Dataset: Generations and Gender Survey Estonia 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 Estonia Wave 1

Alternative Title

GGS Estonia 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 Estonia Wave 1

Alternative Title

GGS Estonia Wave 1

Parallel Title

Eesti Pere- ja Sündimusuuring (EPSU).

Identification Number


Authoring Entity

Name Affiliation
Kalev Katus Tallinn University

Other identifications and acknowledgments

Name Affiliation Role
Estonian Institute for Population Studies (EDI) Tallinn University Development, implementation
Estonian GGS Working Group Tallinn University Development


Name Affiliation Abbreviation Role
Kalev Katus EDI Director
Luule Sakkeus EDI Researcher
Allan Puur EDI Researcher

Funding Agency/Sponsor

Name Abbreviation Role Grant
Eesti Statistikaamet (Statistical Office of Estonia) SA
Rahvastikuminstri büroo (Office of the Minister for Population Affairs

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
Estonian Institute for Population Studies (EIPS)

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
2004-09 2005-12


Estonia  (EST)

Geographic Coverage

Whole territory of Estonia.

Geographic Unit

County (Estonia is divided into 15 counties).

Unit of Analysis



Resident population (incl. those living in institutions), birth cohorts 1924-1983 (aged 21-80 on December 31st, 2004).

Kind of Data

Survey data

Time Method


Data Collector

Estonian Institute for Population Studies, Tallinn University  (EDI)

Sampling Procedure

1.1 Type of frame: Individual records (name list of persons) of the 31.03.2000 population and housing census, updated by means of population register for deaths, emigrations and changes of address that occurred between the census date and survey.
1.2  Frame coverage: Estimated coverage of the target population by the frame is 99.8%. Under-coverage constitutes of new immigrants in 2000-2004 (2,915 persons or 0.2%  of the census population). Over-coverage of deceased persons and out-migrants was removed through updating the frame by means of population register.
1.3 Frame size: 1,031,556 individuals (born in 1924-1983).
1.4 Level of units available: Individuals.

2. Sampling method
2.1 Sampling method type: Simple Random Sampling (SRS).
2.2 Sampling stage definition
  - PSU: Individual.
  - SSU: NA.
  - TSU: NA.
2.3 Sampling stage size
  - PSU: NA (primary sampling unit was individual; respondents were sampled directly from the frame).
  - SSU: NA
  - TSU: NA
2.4 Unit selection: Random number generator.
2.5 Final stage unit selection: Simple Random Sampling (one-stage sampling, individuals were sampled directly from the frame).
2.6 Within Household unit selection: NA (primary sampling unit was individual, respondents were sampled directly from the frame).
2.7 Stratification: Explicit (different sampling probabilities for men and women, lower for men).
2.8 Sample size:
  - Starting size sample: 11,192.
  - Aimed total size at Wave 1: 8,000.
  - Aimed total size at Wave 3: None.
2.9 Estimated Non-response
  - Initial non-response: 29.8%.
  - Yearly attrition:  
  - Non response measures: Substitutes (sampled and matched by gender, 5-year birth cohort and county).
  - Within household non-responses measures: None (if the designated respondent did not answer, the household was marked   as non-response).

Mode of Data Collection

Method: Face-to-Face (personal interview) was the main method. In addition, a drop-off-mail-back questionnaire was used to collect data mainly on attitudinal questions. Return rate of the drop-off questionnaire was 80.3% of the respondents.
Technique: Paper and Pencil (PAPI).

Type of Research Instrument

Structured questionnaire in Estonian and Russian.

Characteristics of Data Collection Situation

1. Interviewers
1.1 Total number of interviewers: 130.
1.2 Number of interviewers in the field: The number varies according to the stage of fieldwork. Some interviewers quitted at an early stage of the work. At the later stages of the fieldwork the number of active interviewers decreased as more and more interviewers completed their task.
1.3 Network organization: Centralized coordination.
1.4 Working arrangement of interviewers: The network was project-based and consisted of both full- and part-time interviewers. Most of the interviewers were working or had previously worked as interviewers for Statistical Office or polling firms. They were hired by the institute on fixed term basis.
1.5 Payment of interviewers: Per interview + travel expenses.

2. Interviewer training:  
2.1 General interviewing: The majority of the interviewers (nearly 90%) had previous training in interviewing either in Statistical Office or polling firms (interviewing techniques, appointments, conversion of refusals, etc.).
2.2 Survey specific: Before the fieldwork started, a series of GGS-specific training seminars was organized in several locations in Estonia. The training was focused on the GGS survey instrument (questionnaire) and procedures of the fieldwork.
2.3 Length: General training varied depending on survey organization (typically 2-3 days). The GGS-specific training was 1.5 day.
2.4 Control of performance: The quality was monitored by checking the filled-in questionnaires. The interviewers received personal feedback from the coordinator. A letter describing typical problems that were detected was circulated to all interviewers at the early stage of the fieldwork.
2.5 Interviewer survey: Yes. A brief questionnaire was distributed among the interviewers once the fieldwork was completed. It collected background information about interviewer, the contacting procedures, and experiences with respondents, comments on questionnaire modules, etc. Altogether 106 interviewers responded.

3. Contact protocols
3.1 Advance letter: All respondents received an advance letter introducing the survey and informing about the coming of the interviewer. The letter explained the purpose, subject of the survey, the institutions involved. The letter requested respondent's cooperation.
3.2 Cold contacts: Mixed practice. Usually the interviewers tried to make a telephone contact and schedule an appointment for the face-to-face interview. But this was not always feasible and part of the interviewers preferred to start with face-to-face contact.
3.3 Scheduling / scattering: Yes. To get a higher response rate, contact attempts were scattered over different days of week and parts of the day.
3.4 Contact history: Yes. The interviewer documented attempts to contact the respondent on a special form. For each case of non-response, the form was checked by the coordinator.
3.5 Min number of contacts: Number was set for the attempts of face-to-face contacts (5 for respondents in urban areas, 3 in rural areas).
2.6 Max number of contacts: No.

4. Questionnaire localization
4.1 Validation: Retranslation of the questionnaires.
4.2 Pre-test: A pilot was carried out in June 2003 (120 respondents). The pilot study confirmed the possibility to increase the number of event histories and to also expand the target population to include the population groups of foreign origin using a Russian language questionnaire.
4.3 Length of interview: Respondents who agreed for the interview were generally cooperative. Average length of interview was 99 minutes but it varied according to the complexity of life history and household composition of the respondent. The presence of another person was reported at 24% of the interviews. Difficulties were reported at 4% of the interviews (in most cases recall difficulties).

Actions to Minimize Losses

1.  Dealing with nonresponse
1.1 Screening: No.
1.2 Refusal conversion: Usual techniques of refusal conversion, i.e., insisting on the importance of the survey, its international dimension, addressing specific concerns of the respondent, etc.
1.3 Incentives: No.

2. Tracking of sampled units
2.1 Respondent contact information: The addresses of the respondents were recorded.
2.2 Other contact information: Since the funding was available for a single wave, other contact information was not recorded. Respondents can be followed up by means of the population register.
2.3 Cards: No.
2.4 Additional surveys: No.
2.5 Administrative records: No.

Control operations

Controls (consistency checking) were applied at the stages of data entry and data cleaning.


A weighting variable "aweight" at the respondent level was developed to adjust the collected data for an overrepresentation of women, underrepresentation of men and younger birth cohorts. Weighting variable considers age and sex groups and adjusts the sample to age-sex composition of the Estonian population at the beginning of 2005.

Cleaning Operations

The datafile was checked for logical inconsistencies, open-ended answers were checked and recoded, if necessary.

Response Rate

Response rate - Final disposition codes:
I = complete interview: 7,855
P = partial interview: 0
NE = non-eligible : 0
NC = non-contact : 1,142
R = refusal: 1,783
O = other non-response: 412 (this category includes less than partically completed questionnaires due to inability of the respondent to provide answer)
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 the Estonian context. Due to funding constraints the plans for panel waves were not feasible and part of the GGS  items were not implemented. The added questions, not included in the harmonized data file, are country-specific and serve for the comparability with previous national surveys, incl. the FFS.The added questions deal with topics ike abortion history, migration history as well as education and work histories. An additional module containing attitudinal questions was also developed.


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

Estonian 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, a622 (corrected, with consequences on the response rate of subsequent variables).

- 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.
- New consolidated variables on respondents' partners current activity: a940.
- 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*.
- New weight variables: aweight

FIRST DATASET RELEASED: V. 3.0. (March 2011).


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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