Dataset: Generations and Gender Survey Austria Wave 1 & Wave 2

Abstract

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 Austria Wave 1 & Wave 2

Alternative Title

Wave 1 & Wave 2

Identification Number

GGSW1.W2.21

Date of Distribution

2015-04-17

Version

Working Version: GGS Wave 1 Version 4.3 and GGS Wave 2 Version 1.3.

Update of variable catagories and documentation with the release of Poland Wave 2 Version 1.3.

Date: 2018-02-26

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 team, 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.

PLEASE NOTICE THAT WE DOCUMENT ONLY VARIABLES HAVING VALID CASES.  
VARIABLES HAVING ALL SYSTEM MISSING CASES ARE NOT DOCUMENTED.  
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

GGS_W1-V.4.3.&W2-V.1.3_Austria

Producer

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

Study Description

Full Title

Generations and Gender Survey Austria Wave 1 & Wave 2

Alternative Title

Austria Wave 1 & Wave 2

Parallel Title

"Familienentwicklung in Österreich" (Development of the family in Austria)

Identification Number

GGSW1.W2.21

Authoring Entity

Name Affiliation
Norbert Neuwirth Austrian Institute for Family Studies (OeIF); University of Vienna

Other identifications and acknowledgments

Name Affiliation Role
Andreas Baierl Austrian Institute for Family Studies (OeIF); University of Vienna Creation and documentation of GGS-HDF (only Wave 1)
Caroline Berghammer Vienna Institute of Demography (VID) Preparation & testing of survey instruments
Isabella Buber-Ennser Vienna Institute of Demography (VID) Preparation of survey instruments; additional weighting
Christine Geserick Austrian Institute for Family Studies (OeIF); University of Vienna Preparation & testing of survey instruments
Richard Gisser Vienna Institute of Demography (VID) Contributions to all stages (only Wave 1)
Markus Kaindl Austrian Institute for Family Studies (OeIF); University of Vienna Documentation of Austrian questionaire
Karin Klapfer Statistics Austria (STAT) Conduction of GGS-Survey (only Wave 1)
Josef Kytir Statistics Austria (STAT) Conduction of GGS-Survey
Georg Wernhart Austrian Institute for Family Studies (OeIF); University of Vienna Preparation & testing of survey instruments

Producer

Name Affiliation Abbreviation Role
Norbert Neuwirth Austrian Institute for Family Studies (OeIF); University of Vienna nn@oif.ac.at GGP-Austria; project coordinator; CDB data; GGS data quality procedures; GGS Data Harmonization
Andreas Baierl Austrian Institute for Family Studies (OeIF); University of Vienn ab@oif.ac.at GGS Data Harmonization (Wave 1)
Markus Kaindl Austrian Institute for Family Studies (OeIF); University of Vienna mka@oif.ac.at GGS Data Harmonization (Wave 2)
Rudolf Schipfer Austrian Institute for Family Studies (OeIF); University of Vienna rs@oif.ac.at CDB Data Collection

Funding Agency/Sponsor

Name Abbreviation Role Grant
Federal Ministry for Health, Family and Youth BMGFJ Leader (Wave 1)
Federal Ministry for Economic Affairs and Labour BMWA Wave 1
Federal Ministry for Science and Research BMWF Wave 1 & Wave 2
Federal Ministry for Economics, Family and Youth BMWFJ Leader (Wave 2)

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

Depositor

Name Affiliation Abbreviation
Austrian Institute for Family Studies (OeIF); University of Vienna.

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
2008-09-15 2009-02-15 WAVE 1
2012-09-22 2013-05-27 WAVE 2

Country

Austria  (AUT)

Geographic Coverage

Whole territory of Austria.

Geographic Unit

NUTS 4

Unit of Analysis

Individuals.

Universe

WAVE 1
Sufficiently German speaking men and women aged 18-45 on July 1st 2008 living in private households in Austria.

WAVE 2  
Sufficiently German speaking men and women aged 18-49 (Wave 1 respondents + refreshers) on Septmber 1st 2012 living in private households in Austria.
Concering panel respondents: panel survival: 78%; age range 22-49

Kind of Data

Survey data.

Time Method

Panel.

Data Collector

Statistics Austria  (STAT)

Sampling Procedure

WAVE 1 SAMPLING PROCEDURE   
1. Sampling frame
1.1 Type of frame: A real random sample of individuals (1) within the targeted age ranges (2) living in private households, drawn from the central national population register (Zentraler Melderegister; MR).
1.2  Frame coverage: As the sample was drawn from the central register, we should have full coverage.  Some people who had moved in-between date of sampling (July 2008) and survey (September 2008-February 2009) were harder to identify; additional procedures had to be engaged (passing the updated contact information to another interviewer, who is responsible for this region) but even some of them could be found and interviewed. Nobody should be excluded a-priori.
1.3 Frame size: 9,006.
1.4 Level of units available: Individuals.

2. Sampling method
2.1 Sampling method type: SRS (Simple Random Sampling).
2.2 Sampling stage definition
  - PSU: Individuals aged 18-45.
  - SSU: NA.
  - TSU: NA.
2.3 Sampling stage size
  - PSU: 9,006.
  - SSU: NA.
  - TSU: NA.
2.4 Unit selection: Random number generator.
2.5 Final stage unit selection: SRS (Simple Random Sampling).
2.6 Within Household unit selection: Random selection is based on registered individuals (see above). Selection did not depend on any household characteristics.
2.7 Stratification: Explicit - by design we draw 60% women and 40% men (3000 : 2000 in net sample).
2.8 Sample size:
  - Starting size sample: Gross sample size: 9,006; Net sample size: 5,000 (not all addresses within the gross sample needed to be contacted).
  - Aimed total size at Wave 1: 5,000  (Age range: 18-45).
  - Aimed total size at Wave 3: 4,050 cases with full panel information expected.
2.9 Estimated Non-response
  - Initial non-response: 36%.
  - Yearly attrition: We expect about 12% attrition in the second wave, and 8% at the third wave. At the end of the interview, wave 1, 96% agreed  to be interviewed again.
  - Non response measures: Oversampling
  - Within household non-responses measures: None.
   
WAVE 2 SAMPLING PROCEDURE   
1. Sampling frame
1.1 Type of frame: (1) panel sample: each Wave 1 respondent still living in Austria was recontacted, 78% panel survival; (2) refresher sample: young adults aged 18-22 (not targeted in Wave 1) taken in (3)refreshers of age cohorts that showed low panael survival.                                                                                                                                                                                                                                                                                                                                                                                                      
ATTENTION: Just panel respondents are included in the harmonised datafile. The full file (panel + refreshers) can be obtained on request from ggp@oif.ac.at.  
SO, FOR USERS OF THE HARMONISED FILE, THE RELEVANT INFORMATION ON SAMPLE SIZE IS SHOWN IN (1) BELOW !  
1.2  Frame coverage: (2) and (3)  based of central national population register (Zentraler Melderegister, ZMR)  
1.3 Frame size: (1)  5000, (2) 1372, (3) 128.
1.4 Level of units available: Individuals.

2. Sampling method
2.1 Sampling method type: (2) and (3) SRS (Simple Random Sampling); (1) drawn by SRS for wave 1.
2.2 Sampling stage definition
  - PSU: Panel Sample   
  - SSU: Individuals 18-22 (refresher sample)
  - TSU: Individuals (females; higer age cohorts)
2.3 Sampling stage size
  - PSU: 6720
2.4 Unit selection: (2 & 3)  Random number generator.
2.5 Final stage unit selection: SRS (Simple Random Sampling).
2.6 Within Household unit selection: Random selection is based on registered individuals (see above). Selection did not depend on any household characteristics.
2.7 Stratification: Explicit - by design we draw 60% women and 40% men in wave 1. sample (2) also 60% women 40% men.  
2.8 Sample size:
  - Starting size sample:  
  - Aimed total size at Wave 1: 5000
  - Aimed total size at Wave 3: 3400
2.9 Estimated Non-response
  - Initial non-response: 42%
  - Yearly attrition: Attrition had become higer as expected. We nearly had 22% panel mortality. This was partly due to the fact that the intervall between the panal waves had widened up to 4 years!
  - Non response measures: Incentives, additional sampling for cohorts with higher panel mortality
  - Within household non-responses measures: None.

Mode of Data Collection

Method: Face-to-Face (personal interview)
Technique: Computer-Assisted (CAPI)

Type of Research Instrument

Structured questionnaire in German. It was used the German version as translated for German GGS, with some modifications due to language differences between the two countries.

Characteristics of Data Collection Situation

WAVE 1 DATA COLLECTION
1. Interviewers
1.1 Total number of interviewers: 153
1.2 Number of interviewers in the field: No exact information about that. Basically, we worked with the same staff for the whole period. In November 2008 about 30 interviewers were taken in additionally.  
1.3 Network organization: Centralized.
1.4 Working arrangement of interviewers: Contracted, no students, experienced professionals.
1.5 Payment of interviewers: Per interview.

2. Interviewer training
2.1 General interviewing: We had spent a whole day on GGS-training; main points of agenda [1] programme presentation (GGP, what for  ~2 hrs);  [2] presentation of instrument (CAPI-demo; ~3 hrs);  [3]  special small group training and interview simulation for the most sensitive parts of the interview ~ up to 4 hrs.
2.2 Survey specific: See above.
2.3 Length: See above.
2.4 Control of performance: Control of performance: Path following routine within CAPI; automated tests within CAPI;  5% were checked by recontacting; just 1 interview was discovered as faked. Another interviewer had interviewed the identically named father instead of the son.   
2.5 Interviewer survey: Yes, see above.

3. Contact protocols
3.1 Advance letter: Yes; two letters, one by STAT-office, the other by the Federal Minister of family affairs.
3.2 Cold contacts: (1) Letters, (2) Telephone to arrange date and time of the interview, (3)  Face-to-face-interview.
3.3 Scheduling / scattering: Arrangement of date & time was within responsibility of the interviewer.
3.4 Contact history: Yes, within the data production file.  
3.5 Min number of contacts: No.
3.6 Max number of contacts: Not prescribed, just recommended  (5-8 times, depending on household composition, sex & age of respondent, region).

4. Questionnaire localization
4.1 Validation: No.
4.2 Pre-test: Yes. Some country-specific answers were added in the questionnaire. As to the pilot, Germany conducted the survey in December 2005, the surveys are quite identical, so the Germans "executed our pilot". Intensive checks and simulations were made regarding the CAPI-programme, about 30 test-interviews were conducted, but not a pilot study in it's formal sense.
4.3 Length of interview: 64 minutes (average mean); 60 minutes (median). Respondents were "paid" with a supermarket-cheque (€15,-). We developed a small questionnaire with specific questions for the partner and recommended that the partner should fill in this written questionnaire in another room, if possible. We had special trainings on the sensitive questions.


WAVE 2 DATA COLLECTION
1. Interviewers
1.1 Total number of interviewers: 146
1.2 Number of interviewers in the field: All interviewers were in for the whole field phase.  
1.3 Network organization: Centralized.
1.4 Working arrangement of interviewers: Contracted, no students, experienced professionals.
1.5 Payment of interviewers: Per interview.

2. Interviewer training
2.1 General interviewing: We had a whole training day, where we (1) presended the GGS2 programme (most interviewer also were in GGS1)[2:30 h] (2) presented the CAPI-demo [1:30], (3) had small workings groups for CAPI-based simulation of most sensitive parts of the questionaire [3:30] and (4) had specialized training units for F2F interviewing the most sensible parts [up to 2h]  
2.2 Survey specific: See above
2.3 Length: See above
2.4 Control of performance: Path following routine within CAPI; automated tests within CAPI;  5% were checked by recontacting; no interview was discovered as faked. Ex post we had to eliminate 6 cases, where obiousely another person had been interviewed in wave 1.
2.5 Interviewer survey: Yes, see above.

3. Contact protocols
3.1 Advance letter: Letter by STAT
3.2 Cold contacts: (1) Letters, (2) Telephone to arrange date and time of the interview, (3)  Face-to-face-interview.
3.3 Scheduling / scattering: NA
3.4 Contact history: Yes, within the data production file.  
3.5 Min number of contacts: No.
3.6 Max number of contacts: Not prescribed, just recommended  (5-8 times, depending on household composition, sex & age of respondent, region).

4. Questionnaire localization
4.1 Validation: No.
4.2 Pre-test: We had several test interviews to some dozens of real persons. In addition, we held test interviews (role play) between the 147 interviewers, especially in the sections of the questionaire that were rather complicated.
4.3 Length of interview: Length of interview: 65 minutes (average mean); 64 minutes (median). Respondents were "paid" with a  supermarket-cheque (€20,-). We developed a small questionaire with specific questions for the partner and recommended that the partner should fill in this written questionaire in another room, if possible. We had special trainings on the sensitive questions.

Actions to Minimize Losses

WAVE 1
1.  Dealing with nonresponse
1.1 Screening: Yes, by the first questions the information imputed from the centran register was checked.
1.2 Refusal conversion: Basically, the respondents showed a high grade of cooperativeness. For some items the non-resonse rate is significantly higher, but that's a respondent's decision we have to accept.
1.3 Incentives: Yes (supermarket cheque of €15,-).

2. Tracking of sampled units
2.1 Respondent contact information: Yes, some contact details of the respondent were collected.
2.2 Other contact information: No.
2.3 Cards: A "thank-you-letter" was sent to all the respondents. As Austria has a very good and recent centralized registration system (Zentraler Melderegister), we are in the position to follow the repondent within Austria. Just for verifying, we also send christmas greeting cards etc. to get aware of some emigrants etc. (the central register will give us the adresses of all respondents that have moved within Austria. So, we still cannot catch the emigrated, but we are keeping track of the within-Austria-migration).
2.4 Additional surveys: None.
2.5 Administrative records: Yes, again part of production file; Respondent-ID <=  Status change.

WAVE 2
1.  Dealing with nonresponse
1.1 Screening: Yes, by the first couple of questions the information imputed from the central register and/or wave 1 was checked.
1.2 Refusal conversion: Basically, the respondents showed a high grade of cooperativeness. For some items the non-resonse rate is significantly higher, but that's a respondent's decision we have to accept.
1.3 Incentives: Yes (supermarket cheque of €20,-).

2. Tracking of sampled units
2.1 Respondent contact information: Yes, some contact details of the respondent were collected. As we can follow the respondents within Austria by the Austrian central register, we should find them again. In fact we just had a handfull of blanks from wave 1 - one had died, two were institutionalized (prison, rehab) and some have emigrated.  
2.2 Other contact information: No.
2.3 Cards: A "thank-you-letter" was sent to all the respondents. As Austria has a very good and recent centralized registration system (Zentraler Melderegister), we are in the position to follow the repondent within Austria. Just for verifying, we also send christmas greeting cards etc. to get aware of some emigrants etc. (the central register will give us the adresses of all respondents that have moved within Austria. So, we still cannot catch the emigrated, but we are keeping track of the within-Austria-migration).
2.4 Additional surveys: No.
2.5 Administrative records: Yes, see above.

Control operations

See above; register queries.

Weighting

WAVE 1  
Yes, asymptotic weightig procedures:
- step1: age[1] * sex; labour market participation * sex * age[5]  
- step2: Land of origin; form of (co)habitation
- step3: Parity of women.
Two weighting variables:
1) Weight: Standardized weight based on the country specific population weight (recommended for use) .
2) Population Weight: Country specific population weight.

WAVE 2
Yes, asymptotic weightig procedures:
step1: age[1] * sex; labour market participation * sex * age[5]
step2: Land of origin; form of (co)habitation
step3: Parity of women.

Cleaning Operations

WAVE 1
We had some automated consistency checks during the CAPI-interview. After completion the ex-post consistency checks were activated, like some family relations, starting + ending dates, etc.

WAVE 2
Data was compared to wave 1 so as to dectect and correct inconsistencies. This was done for reported number of children and information on partners. In case of inconsistencies, wave 2 data was replaced with wave 1 data. In few cases, data should be corrected in wave 1 datafile instead. Discrepancies on partneship histories and employment histories were not corrected.

Response Rate

WAVE 1
Response rate - Final disposition codes:
I = complete interview: 5,000
P = partial interview: 132
NE = non-eligible : 769
NC = non-contact : 867
R = refusal: 1943
O = other non-response: 295
UC = unknown eligibility, contacted
UC = unknown eligibility, non-contact: 867
Note: As we know that all persons randomly selected (by sex & age) from the population register in the gross sample are/should be eligible, our missing-codes do not differentiate between these two UC ("unknown eligibility').
eC = estimated proportion of contacted cases of unknown eligibility that are eligible: NA
eN = estimated proportion of non-contacted cases of unknown eligibility that are eligible: NA
Overall response rate: 60.7%.

WAVE 2
FOR USERS OF THE HARMONISED FILE (including only panel respondents), THE RELEVANT INFORMATION ON FINAL DISPOSITION CODES IS SHOWN IN (1) BELOW!  
I = complete interview: (1) 3912 (2) 763 (3) 54
P = partial interview: no stastics on this group; summarized together with R (refusals)
NE = non-eligible : 0
NC = non-contact : (1) 57 (2) 84 (3) 0
R = refusal: (1) 707 (2) 387 (3) 56
O = other non-response: (1) 0 (2) 8 (3) 0
UC = unknown eligibility, contacted: 0
UC = unknown eligibility, non-contact: (1) 324 (2) 21 (3) 1
eC = estimated proportion of contacted cases of unknown eligibility that are eligible: 0
eN = estimated proportion of non-contacted cases of unknown eligibility that are eligible: 0

ATTRITION BETWEEN WAVE 1 AND WAVE 2
The Austrian GGS panel has a relatively low dropout (22%) and is affected by a small bias towards family-oriented persons as well as less-educated respondents and persons with migration backgrounds, but the data can be used without concern about selectivity.  
Isabella Buber-Ennser, Attrition in the Austrian Generations and Gender Survey: Is there a bias by fertility-relevant aspects?, Demographic Research (31), 2014, 459-496.

Completeness of Study Stored

WAVE 1
We imposed a couple of additional items that were not harmonized afterwards. Despite this fact, all items of the core questionaire and all items of additional module-wave1 are in the Austrian harmonized GGS-file. The additional questions that were not included in the harmonized file concern respondents' and partners' activity and income, including an Austrian-specific form of employment (something between employees and self-employed), religiosity, and childbearing intention.

WAVE 2
ATTENTION: the 822 sample refrechers are not included in the harmonised datafile. The full datafile (panel + refreshers) can be obtained by request from ggp@oif.ac.at.

Restrictions

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 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 transferred to the Wave 2 data.

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 ggp@unece.org http://www.unece.org/pau/

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.

Conditions

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.

Disclaimer

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

Website of Familienentwicklung in Österreich

Austria_Questionnaire_W1_de

Austria_Questionnaire_W2_de

Other References Note

Austrian country presentations at the GGP International Working Group Meetings

Some technical details on the Austrian Generations and Gender Survey Wave 2.

Report by Isabella Buber-Ennser (Vienna Institute of Demography, Research Report 36)

Attrition in the Austrian Generations and Gender Survey: Is there a bias by fertility-relevant aspects?

Article by Isabella Buber-Ennser (Demographic Research 31(16):459-496)

Data Files Description

File Name

GGS_Wave1_Austria_V.4.3..NSDstat

Contents of Files

GGS Wave 1

VARIABLES HAVING ALL SYSTEM MISSING CASES ARE DROPPED BEFORE PUBLICATION IN NESSTAR.
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".

File Structure

Record Group

Overall Case Count

5000

Overall Variable Count

1315

Type of File

Nesstar 200801

Extent of Processing Checks

WAVE 1 DATA HARMONISATION
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

Version

Harmonized dataset, GGS Wave1, version 4.3.

Notes

IMPROVEMENTS INTRODUCED WITH V.4.3. (August 2016):
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)

IMPROVEMENTS INTRODUCED WITH V.4.2. (February 2014):
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.

IMPROVEMENTS INTRODUCED WITH V.4.1. (April 2012):
- Variables corrected: amarstat ankids anpartner, a540t, a208c* (now with corrected labels).
- Variables now available: aweight_2101

IMPROVEMENTS INTRODUCED WITH V.4.0 (March 2012):
- New constructed variables: asex aage abyear aeduc aactstat aparstat amarstat anpartner ankids ahhsize ahhtype ahhsize ahhtype.
- 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)
- New weight variables: aweight_2101 Country specific population weight, aweight Standardized weight based on the country specific population weight (recommended for use).

FIRST DATASET RELEASED: V. 3.0 (November 2010).

File Name

GGS_Wave2_Austria_V.1.3..NSDstat

Contents of Files

GGS Wave 2

VARIABLES HAVING ALL SYSTEM MISSING CASES ARE DROPPED BEFORE PUBLICATION IN NESSTAR.
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, Activity and Education History, 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".

File Structure

Record Group

Overall Case Count

3912

Overall Variable Count

1389

Type of File

Nesstar 200801

Extent of Processing Checks

WAVE 2 DATA HARMONISATION: see "Extent of Processing Checks" "WAVE 1 DATA HARMONISATION".

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

Version

Harmonized dataset, GGS Wave2, version 1.3.

Notes

IMPROVEMENTS INTRODUCED WITH GGS_Wave2_V.1.3 (August 2016)
Correction of the following variables that were previously  erronous: b343_*, bnnumdissol, bnumdissol, bnnumdivorce, bnumdivorce, bnnummarriage, bnummarriage.

FIRST DATASET RELEASED: V.1.2. (April 2015).

Notes

WAVE 2 DATASETS - Main differences compared to WAVE 1 datasets
Wave 2 datasets include an additional new section that had not been implemented in the Wave 1 data collection. It is the section no. 8 "Activity and Education History". Respondents report comprehensively on their activity and education history since age 16. Two additional sections are also present at the end of wave 2 dataset: "Interviewer observations" and "Interviewer report" (respectively sections no. 13 and 14).
A set of constructed variables at the top of the data file increase the usability of the GGS data by summarizing key socio-demographic characteristics of the respondent (age, birth year, sex, level of educational attainment, activity status, partnership status, number of co-resident partners, number of children, household size, household type). An additional set of variables consolidates information on the current activity of the respondent and his/her partner that is otherwise spread over the questionnaire. Another set of consolidated variables concern respondents' parents and parental home.

WAVE 2 DATASETS - Variables names
Variables in the Wave 2 data sets that are consistent with variables implemented in the Wave 1 questionnaire are named identically. Wave 2 variable names start with the letter "b" compared to letter "a" in Wave 1. Variables that have not been implemented in Wave 1 but collected in Wave 2 begin with "bn".  
In Wave 2 datasets published in Nesstar, the variable "brid - R identification number" has been renamed into "arid" (same variable name than Wave 2). This allows the user to merge Wave 1 and Wave 2 datasets in Nesstar.
In Wave 2 datasets published in Nesstar, variable labels have the indication "(W2)". This allows the user to distinguish Wave 2 variables from Wave 1 variables, on the basis of the variable labels.

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