Dataset: Generations and Gender Survey Germany-Turkish subsample 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 Germany-Turkish subsample Wave 1 & Wave 2

Alternative Title

GGS Germany-Turkish subsample Wave 1 & Wave 2

Identification Number

GGS.W1.W2.14.51

Date of Distribution

2013-03-29

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 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.

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_Germany_Turkish-subsample

Producer

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

Study Description

Full Title

Generations and Gender Survey Germany-Turkish subsample Wave 1 & Wave 2

Alternative Title

GGS Germany-Turkish subsample Wave 1 & Wave 2

Parallel Title

Generationenbeziehungen und Rollenverteilungen

Identification Number

GGS.W1.W2.14.51

Authoring Entity

Name Affiliation
Federal Institute for Population Research (BiB)

Producer

Name Affiliation Abbreviation Role
Federal Institute for Population Research BiB

Funding Agency/Sponsor

Name Abbreviation Role Grant
Federal Institute for Population Research BiB

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
Federal Institute for Population Research BiB

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
2006-05-15 2006-11-09 Wave 1
2009-09-15 2010-02-15 Wave 2

Country

Germany  (DEU)

Geographic Coverage

Whole Germany.

Geographic Unit

So-called "Regierungsbezirk" (NUTS 2 level).

Unit of Analysis

Individuals

Universe

WAVE 1
Turkish nationals registered and residing in Germany in 2006, aged 18 to 79 and living in private household in Germany.

WAVE 2
Persons who took part in Wave 1 and  expressed a willingness to be re-contacted, who lived in private households in 2006, were aged between 18 and 79 at the time of the interview and had Turkish nationality.

Kind of Data

Survey data

Time Method

Panel

Data Collector

TNS Infratest

Sampling Procedure

WAVE 1 SAMPLING PROCEDURE  
1. Sampling frame
1.1 Type of frame: The frame is set on information of local immigration authorities and base data originate from the Federal Register of Foreigners.
1.2  Frame coverage: NA
1.3 Frame size: NA
1.4 Level of units available: NA

2. Sampling method
2.1 Sampling method type: Three-tier procedure was selected in order to obtain a random sample: 1) local immigration authorities; information at the level of the districts, used in order to estimate the number of respondents at municipality level; basis for this was the share of the total population in the municipality as against the total population in the district (base data originate from the Federal Register of Foreigners (as per: 30 September 2005)); 2) each municipality in Germany was allocated a significance weight for the sampling at municipality level; sample selection of the municipalities was carried out with significance weight; 3) in the residents registration offices of the municipalities which were drawn, a random selection of respondents took place; municipalities in which insufficient number or no Turkish nationals live were removed from the sample.
2.2 Sampling stage definition
  - PSU: Sample points / muncipalities.
  - SSU: Adresses per point.
  - TSU: NA
2.3 Sampling stage size
  - PSU: 400 sample points (93 muncipalities).
  - SSU: 30 adresses per point (=gross estimate 12,000).
  - TSU: NA
2.4 Unit selection: NA
2.5 Final stage unit selection: NA
2.6 Within Household unit selection: NA
2.7 Stratification: NA
2.8 Sample size
  - Starting size sample: 11,876.
  - Aimed total size at Wave 1: 4,045.
  - Aimed total size at Wave 3: NA
2.9 Estimated Non-response
  - Initial non-response: 7,681.
  - Yearly attrition: From wave 1 to wave 2 around 3/4 (75%).
  - Non response measures: None.
  - Within household non-responses measures: NA

WAVE 2 SAMPLING PROCEDURE: same population than Wave 1 who had agreed to be re-contacted, i.e. n=2,602 respondents.

Mode of Data Collection

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

Type of Research Instrument

Structured questionnaire in German and Turkish translation aid (used if respondent was not able to understand the German question).

Characteristics of Data Collection Situation

WAVE 1 DATA COLLECTION
1. Interviewers
1.1 Total number of interviewers: 321.
1.2 Number of interviewers in the field: NA
1.3 Network organization: Centralized network with 6 regions being coordinated from TNS infratest. Local field coordinators were responsible for the fieldwork conducted within the region.
1.4 Working arrangement of interviewers: Part-time.
1.5 Payment of interviewers: Paid per interview (successful contact).

2. Interviewer training:  
2.1 General interviewing: Not for this project but in general with training materials distributed by central network and training conducted locally by field coordinators.
2.2 Survey specific: Yes, by sending written interviewer instruction before fieldwork started.
2.3 Length: 1 hour.
2.4 Control of performance: For randomly selected 10% of the interviews postcards with some questions about fieldwork (e.g. length of interview) were sent to the respondent. In case of questionable interviews the whole work (100%) of the interviewer was controlled.
2.5 Interviewer survey: No.

3. Contact protocols
3.1 Advance letter: Yes, interviewers could make use of a general contact letter as soon as they contacted the household.
3.2 Cold contacts: Face-to-face.
3.3 Scheduling / scattering: Yes, interviewers were entitled to scatter contact attempts by making sure that more than 50% of contact attempts were in the afternoon of week-days or on week-ends.
3.4 Contact history: No.
3.5 Min number of contacts: 4.
2.6 Max number of contacts: No.

4. Questionnaire localization
4.1 Validation: No.
4.2 Pre-test: Yes, with 50 persons; normal survey rules using the CAPI software. Country-specific response catagories were used for questions on e.g., education and occupation. 6 additional country-specific questions were added as compare to the harmonised questionnaire. These questins concern family policy measures, fertility intentions and abortion.
4.3 Length of interview: Average length of interview: 73 minutes, with wide range (minimum 37 minutes, maximum 185 minutes) according to the composition of the household and the biography of the respondent.

WAVE 2 DATA COLLECTION
1. Interviewers
1.1 Total number of interviewers: 197.
1.2 Number of interviewers in the field: DK
1.3 Network organization: Centralized network coordinated from TNS infratest.
1.4 Working arrangement of interviewers: Interviewers deployment followed the principle that the same interviewers were deployed again for the follow-up questionnaire wherever this was possible and meaningful.
1.5 Payment of interviewers: DK

2. Interviewer training:  
2.1 General interviewing: Yes
2.2 Survey specific: The interviewers were trained using written training material which contained both the objectives of the study, the nature of the selection process and information on individual difficult complexes of questions.
2.3 Length: DK
2.4 Control of performance: Routine postcard checks in 10% of all interviews conducted. As soon as abnormalities emerge, this triggers a check of all interviews conducted by the interviewer in question. Follow-up visits are also carried out by contact interviewers in ambiguous cases, in addition to postcard checks.
2.5 Interviewer survey: DK

3. Contact protocols
3.1 Advance letter: Prior to the questioning by the interviewers, the respondents received a centrally-dispatched letter informing them of the coming questionnaire.
3.2 Cold contacts: NO
3.3 Scheduling / scattering: DK
3.4 Contact history: DK
3.5 Min number of contacts: DK
2.6 Max number of contacts: DK

4. Questionnaire localization
4.1 Validation: No.
4.2 Pre-test: No. The computer-aided questionnaire program was taken over from the main GGS survey conducted on the German sample, which had been tested in detail by Infratest and the BIB prior to the field phase.
4.3 Length of interview: Average length of interview: 69 minutes , with wide range (minimum 29 minutes, maximum 142 minutes) according to the composition of the household and the biography of the respondent. As had already been the case in the first survey wave, interviews in which the Turkish translations were used, at an average of 88 minutes, were much longer than those which were conducted in German(65 minutes).

Actions to Minimize Losses

WAVE 1 ACTIONS
1.  Dealing with nonresponse
1.1 Screening: No.
1.2 Refusal conversion: No specific training for this project only general training.
1.3 Incentives: Money.

2. Tracking of sampled units
2.1 Respondent contact information: Yes, addresses (not email-addresses).
2.2 Other contact information:  
2.3 Cards: A "thank-you-letter" and birthday- and holiday cards were sent to all the respondents (planned frequency of contacts with the respondents between the two waves: 3). Furthermore, a brochure with results of Wave 1 was sent.   
2.4 Additional surveys: No.
2.5 Administrative records: NA

WAVE 2 ACTIONS
1.  Dealing with nonresponse
1.1 Screening: Yes.In addition to annual contacts, enquiries were also made to the residents’ registration offices with regard to those individuals where our letters were returned by the post office and where the ensuing postal enquiries did not provide a valid address.
1.2 Refusal conversion: DK
1.3 Incentives: The participants in the sub-sample received € 10 from the interviewer as an incentive. The participants were informed about this in the advance letter.

2. Tracking of sampled units
2.1 Respondent contact information: Yes, addresses (not email-addresses).
2.2 Other contact information: Yes.
2.3 Cards: Regular panel maintenance was carried out in the interim period by TNS Infratest. A "thank-you-letter" and birthday- and holiday cards were sent to all the respondents (planned frequency of contacts with the respondents between the two waves: 3). Furthermore, a brochure with results of Wave 1 was sent.
2.5 Administrative records: Yes (Einwohnermeldeamt)
The survey was carried out in the period from mid-September 2009 to mid-February 2010. A fieldwork time of three months to mid-December 2009 had originally been planned. Because of the n=884 interviews that had been carried out by mid-December and of a relatively promising share among those who were not reached, TNS Infratest Sozialforschung decided to invest in additional, unplanned post-processing. This post-processing contributed important additional interviews, so that a total of n=1,033 questionnaires had been carried out by mid-February 2010.

Control operations

WAVE 2 CONTROL OPERATIONS
Using the possibilities offered by CAPI, a "soft" comparison took place in the background with the core information on date of birth and sex in order to ascertain during the interview whether there were any deviations between the first questionnaire and the follow-up questionnaire when it came to the core data.

Weighting

WAVE 1 WEIGHTING
Yes, two weighting variables, household and personal weight. Procedure: The overall sample was adjusted to the target structures of the characteristics Federal Land, age groups, sex and education known from the official statistics. The publication of the Federal Statistical Office served as a data basis. The margin weighting by Federal Land and municipality size class (BIK) was based on an estimate based in turn on the information from the Federal Register of Foreigners at the level of the local immigration authorities.

WAVE 2 WEIGHTING
Same procedure as for the second wave of the German sample. The method applied is the consecutive factor weightings, which allows to conpensate for the distortions that may arise from drop-outs at the second wave. Three weighting variables have been calculated: 1) bweight_1402: longitudinal weight. The realised sample of the second wave was adjusted to the same target structures for the weighting of the second wave. The information on those who were re-contacted as to Federal State, age group, sex and BIK from the first survey wave formed the basis for this weighting. The official data basis is hence once more the target structure of the first weighting. 2) bweight_1401: Cross-sectional weighting. In addition to a longitudinal weighting of the drop-out processes, an adjustment of the structures was carried out in 2009 using reference data. In order to reach a cross-sectional weighting for the second survey time, an adjustment was carried out to the current structures on the longitudinal factors described above. 3) bweight: standardised weight.

Cleaning Operations

WAVE 2 CLEANING OPERATIONS
The main cleaning operations were: a) Editing of raw data and pre-harmonization: Renaming all variables names, (Re-)Translating all labels from German to English, Recoding variables if structure differed from the harmonization standard, Checking and coding of user missing values and system missing values, Checking of consistency of filters, Coding of basic information on education into ISCED-97 and occupation into ISCO-88
b) Checks for inconsistent results and logical consistency: checking the internal plausibility (e.g. household roster, dates),  plausibility between survey waves (e.g. sex and year of birth)
If possible corrections have been conducted. Otherwise cases or responses had been removed or documented. For more details and results: Naderi et al. 2012. http://www.bib-demografie.de/SharedDocs/Publikationen/DE/Materialien/121d.pdf?__blob=publicationFile&v=3

Response Rate

WAVE 1
Response rate - Final disposition codes:
I = complete interview: 4,045
P = partial interview: NA
NE = non-eligible : 2,015 + 150 (interviews carried out)
NC = non-contact : 3,127
R = refusal: 2,901
O = other non-response: 1,652
UC = unknown eligibility, contacted: NA
UC = unknown eligibility, non-contact: NA
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

WAVE 2
Response rate - Final disposition codes:
I = complete interview: 1,033 (of which 35 interviews had to be removed due to wrong respondent surveyed. HENCE: 998 interviews)
P = partial interview: DK
NE = non-eligible: 47
NC = non-contact: 605
R = refusal:  641
O = other non-response: 210
UC = unknown eligibility, contacted: NA
UC = unknown eligibility, non-contact: NA
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

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 the Federal Institute for Population Research (BiB) - Pages on German GGS

Germany_Turkish-Subsample_Questionnaire&ShowCards_W1_tr

Other References Note

German country presentations at the GGP International Working Group Meetings

Technical papers - Online link

Generations and Gender Survey. Dokumentation der Befragung von türkischen Migranten in Deutschland

Authors: Andreas Ette, Gert Hullen, Ingo Leven and Kerstin Ruckdeschel  
Materialien zur Bevölkerungswissenschaft 121b. Wiesbaden: Bundesinstitut für Bevölkerungsforschung

Generations and Gender Survey. Documentation of the Second Wave of the Sub-Sample of Turkish Nationals Living in Germany

Authors: Robert Naderi, Linda Beyreuther, Andreas Ette, Ingo Leven, Detlev Lück, Ralina Panova, Monika Pupeter, and Lenore Sauer  
Materialien zur Bevölkerungswissenschaft 121d. Wiesbaden: Bundesinstitut für Bevölkerungsforschung

Data Files Description

File Name

GGS_Wave1_Germany_Turkish_subsample_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

4045

Overall Variable Count

1371

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, a106b, a108, a109_1, a109_2, a110, a111, a303b, a304, a305, a306, a316b, a317, a318, a319, a374b, a375, a376, a377, a513b, a514, a515, a533b, a534, a535, a540, a521u, a541u, a5106a_b, a5106a_s, a5107.
- Value labels defined: a5108_2 (values of user missings now as according codebook).
- Variables dropped because erroneously included: Hhincome, Rincome, Rincome_f.

IMPROVEMENTS INTRODUCED WITH V.4.0 (March 2012):
- New constructed variables: asex, aage, abyear, aeduc, aactstat, aparstat, amarstat, anpartner, ankids, 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: a602 (with consequences on the response rate of subsequent variables), a622, a623, a624, a625, a626, a627*, a628*, a629*.
- Changes in the variable/value labels: atype (country specific list range 1401,1410 instead of 1400,1409).

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

File Name

GGS_Wave2_Germany_Turkish_subsample_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, 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

997

Overall Variable Count

1182

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.

IMPROVEMENTS INTRODUCED WITH GGS_Wave2_V.1.2 (April 2015)
The update from v1.1 to v1.2 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: bnumdissol, bnnumdissol, bnumdivorce, bnnumdivorce, bnnummarriage, bnummarriage, bnumpartnerships, bnnumpartnerships, bnrespartafterw1, blivingwithpartner, bchildprevp, bnchildprevp, bfemage, bmaleage, bfemeduc , , bmaleeduc, bfertintent, bnumbiol, bnumnonres, bnumres, bnumstep, bnumallchild, bageoldest, bageyoungest, bcoreschild, bcoresgrandp, bcoresparen, bcoressibl , bhhtype.
- Variables derived from month and year variable: b121AgeR, b150AgeR , bn152AgeR, b239aAgeR, b239bAgeR, b240AgeR, bn304Agb303cAgeP, b311AgeR, b315AgeP, b316cAgeP, b371AgeR, b372bAgeR, b372bTdiff, b374cAgeP, b5116AgeR, b5117bAgeR, b603AgeR, b608AgeP, b608AgeR, b610AgeP, b610AgeR, b621AgeP, b621AgeR, b871AgeR, b907Dur, b911Dur, b914AgeP, b914Dur, b941AgeP.
- Variables derived from hours and minutes variables: b324hour, b520hour, b540hour, b221hour_x.
- Variables derived from frequency and unit variables: b203c_xw, b204c_xw, b205mnth, b241mnth, b325mnth, b521mnth, b1008mnth.
- Occupation variables recoded into ISCO-88 1 digit: b828_1dig, b832_1dig, b861_1dig, b917_1dig, b921_1dig, b933_1dig.
- Three groups of variables derived from section no. 8 "Activity and Education History": 1) variables counting the total number of different activity and education situations Rs has had since age 16 (i.e., bnnumworkstatuses, bnnumstudentstatuses, bnnumemplstatuses, bnnumselfemplstatuses, bnnumhelpfamstatuses, bnnumunemplstatuses, bnnumretiredstatuses, bnnummilitarystatuses, bnnumhomestatuses, bnnummatleavestatuses, bnnumparleavestatuses, bnnumdisabilitystatuses, bnnumotherstatuses, bnnum1401, bnnum1501, bnnum1801, bnnum1301, bnnumparttime, bnnumfulltime, bnnumboth, bnnumparttime_1801, bnnumparttime_1802, bnnumpartfulltime_1803, bnnumfulltime_1804, 2) the total duration in month of each of the different situation (i.e., bndurstudentstatuses, bnduremplstatuses, bndurselfemplstatuses, bndurhelpfamstatuses, bndurunemplstatuses, bndurretiredstatuses, bndurmilitarystatuses, bndurhomestatuses, bndurmatleavestatuses, bndurparleavestatuses, bndurilldisabledstatuses, bndurotherstatusstatuses, bndur1501, bndur1401, bndur1301, bndurparttime, bndurlastparttime, bndurstudwhilework), 3) the age of R at the beginning and end of part-time employments (i.e., bn876_xAgeR, bn877_xAgeR, bn878xAgeR, bn879_xAgeR).

The availability of these variables in each different country-specific file depends on the availability of variables used for their calculation.

IMPROVEMENTS INTRODUCED WITH V.1.2. in Nesstar GGS micro data files (April 2015):
Publication of variables that were previously deleted before dataset release in Nesstar. The following variables are concerned: grid variables, month and year variables, hours and minutes variables, frequency and unit variables, and occupation variables.

FIRST DATASET RELEASED: V.1.1. (March 2013).

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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