents per country at Wave 1.
- A theory-driven and multidisciplinary questionnaire. It provides data for policy relevant research by demographers, economists, sociologists, social policy researchers, social psychologists and epidemiologists. The questionnaire is inspired by the theory of planned behavior.
- Possibility to combine the survey data with macro data provided by the GGP Contextual Database. This combination enables analyses of individuals and families in their cultural, economic, political, social and policy contexts.

Variable Groups

Document Description

Full Title

Generations and Gender Survey Norway Wave 1

Alternative Title

GGS Norway Wave 1

Identification Number


Date of Distribution



Working Version: GGS Wave 1 Version 4.3.

Update of variable catagories and documentation with the release of Sweden Wave 1 Version 4.3.1

Date: 2017-12-22

Guide To Codebook

In the field “Study Description”, users can find metadata about surveys. This includes the distributors, keywords, abstract, and guidelines on the bibliographic citation.  
Country specific metadata include information on survey producers, methodology and processing. This information was provided by the GGP-country teams, based on a metadata grid with pre-structured questions. Links to relevant references (e.g., working papers and questionnaires) are also provided.  

The field “Data Files Description” provides metadata about the data file, such as file contents, missing values, as well as changes across different GGS versions.

The field "Variable Description" provides information on each variable, such as question text, descriptions of country specific categories and variables, universe (i.e., subset of respondents to whom the question was asked), country specific deviations to GGS routing, descriptions of the ways in which consolidated and derived variables are calculated. Variables are ordered according to the sections of the GGS codebook.

This is the reason why the total no. of variables in the documentation is smaller than the total number of variables in the SPSS and STATA files.

Full Title



Name Affiliation Abbreviation Role
Arianna Caporali Institut national d'études démographiques (INED) AC

Study Description

Full Title

Generations and Gender Survey Norway Wave 1

Alternative Title

GGS Norway Wave 1

Identification Number


Authoring Entity

Name Affiliation
Trude Lappegård Statistics Norway

Other identifications and acknowledgments

Name Affiliation Role
Statistics Norway Surveys department Statistics Norway Tracking, data cleaning, weighting


Name Affiliation Abbreviation Role
Trude Lappegård Statistics Norway Senior researcher

Funding Agency/Sponsor

Name Abbreviation Role Grant
Norges forskingsråd (Norwegian research council) NFR 168373/S20
Barne- og familiedepartementet (Ministry of Children and Family Affairs) BFD 168373/S20
Arbeidsdepartementet (Ministry of work issues) AD 168373/S20
Helse- og omsorgsdepartementet (Ministry of health issues) HOD 168373/S20
Kommunal- og regionaldepartementet (Ministry of regional issues) KRD 168373/S20
Statistisk sentralbyrå (Statistics Norway) SSB 168373/S20
Norsk institutt for forskning om oppvekst, velferd og aldring (Norwegian Social Research) NOVA 168373/S20

Data Distributor

Name Affiliation Abbreviation
Institut national des études démographiques - 133 boulevard Davout 75980 Paris Cedex 20, France. INED
Netherlands Interdisciplinary Demographic Institute - Lange Houtstraat 19, NL-2511 CV The Hague, The Netherlands NIDI


Name Affiliation Abbreviation
Statistics Norway

Bibliographic Citation

United Nations 2005. Generations & Gender Programme: Survey Instruments. New York and Geneva: UN, 2005.

List of Keywords

Date of Collection

Start End Cycle
2007-01-08 2008-09-15


Norway  (NOR)

Geographic Coverage

Country representative.

Geographic Unit

Nuts 2.

Unit of Analysis



Norwegian speaking persons aged 18-79 on December 31st 2006 living in private households in Norway, with an available phone number.

Kind of Data

Survey data

Time Method


Data Collector

Sampling Procedure

1. Sampling frame
1.1 Type of frame: Population register.
1.2  Frame coverage: Registered population of Norway.
1.3 Frame size: Total registered population of Norway on December 31st 2006.
1.4 Level of units available: Individuals.

2. Sampling method
2.1 Sampling method type: Random probability sampling.
2.2 Sampling stage definition
  - PSU: Regions (nuts 2).
  - SSU: Centrality.
  - TSU: Sex  
  - FSU: Age
2.3 Sampling stage size
  - PSU: 7
  - SSU: 2
  - TSU: 2
  - FSU: 3
2.4 Unit selection: Random number generator from 78 strata.
2.5 Final stage unit selection: Simple Random Sampling.
2.6 Within Household unit selection: None.
2.7 Stratification: NA
2.8 Sample size
  - Starting size sample: 25,309.
  - Aimed total size at Wave 1: 11,995.
  - Aimed total size at Wave 3: 6,747.
2.9 Estimated Non-response
  - Initial non-response: 35%.
  - Yearly attrition: 25%.
  - Non response measures: NA.
  - Within household non-responses measures: None.

Mode of Data Collection

Method: Telephone interviews, self-administered postal interviews and use of register data.  
Technique: Web-assisted (CATI) for the telephone interview and Paper and Pencil (PAPI) for the self-administered postal.

Type of Research Instrument

Structured questionnaire in Norwegian.

Characteristics of Data Collection Situation

1. Interviewers
1.1 Total number of interviewers: 223.
1.2 Number of interviewers in the field: 1-223.
1.3 Network organization: Centralized.
1.4 Working arrangement of interviewers: Part-time.
1.5 Payment of interviewers: Per hour.

2. Interviewer training:  
2.1 General interviewing: Yes, general interview techniques, CATI and general knowledge on surveys carried out by Statistics Norway survey department.
2.2 Survey specific: Outline of the purpose of the study, the questionnaire, handling of sensitive questions and contact strategies.
2.3 Length: One day specific training for the interview. All recruited interviewers were experienced and trained interviewers of Statistics Norway survey department.
2.4 Control of performance: No.
2.5 Interviewer survey: No.

3. Contact protocols
3.1 Advance letter: Yes, each individual selected in the sample received an advanced letter introducing the survey and announcing the telephone call of an interviewer and the reason for his/her call, the survey subject, the agencies involved in the survey, the size of the survey. The letter included also information about the use of additional register data to facilitate the data collection and to reduce the interview time. The selected individuals were also invited to take contact if he/she had questions respective to the survey (free telephone number or by e-mail) or data privacy (contact information of the data protection officer). The letter included also a leaflet with information about the survey and two scale cards that could be used during the interview. Some of the information in the letter was adapted to the age of the selected individuals and if they were part of an earlier survey or not.
3.2 Cold contacts: Telephone.
3.3 Scheduling / scattering: Yes. To get the highest response rate, contact attempts were scattered over different days of the week and different parts of the day.
3.4 Contact history: Yes. For each contact attempt the interviewer had to report the date, the time and the outcome grid.
3.5 Min number of contacts: No.
2.6 Max number of contacts: No.

4. Questionnaire localization
4.1 Validation: No.
4.2 Pre-test: Two rounds with in-depth qualitative interviews (in total 19 interviews) using different parts of the questionnaire and different versions of the announcing letter were carried out in June and August 2006. A pilot of the telephone interview was carried out in December 2006 (150 respondents).
4.3 Length of interview: The average duration of interview was 43 minutes, with a large variance according to the composition of the household and the complexity of the family structure and history of the respondent.

Actions to Minimize Losses

1.  Dealing with nonresponse
1.1 Screening: No.
1.2 Refusal conversion: No special methods - usual techniques of refusal avoidance, i.e. specify that personal information will remain confidential, offer to call for changing the time of interview, insistence of the research purpose.
1.3 Incentives: Yes. Among those completing both the telephone interview and sending back the self-administered postal interview, 7 individuals were drawn to win a gift voucher amounting to 10,000 NOK (approximately 1,250 Euro).

2. Tracking of sampled units
2.1 Respondent contact information: No.
2.2 Other contact information: No.
2.3 Cards: No.
2.4 Additional surveys: For a part of the panel sample the GGS is the second round. 7,861 individuals aged 40 years or older in 2002, participated already in 2002/03 in the "Norwegian Live Course Ageing and Generation Study", a quantitative survey, based on computer assisted telephone interviews on topics as ageing, health, work and retirement, familiy relations in the second half of the life and well-being.
2.5 Administrative records: Yes, whole sample is based on administrative records.

Control operations

Automatically consistency checks through the CATI system during the interview.


A weighting variable (aweight_2001) at the respondent level was built to reduce any non-response bias. The sample has been weighted according to the net sample. The variables used in the weights are sex, age, geographical region, centrality and education. The largest bias is related to education: those with primary education are somewhat underrepresented in the Norwegian GGS (5.5% difference between gross and net sample), whereas persons with college or university education are somewhat overrepresented (6.5% difference between gross and net sample).
The other weighting variable (aweight) is a standardized weight based on country specific population weight and it is recommended for use.

Cleaning Operations

The datafile was checked and anonymized by Statistics Norway / NOVA before being sent to data harmonization.

Response Rate

Response rate - Final disposition codes:
I = complete interview: 15,114
P = partial interview: 42
NE = non-eligible: 479 respondents not interviewed due to death, emigration or institution, 264 respondents sorted out due to age limit (aged 80 years or older), 11 respondents sorted out due to anonymisation.
NC = non-contact: 2,186
R = refusal: 6,705
O = other non-response: 1,047
UC = unknown eligibility, contacted DK
UC = unknown eligibility, non-contact: DK
eC = estimated proportion of contacted cases of unknown eligibility that are eligible: DK
eN = estimated proportion of non-contacted cases of unknown eligibility that are eligible: DK

Completeness of Study Stored

The GGS core questionnaire was adapted to fit with the Norwegian context and because of time and budget constraints some questions were dropped of modified. Other questions - belonging to the second wave of the "Norwegian Life Course Ageing and Generation Study" - were added. The added questions are not part of the GGS harmonized data file.


In order to access micro data files, users have to sign and submit a Statement of affiliation, confidentiality and acceptable usage. They also have to submit a title and abstract of their research project. They can use the data for all their research projects, except for datasets from Australia, Belgium and Norway. Users of these datasets need to submit a new application form if they want to use the data in a different research project. The access rights from Wave 1 data are NOT transferred to the Wave 2 data. Wave 1 data users need to submit a new application form to gain access to Wave 2 datasets.

Access Authority

Name Affiliation E-mail address Universal Resource Identifier
UNECE Population Unit - Palais des Nations - CH-1211 Geneva 10 - Switzerland. Tel: +41 22 917 24 77 - fax: +41 22 917 01 07

Citation Requirement

In any work emanating from research based on the Generations and Gender Survey micro-data, I will acknowledge that these data were obtained from the GGP Data Archive and refer to the publication that describes the model survey instruments: United Nations 2005. Generations & Gender Programme: SurveyInstruments. New York and Geneva: UN, 2005

Deposit Requirement

Users of GGS micro-data are required to send any research papers based on the Generations and Gender Survey micro-data or aggregate tabulations to the Population Activities Unit of the UN Economic Commission for Europe, for inclusion in the GGP publications archive.


In order to access, it is necessary to subscribe to the GGP Data User Space, and to follow the instructions available on the GGP data access webpage.


The authors and producers bear no responsibility for the uses of the GGS data, or for interpretations or inferences based on these uses. The producers accept no liability for indirect, consequential or incidental damages or losses arising from use of the data collection, or from the unavailability of, or break in access to the service for whatever reason.

Related Materials


Other References Note

Norwegian country presentations at the GGP International Working Group Meetings

Data Files Description

File Name


Contents of Files

This is the reason why the total no. of variables in the Nesstar data file is smaller than the total number of variables in the SPSS and STATA files.

Variables are ordered according to the sections of the GGS codebook: Household, Children, Partnerships, Household Organisation and Partnership Quality, Parents and Parental Home, Fertility, Health and Well-Being, Respondent's Activity and Income, Partner's Activity and Income, Household Possessions, Income and Transfers, Value Orientations and Attitudes, Interviewers' report.
The variables begin with a letter designating the wave of data collection ("a" for the first wave likewise "b" for the second wave). We have attempted to keep the names of variables the same across the waves, and all the new variables would be identified as follows ["wave letter"]n e.g.  bn301.  
Although we encourage the countries to strictly follow the GGS Questionnaire, countries might implement a question that differs to a considerable extent from the GGS Questionnaire. In this case either we add country specific response values, or we introduce a country specific variable.  
Country specific values are added when the question follows the model questionnaire, but the answers are not at all or partly compatible. They are at least 4 digits long (F4 format) and begin with the country code: e.g., Australia 2401. Hence, the country code, as an example, for Australia is 24.  
A country specific variable is introduced when the question differs from the model questionnaire albeit measuring the same concept. This kind of variables is identified with a suffix given by the country code plus a number, e.g., Australia a119_2401.
In order to have an overview of GGS country code, please refer to the variable "acountry".

Overall Case Count


Overall Variable Count


Type of File

Nesstar 200801

Extent of Processing Checks

The data is submitted in an already pre-harmonised form. It is prepared and organised according to the GGS standards.  
Harmonisation aims at achieving a clear and comparable format of the GGS micro-data files that would be adequate for cross-country comparison.  The harmonisation procedure basically is composed of:
1. Label checks  
This step makes sure that all the variables are named the same across the countries and refer to a particular question in the GGS Questionnaire. Also the value labels are checked. They should be the same across GGS datasets.  
2. Dealing with grids
The GGS Questionnaire holds several grids of either event history information or members of the household. Such data needs to be harmonized with specific attention to order and logical consistency of grid-rows (be either household members or events such as births). In data sense each row of the grid is represented by variable name followed by a subscripted number ("_#"). Each subscript thus represents one household member or one event. Part of the grid harmonization is grid sorting. Grid rows are sorted according to pre-defined key. For example in the household grid, the household members are sorted according to their relationship to the respondent i.e. the relation to respondent variable (ahg3_# or bhg3_# ). Respondents would appear, first, followed by their partners and children if any and then followed by other household members. As there may be more then one child (or other relative) living in the household they also would need to be sorted. In the case of the household grid, age is used as the secondary sorting key (starting with the oldest person to the youngest).
3. Routing
Routing check ensures that the structure of underlying data set matches the structure of the GGS questionnaire. Its main goal is to code any given variable in the dataset to either a valid response, nonresponse or skip as indicated in the questionnaire. Consequently, the indicated skip in the quetionnaire is represented with a system missing code (. in STATA, sysmis in SPSS), while the missing information for other reasons is coded into non-applicable/no response (i.e. codes 7, 8, 9 in SPSS or .a, .b, .c in STATA).  
4. Consolidation  
The process consolidates the information scattered over several variables into a single one. The consolidation procedure is carried out in the Children Section, the Partnership Section and the Parents and Parental Home Section.
5. Imputation  
Due to its sensitive nature, the respondents are reluctant to share income information with the interviewer. In order to be able to use income information in a cross country comparative study and not to loose too many observations in the process it is necessary to impute the approximately correct distribution of the income variable in each country.  
6. Calculation of derived variables
We calculate derived variables out of the following variables:
- grid variables (i.e., household grid, children grid, and partnership history grid); the codebook starts with the constructed variables that sum the key socio-demographic characteristics of the respondent.
- month and year variables,  
- hours and minutes variables,
- frequency and unit variables.  
Occupation variables are recoded into ISCO-88 1 digit.
Explanations of the ways in which consolidated and derived variables are obtained, are available under the field "Note" of the "Variable Description" sections.
For a more detailed and technical procedure please refer to the Data Cleaning and Harmonisation Guidelines.

Missing Data

The following missing values have been assigned:
- 6, 96, 996, etc. = Unknown (only for consolidated variables in the group "administrative variables")
- 7, 97, 997, etc. = Don't know
- 8, 98, 998, etc. = Refusal
- 9, 99, 999, etc. = Not-applicable/no response


Harmonized dataset, GGS Wave1, version 4.3.


Variables corrected with Version 4.3.
- fertintent (no more ambiguous labelling)
- a1101 (corrected error in coding)
- aweight (now available also for NLD CZE SWE POL)
- aregion (now available also for HUN)
- aplace (now available also for HUN)
- a5112 (corrected routing error for ROU)
- a5113 (corrected routing error for ROU)
- a5114 (corrected routing error for ROU)
- a5115 (corrected routing error i for ROU)
- a211b_ (corrected error for POL & GEO)
- ankids (corrected error for POL & GEO)
- a1008mnth (corrected error for NGR & BEL)
- a108 (now available for SWE)
- a109_1 (now available for SWE)
- a109_2 (now available for SWE)
- a149 (now available for SWE)
- a309 (now available for SWE)
- aregion (now available for SWE)
- a620_ (corrected error for DEU & CZE)
- a402 (corrected error for POL)
- a149 (corrected error routing error in NOR)
- a344 (corrected error routing error in NOR)
- a256_ (corrected error for POL & GEO)

The update from v4.1 to v4.2 does not include corrections of existing variables.  
The update only includes additional variables which are derived from the pre-existing datasets
- Variables derived from grid variables and variables which concern the respondents and his/her partner: numdissol numdivorce nummarriage numpartners livingwithpartner childprevp femage maleage femeduc maleeduc fertintent numbiol numres numnonres numstep numallchild ageyoungest ageoldest numrespleave numotherparentleave coreschild coresparen coresgrandp coressibl.
- Variables derived from month and year variable:  
a808Dur a822Dur a907Dur a911Dur a914Dur; a303cAgeP a315AgeP a316cAgeP a374cAgeP a608AgeP a610AgeP a617bAgeP a621AgeP a914AgeP a941AgeP; a107AgeR a121AgeR a150AgeR a239aAgeR a239bAgeR a240AgeR a301AgeR a302bAgeR; a311AgeR a314bAgeR a314dAgeR a371AgeR a372bAgeR a603AgeR a608AgeR a610AgeR a613AgeR a614AgeR a619AgeR a621AgeR a816AgeR a822AgeR a871AgeR a5116AgeR a5117bAgeR; a302bTdiff a314bTdiff a314dTdiff a372bTdiff.
- Variables derived from hours and minutes variables: a324_hour a520_hour a540_hour.
- Variables derived from frequency and unit variables: a205mnth,a241mnth,a325mnth,a355mnth,a359mnth,a363mnth,a367mnth,a521mnth,a541mnth,a1008mnth,a1102mnth; a203c_?w a204c_?w.
- Occupation variables recoded into ISCO-88 1 digit: a828_1dig a832_1dig a861_1dig a917_1dig a921_1dig a933_1dig a5112_1dig a5114_1dig.

- Variables corrected: amarstat, ankids, a306, a309, a357, a365, a5106a_b,a5106a_s, a832.

- New constructed variables: asex aage abyear aeduc aactstat aparstat amarstat anpartner ankids ahhsize ahhtype ahhsize.
- New consolidated variables on respondents' current activity: a870, a871m, a871y, a873, a874, a875.
- New consolidated variables on respondents' partners current activity: a940, a941m, a941y, a943, a945.
- Variables corrected: a601 and a602 (corrected, with consequences on the response rate of subsequent variables), a622, a623, a624, a625, a626, a627*, a628*, a629*, a631*, a383 (now rounded), a864*ff, a936*, a334m*, a5106_a, a5106_b
- New weight variables: aweight_2001 (country specific population weight), aweight (Standardized weight based on country specific population weight, recommended for use).
- Variables which do not have country specific categories anymore: a149 a309 a380 (coded using ISCED 97), a203b_* (coded into GGS values: "part time kindergarden" and "kindergarden" merged into "nursery","relatives" dropped since this is information childcare, "no arrangement" into missing).
- Variables which have now country specific values: a203c_*
- Variables now available: a344y (now available also for widows/widowers).

The individual income variables of the Respondent a866_* and the partner a938_* have been renamed  into country specific variables a866_*_2000 and a938_*_2000, respectively. There are two deviations from the GGS Core Questionnaire for these variables. They are first, the annual and second, the gross amounts of payments for each income  type.  
For the Respondent (not the partner!) another country specific variable has been made available: a866_2000. This  "after-tax income" is calculated as the sum of wages and salaries, income from self-employment, property income and  transfers received minus total assessed taxes and negative transfers.


Before publication in Nesstar GGS micro data files are further processed so as to ease online data browsing and analysing.
We delete variables having all system missings.


Metadata Index

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