European Social Survey

In this online exercise, we will look at the European Social Survey (ESS). The ESS is funded by the European Union as well as participating European countries. It conducts face-to-face interviews every two years in more than 30 European countries. Besides questions on politics, it also features a large set of socio-economic variables. It also ask for vote choice in the previous national election. All data is available here..

Each wave of the ESS has a different theme, the most recent being wave 11 that focused on Social inequalities in health and gender in contemporary Europe, which we will also use below. Data was collected between March 2023 and June 2024. While reading, please keep in mind the questions below and answer them once you reached the end. In the final panel, we will provide a link to a platform with an interactive version of the dataset and additional tasks.

Table 1: General Tasks for the Dataset

Tasks
Does the individual-level relationship between income and support for EU integration translate to a between-country comparison?

Individual-level relationship between income and support for EU integration

We will focus on the relationship between income and support for EU integration, as described in chapter 2 of the book. Here, the assumption is that richer people are more likely to support EU integration because they benefit more from it, for example due to being able to choose jobs anywhere in Europe. The ESS measures income as a household’s total net income in deciles. The question they pose is “please tell me which letter describes your household’s total income, after tax and compulsory deductions, from all sources? If you don’t know the exact figure, please give an estimate.” They show respondents a range of letters from 1st decile to 10th decile. Of course, this measure is not perfect, as it is very hard for individual respondents to correctly estimate the income distribution of the country. In addition, many people might not know their exact income themselves, as outstanding taxes, irregular payments for one-off jobs, or income from additional sources such as rent, investments or self-employment might make it hard to estimate. However, asking for an exact amount of money a person earns each month, as other surveys do, comes with similar drawbacks and has the added difficulty of respondents being unwilling to reveal this number to the interviewer.

Support for EU integration is measured as: “Now thinking about the European Union, some say European unification should go further. Others say it has already gone too far. Using this card, what number on the scale best describes your position?”. Respondents indicate their position on a scale ranging from 0 (Unification already gone too far) to 10 (Unification go further).

Figure 1 shows the relationship between the two variables on the aggregate level (pooling respondents from all countries together). We can see that as income increases, support for EU integration goes up. Overall, support increases from about 5.1 for low income levels to 5.8 for high income levels.

We can now compare this with an aggregated analysis on the country level by adding GDP per capita as an explanatory variable and aggregating the support for EU integration on the country level. Figure 2 shows this relationship. Overall, we can see no relationship between GDP per capita and support for EU integration. In other words, richer countries are not more likely to support EU integration than poorer countries. This is an example of the importance of choosing the correct level of analysis to suit your research question as outlined in chapter 2 of the book.