Dataset: Generations and Gender Survey Romania Wave 1

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 Romania Wave 1

Alternative Title

GGS Romania Wave 1

Identification Number

GGSW1.19

Date of Distribution

2010-03-25

Version

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 partly by the GGP-country team based on a structured questionnaire to UNECE, and partly it was taken from the references listed under “Other References Note”.

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_Wave1_Romania_V.4.3

Producer

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

Study Description

Full Title

Generations and Gender Survey Romania Wave 1

Alternative Title

GGS Romania Wave 1

Identification Number

GGSW1.19

Authoring Entity

Name Affiliation
National Institute of Statistics

Funding Agency/Sponsor

Name Abbreviation Role Grant
United Nations Population Fund Romania UNFPA Romania
Max Plank Institute for Demographic Research MPDIR

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

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
2005-11-07 2005-12-18

Country

Romania  (ROU)

Geographic Coverage

Whole country

Unit of Analysis

Individuals

Universe

Private households, persons 18-79 years (women and men)

Kind of Data

Survey data

Time Method

Panel

Sampling Procedure

1. Sampling frame
1.1 Type of frame: Dwelling lists: EMZOT (master sample)
1.2  Frame coverage: Whole population of Romania.
1.3 Frame size: Around 1.5 mil dwellings(13% of total permanent dwellings); 780 research centres(PSU): 427 urban, 353 rural
1.4 Level of units available: dwellings.

2. Sampling method
2.1 Sampling method type: multistage sample design - four stages
2.2 Sampling stage definition
- PSU: Research centres
- SSU: Dwellings addresses.
- TSU: NA.
2.3 Sampling stage size
- PSU: 420 research centres(54% of total number of EMZOT centre) 229 urban, 191 rural
- SSU: 14280 dwellings(12600 dwellings in initial sample+ 1680 dwellings reserve sample)
- TSU: NA.
2.4 Unit selection: DK
2.5 Final stage unit selection: DK
2.6 Within household unit selection: kish method (eligible persons 18-79 years)
2.7 Stratification: DK
2.8 Sample size:
- Starting size sample: around 10080 (5040 women, 5040 men)
- Aimed total size at Wave 1: DK
- Aimed total size at Wave 3: DK
2.9 Estimated Non-response: DK

Mode of Data Collection

Method: Face-to-Face (personal interview)
Technique: Paper and pencil (PAPI) - Registration method

Type of Research Instrument

Structured questionnaire in Romanian.

Characteristics of Data Collection Situation

WAVE 1 DATA COLLECTION
1. Interviewers
1.1 Total number of interviewers: 442 interviewers  
1.2 Number of interviewers in the field: 1 interviewer in each research centre.
1.3 Network organization: Structured on three levels: 42 local responsibles (42 counties–territorial units NUTS 3); 44 supervisors(1 at 12 interviewers).
1.4 Working arrangement of interviewers: DK
1.5 Payment of interviewers: DK

2. Interviewer training:  DK

3. Contact protocols
Preliminary visits: 2-6 Nov 2005
- Identify the address;
- Identify of dwelling and household status;
- Verify the existance of eligible persons;
- Establish the interview date.

4. Questionnaire localization
4.1 Validation: DK
4.2 Pre-test: The questionnaire was tested in November 2004 in 41 counties and Bucharest. In total 424 dwellings with eligible persons (18-79 years; 212 women and 212 men) were selected. The dwellings were based in 108 research centres(65 urban, 47 rural). The test was possible thanks to the financial support of UNFPA and technical support of NIS.
4.3 Length of interview: Average interview duration: 90-100 min. (89.3 min urban, 97.8 min rural).

Weighting

Composed post-stratification weight that combines two weights: a) based on age, gender, region (full matrix) and b) based in age, sex, household size (margins).

Cleaning Operations

Files with clean data: logical controls and data cleaning; large number of correlations between variables (around 1260).

Response Rate

Realized sample:
- Complete interviews: 11986 pers. (6009 women, 5977 men);
- Response rate: Total: 85.8%; Women: 86.3%; Men: 85.6%.

Completeness of Study Stored

Household questionnaires were also compiled with the aim of gathering household identification data.

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, 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 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

Romania_Questionnaire_W1_ro

Other References Note

Romanian country presentations at the GGP International Working Group Meetings

Data Files Description

File Name

GGS_Wave1_Romania_V.4.3..NSDstat

Contents of Files

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".

Overall Case Count

11986

Overall Variable Count

1446

Type of File

Nesstar 200801

Extent of Processing Checks

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, anpartner, ankids, a306, a309, a357, a365, a5106a_b,a5106a_s, a832.
- Variables which do not have country specific categories anymore: a149 a309 a322 a380 (coded using ISCED 97).
- Variables corrected: a626 (routing was erroneous) and a540

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: 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).
- Variables that do not have country specific values anymore: a203b (country specific value "Kindergarten" merged into "nursery", no country specificities anymore)
- New weight variables: aweight (available: composed post-stratification weight that combines two weights: a) based on age, gender, region (full matrix) and b) based in age, sex, household size (margins)

IMPROVEMENTS INTRODUCED WITH V.3.0 (August 2010):
- Variables renamed: a203c_1u..._`i'u and a204c_1u..._`i'u, renamed into a203cu_1...`i' and a204cu_1...`i'.
- Variables now available: a370, a383, a384
- Variables for which labels have changed : a376, a1003 and a1004 (previously coded as first, second, third... Mentionned, now coded per item as a yes/no question).

FIRST DATASET RELEASED: V.1.8 (March 2010).

Notes

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.

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