This analysis investigates a dataset provided by European Social Survey (ESS) which is a cross-national survey of attitudes and behaviour from European citizens. The topics covered by ESS are very heterogeneous and include media and social trust, politics, immigration, citizen involvement, health and care, economic, work and well-being.
The analysis focuses on which aspects can influence a person to vote for their country to leave or remain a member of the European Union. The variables selected are mostly socio-demographic such as education, employment status and Union membership status.
The dataset used was ESS9-2018 Edition 3.1 released on 17th of February 2021 and it can be found here.
- CNTRY Country
- EDUYRS Years of full-time education completed
- EISCED Highest level of education, ES - ISCED
- UEMP3M Ever unemployed and seeking work for a period more than three months
- MBTRU Member of trade union or similar organisation
- VTEURMMB Would vote for your country to remain member of European Union or leave
- GNDR Gender
- YRBRN Year of birth
- AGEA Age of respondent. Calculation based on year of birth and year of interview
The analysis of survey data often uses complex sample designs and weighting adjustments in order to make the sample look more like the intended population of the survey. As ESS is a cross-national survey and countries implement different sample designs, it is important to use weights in all analyses to take into consideration the country context, and therefore avoid bias in the outcome.
The Data Analysis can be visualized as a GitHub Page.
