Abstract
This chapter comprises descriptive analyses on the level and development of generalized EU support and its determinants. Relying on 19 repeated, cross-sectional Eurobarometer surveys, the study draws a comprehensive picture of means and developments reported for the entire EU27, groups of countries, as well as for single EU member states between 2006–2015. It is found that the loss of EU trust during the acute phase of the Euro crisis between 2010 and 2013 was considerably larger than a comparable development during the great recession years of 2008/2009. This can be considered an unprecedented volatility in public opinion given the short history of European integration. At the end of the period under investigation the original level has still not been restored. Within the different country groups, the decline of EU trust during the acute phase of the Euro crisis and the development of the explanatory factors vary predominantly in the expected way. For instance, EU trust began to decline substantially when the adjustment programmes were introduced in the respective crisis countries. Strikingly, the temporal non-concurrence of the programmes matches the respective beginning of substantial decline in EU trust in opinion surveys.
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Notes
- 1.
For more information on the EB’s methodology, see GESIS (2017).
- 2.
- 3.
Details of the data compiling process, a list of all utilized datasets, and the construction of singular items will be further explained in the operationalization sections as well as in the appendix.
- 4.
The contextual data consists of 513 observations on level II (one countrycase per survey). Also see prior footnote.
- 5.
For more information on analysing weighted survey data, see Heeringa et al. (2017, 38f.).
- 6.
The three alternatives of EU trust, EU image, and EU memberships are both theoretically but also empirically closely related. The pairwise Pearson’s correlation coefficients obtained in the cumulated dataset show high correlations between the indicators: EU trust ←→ EU image: r = 0.56; EU image ←→ membership: r = 0.59; EU trust ←→ membership: r = 0.50.
- 7.
Those include contextual patterns of country groups reflecting their exposure to the Euro crisis in domain heterogeneity and duration.
- 8.
Another alternative to measure the individual identity structure asks: “In the near future, do you see yourself as: national only, national and European, European and national, European only”. This item has several disadvantages compared to the introduced variables: (1) It was not included in SEB regularly between 2006 and 2011, (2) contradictory to the conceptualization it does point towards the future rather than asking about the current attachment or feeling towards the political community of the EU. Social identity is considered a long-term attitude that is not subject to change in the short run. That is why prospective predictions would not make any sense to be asked for in a survey environment.
- 9.
The complete question wordings are documented in the appendix.
- 10.
All indicators reflect the current values of the period when the respective survey wave was conducted. Since the SEB is biannually conducted in spring and autumn of each year, the economic and financial data report values of the second and fourth quarter of that year respectively.
- 11.
All indicators, their coding and modifications by the author are disclosed in the appendix.
- 12.
Besides these economic, financial, and political country-level variables, I created additional dummy variables in the dataset to reflect the member states’ affiliation to potentially interesting country groups over time. That is, the following variables inform about whether the country had belonged to the respective group at the specific point in time for each of the 513 cases. These dichotomous variables consist of the following attributes: (1) member of the Eurozone, (2) national government changed in prev. year, (3) net contributor/recipient of EU budget in prev. year, (4) official violation of Maastricht criteria (stability and growth pact) in prev. year, (5) financial assistance & conditionality by IMF, World Bank, or European institutions (EFSF, EFSM, ESM), (6) financial assistance & conditionality by European institutions, and (7) same as 6 plus voluntary technocratic government tenure in Italy. Naturally, those country attributes can be used to create several different conditional patterns of country groups that eventually change over time.
- 13.
- 14.
Adding up to 100% since all outcomes are included in the depiction.
- 15.
When depicting this graph, respondents that chose to answer the image question with either “neutral” or “don’t know” are left out. That is why both trend lines add up to 100%.
- 16.
The variable’s numerical range is scaled to 0–1.
- 17.
The correlation between the change of GDP compared to 12 months before and the subjective national economic situation is r = 0.35 (country level, 2006–2015, n = 486).
- 18.
65.22% of respondents expect the personal job situation to remain unchanged; the weighted mean of the non-EZ group amounts to 0.025.
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Bauer, S. (2020). Study I: Level and Development of EU Support and Its Determinants. In: Citizens’ Support for the European Union. Contributions to Political Science. Springer, Cham. https://doi.org/10.1007/978-3-030-16461-4_5
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