EXPLANATION OF THE CONTENTS OF THE DISTRIBUTED FILEFOLDER To get the data.... ############################################################################################ 1. The GGS Wave 1 micro-datafiles for all GGS countries are available online from the GGP Data Archive (http://www.ggp-i.org/). Registration is required before you can access the data. As a result, the original GGS Harmonized Datafiles are not shared here. Interested users can register with the Gender and Generations Surey website. The application process to get access to the full dataset is described here https://www.ggp-i.org/form/procedure/ Directions for registering and accessing the data are provided under the section "Data" at https://www.ggp-i.org. The analysis in this article has been done on Wave 1 v.4.3 of the GGS data. Full documentation of the GGS-data and meta information about the variables are found in the file GGS-W1_V.4.3. - Consolidated.pdf that is provided in the distributed folder. The names of the variables used for the analysis is found in the script "datapreparation.do" ############################################################################################ For the purposue of the analysis in data for men and women aged 30-64 have been selected for the countries Country | Freq. Percent Cum. ------------------+----------------------------------- 11. Bulgaria | 9,282 9.97 9.97 14. Germany | 7,101 7.63 17.60 15. France | 7,236 7.77 25.38 16. Hungary | 10,042 10.79 36.17 17. Italy | 8,758 9.41 45.58 18. Netherlands | 6,461 6.94 52.52 19. Romania | 8,541 9.18 61.69 21. Austria | 4,035 4.34 66.03 22. Estonia | 5,618 6.04 72.07 23. Belgium | 5,322 5.72 77.78 26. Poland | 14,113 15.16 92.95 29. Sweden | 6,565 7.05 100.00 ------------------+----------------------------------- Total | 93,074 100.00 METADATA FOR VARAIBLES INCUDED IN THE ANALYSIS FILE Contains data from Data\GSS-sample.dta obs: 93,074 GGP W1 4.3 (ggp@nidi.nl) vars: 22 17 May 2019 15:30 size: 6,235,958 (_dta has notes) ----------------------------------------------------------------------------------------------------------------------------------------- storage display value variable name type format label variable label ----------------------------------------------------------------------------------------------------------------------------------------- PID str14 %14s acountry byte %26.0g acountry Country arid double %12.0g R identification number ayear int %26.0g ayear Yr of interview aage byte %26.0g aage_lb Age of Respondent asex byte %26.0g asex_lb Sex Respondent ahhtype byte %33.0g ahhtype_lb Household type Respondent ahhsize byte %9.0g Household size including Respondent abyear int %26.0g abyear_lb Birth Year Respondent aeduc byte %43.0g aeduc_lb Highest Education Level of Respondent amarstat byte %26.0g marstat marital status respondent anumbiol byte %9.0g Total number of biological children a148 int %60.0g a148 * Highest reached education level (country-spec. list) aweight double %9.0g Weight EDUC byte %9.0g EDUC Level of education livearr byte %13.0g livearr Living arrangement alone float %9.0g truefalse Respondent lives alone single float %9.0g cohab byte %13.0g cohab RECODE of livearr (Living arrangement) agr5 float %9.0g agr5 5-year age-group agr10 float %9.0g agr10 childless float %9.0g truefalse Childless * indicated variables have notes ----------------------------------------------------------------------------------------------------------------------------------------- Sorted by: acountry arid EXPLANATION OF THE CONTENTS OF THE "DO FILES" All analysis have been done in Stata v.15.1 To run the analysis.... ############################################################################################ 2. You need to edit the first section of the scripts "datapreparation.do" and "analysis.do" and set the appropriate paths to your working directory as well as the paths to Microsoft Word executable to get the automatic generation of the tables and figures document to work. In addition you might need to download some ado-files from ssc and github that are not distributed with Stata´s main distribution. This pertains to: grc1leg at http://www.stata.com/users/vwiggins: estimates_table_docx at https://raw.githubusercontent.com/glennsandstrom/estimates_table_docx/master: blindschemes at http://fmwww.bc.edu/repec/bocode/b: summtab at http://fmwww.bc.edu/repec/bocode/s: 2. Run the script "datapreparation.do". ############################################################################################ 3. Run the script "analysis.do" This script in turn calls the 3 sub-routines that produces the file Tables_and_figures.docx that contain all the output. ############################################################################################ If you have any questions please contact Glenn Sandström, PhD Research Fellow, Docent/Associate Professor Department of Historical, Philosophical and Religious Studies, Umeå University and Research Fellow, Centre for Demographic and Ageing Research (CEDAR), Umeå University and Research Affiliate, Stockholm University Demography Unit (SUDA), Stockholm University and Research Affiliate, Institute of Environmental Medicine (IMM), Epidemiology, Karolinska Institute. Adress: Institutionen för ide och samhällstudier, Umeå Universitet, SE - 901 87 UMEÅ, SWEDEN Phone: +46-90-786 59 75 Mobile: +46-70-509 75 89 E-mail: glenn.sandstrom@umu.se Web: http://www.umu.se/en/staff/glenn-sandstrom/ google scholar: http://scholar.google.se/citations?user=ONhNroEAAAAJ&hl orcid: http://orcid.org/0000-0001-7559-2571 research gate: https://www.researchgate.net/profile/Glenn_Sandstroem github: https://github.com/glennsandstrom