Economic considerations and national identity as drivers of public support for the European Union: a comparison including the economic and political context in 2010 and 2015

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The Institute of Public Administration

Faculty of Governance and Global Affairs – Leiden University

A thesis submitted to the Faculty of Governance and Global affairs at Leiden University in partial fulfillment of the requirements for the degree of Master of Science in

The Institute of Public Administration (Public Administration: International and European Governance).

ECONOMIC CONSIDERATIONS AND NATIONAL IDENTITY AS

DRIVERS OF PUBLIC SUPPORT FOR THE EUROPEAN UNION:

A COMPARISON INCLUDING THE ECONOMIC AND POLITICAL

CONTEXT IN 2010 AND 2015

by M.R.M. Soomers

June 2019 Student number: s1233580

Thesis supervisor: Dr. D.D. Toshkov Second reader: Dr. R. de Ruiter

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Abstract

This thesis is a contribution to the ongoing debate about the relative importance of economic considerations and identity-based considerations in shaping public support for the European Union. It aims to add to the current state of knowledge by performing an analysis based on more recent Eurobarometer survey data. A literature review is provided to theorize that both economic considerations and national identity are able to explain the level of public support for the European Union. Three hypotheses are formulated based on this literature review. First, it is expected that the explanatory power of economic considerations has declined, and the importance of national identity has grown in the years since the crisis has ended. In this thesis, evidence is found that both economic considerations and national identity are related to public support for the European Union. Contrary to our expectations, the explanatory power of economic considerations has remained stable. The explanatory power of national identity has indeed grown. Second, it is expected that the strength of economic considerations in explaining public support for the EU is correlated with the severity of the crisis in a country. The analysis finds no evidence of this relation. Third, it is expected that the strength of national identity-based considerations is correlated with the popularity of populist parties in a country. The analysis finds no evidence of this relationship in 2010, but it does find a significant relationship in 2015.

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Acknowledgements

I would like to express my gratitude to Dr. D.D. Toshkov for his excellent supervision. Dr. Toshkov has taught me so many new things that I just hadn’t encountered in my studies before I started this research project. I could not have completed it without his knowledge, patience, and supportive attitude. I would also like to thank Dr. N.A.J. van der Zwan and Dr. C.J.A. van Eijk for their help in acquiring the skills necessary to perform this research. Many thanks also go to Dr. de Ruiter for agreeing to be the second reader for this thesis.

I would like to thank my parents, my brother, Laurens, and my family and friends for their support during this process. You are the ones who supported my decision to pursue this master’s degree and you are the ones who helped pull me through. Words cannot describe how much you all mean to me. Thank you. Thank you. Thank you.

“Trying and failing and trying again and failing again is normal. (…) it’s good to mess up and learn from it and take risks. It’s especially good to do this in your twenties because we are searching. That’s GOOD. We’ll always be searching but never as intensely as when our brains are still developing at such a rapid pace. (...) do you, you’re searching.”1

1_{Swift, T. (2019, March 06). 30 Things I Learned Before Turning 30. Retrieved June 16, 2019, from}

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Ch. 1: Introduction

1.1 Problem outline

In the early period of European integration, political leaders could decide on further integration without consulting the public. This attitude, described by scholars as ‘permissive consensus’, has been replaced by ‘constraining consensus’ (Hobolt & Wratil, 2015, p. 238). Political leaders in Europe nowadays need to take public support for European integration into account when answering questions about what the future of the European Union should look like.

Therefore, knowledge about the drivers of public support for European integration is important. Unsurprisingly, this topic has gained a lot of attention of scholars in the field of European integration studies over the years. Many studies have focused on the impact of the Euro crisis on public support for European integration. Various scholars have come to the conclusion that during the Euro crisis, the factors that shape public support “have shifted from identity-based concerns before the crisis to more utilitarian considerations during the crisis” (Hobolt & Wratil, 2015, p. 239).

However, recent developments raise the question whether this is still the case now that the crisis has ended. Reading the sentiment in newspapers, and seeing populist party politicians achieve great electoral results, one can wonder if public support for European integration is shifting back to identity-based drivers. Focusing on a puzzle can inform the research question for a research project (Toshkov, 2016, p. 46). In this case I wonder: Were the utilitarian considerations from previous studies temporary and mainly caused by the economic crisis? Has national attachment again become a more powerful explanation for one’s public support for European integration?

1.2 Research question

The problem outlined above then leads to the following research question, that will be answered in this thesis:

‘How has the relative explanatory power of identity-based and economic rationality-based drivers of public support for European integration changed in the years after the Euro crisis ended?’

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1.3 Academic relevance

Studies into European integration have theorized about the factors that shape European integration and tested their assumptions empirically. Scholars have described a shift from identity-based drivers to utilitarian based drivers during the economic crisis. However, a lot has changed since then and therefore it is academically relevant to test the current state of affairs. It is interesting to see whether these theories still hold or if we need to adapt our insights to recent developments. In that sense, my thesis will contribute to the knowledge about European integration by adding the latest developments to the state-of-the-art.

1.4 Societal relevance

European integration has far-reaching consequences for European citizens. Public support for European integration can serve as a source of legitimacy for the European institutions. It is therefore of high societal relevance to look into the factors that shape public support for European integration. By contributing to this knowledge, this thesis will be relevant to both policy- and decision-makers at various levels of governance, as well as citizens.

1.5 Reading guide

In this first chapter, I have introduced the subject and posed the research question that will be answered in this thesis. I have stated the academic and societal relevance of this research. In the second chapter, I will review the literature on public support for European integration. Special attention will be paid to identity and economic rationality as drivers for public support. In the third chapter, I will justify the research design and methodology. I will argue why a multi-level regression analysis of Eurobarometer survey wave is suitable for answering this research question. In the fourth chapter, I will present and analyze the data from the regression analysis. In the fifth and final chapter, I will draw conclusions from the results presented in the previous chapter and answer the research question. I will also discuss the limitations of this research and discuss possibilities for further research.

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Ch. 2: Literature review

In this chapter, the literature about European integration will be discussed. I will elaborate on the state-of-the-art knowledge and assess the relevancy of previous work in the context of my research question. Special attention is paid to factors shaping public support for European integration: identity-based factors and economic rationality. Additionally, this chapter will provide insights on how the Euro crisis has impacted public support. Based on this theoretical framework, the chapter will conclude by formulating hypotheses that will be tested in this research project.

2.1 Public support for European integration

Hobolt (2014) describes the study into attitudes towards European integration as an active research field that has already been looked at from various angles (p. 665). Previous research has studied support for EU institutions, enlargement, or specific elements of the European Union. The most researched aspect is generic support for integration, in which cases the researchers relied on Eurobarometer survey data. Hobolt states two approaches towards European integration that are common in research: a utilitarian approach and an affective approach (p. 666). Hobolt explains the utilitarian approach as “an economic cost-benefit analysis”, whereas the affective approach is about “group conflict and symbolic politics” (Hobolt, 2014, p. 666). The utilitarian approach can be applied to the individual level and to the national level. The idea behind it, is that when an individual or country profits from EU membership, public support for EU membership will be higher. According to Hobolt, the utilitarian approach offers “a compelling framework for understanding differences in support for integration” (Hobolt, 2014, p. 666). However, research has shown that “socio-economic factors generally explain a relatively small proportion of individual-level and cross-national variance in support” (Hobolt, 2014, p. 666). The affective approach is not based on a cost-benefit analysis, but instead looks at group conflict and symbolic politics (Hobolt, 2014, p. 666). Within this approach, European integration is not only about trade liberalization or profit, but also about sovereignty, self-determination and national communities.

Hobolt is not the only one to make this distinction, as many other scholars have also used these two approaches. In 2004, Hooghe and Marks already asked whether identity or economic rationality drive public opinion on European integration (p. 415). They note that most scholars have examined support for European integration in the context of its economic consequences.

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This has resulted in precise knowledge about socio-economic factors that influence one’s preference over European integration. However, another explanation for support for European integration has often been overlooked by these scholars: “the assumption that citizen preferences are driven by group attachments, by the loyalties, values, and norms that define who a person is” (p. 415). In the years that followed, many scholars have attempted to answer the question posed by Hooghe and Marks: whether identity or economic rationality drive public opinion on European integration. This thesis is an attempt to continue that progress by updating the knowledge to a changed environment with the latest Eurobarometer survey data.

2.1.1 Drivers of public support: Identity versus Economic Rationality

As described in the previous paragraphs, scholars have identified two drivers of public support for European integration: political economy and national identity (Hooghe and Marks, 2004, pp. 415-416). In their article, Hooghe and Marks construct a theoretical framework that provides us with insight in both of these explanations for European integration. They theorize an “economic explanation of public opinion on European integration”, as well as an explanation that looks at “identity as a source of public opinion on European integration” (Hooghe and Marks, 2004, p. 415).

2.1.1.1 Economic explanations for public support for European integration

In the literature, many explanations of public support for the European Union and further integration have focused on economic factors. In a way, this makes sense, as European integration has aimed to “remove economic barriers, facilitate mobility of capital and labor, and create a single monetary authority” (Hooghe and Marks, 2004, p. 415). The main idea and most simple expectation that follows from this is that “reducing trade barriers favors citizens with relatively high income, education and occupational skills” (Gabel and Inglehart, as cited in: Hooghe and Marks, 2004, p. 415). It is important to make a distinction between economic circumstances on the collective level and economic circumstances that affect citizens on the individual level. Hooghe and Marks theorize that citizens in countries who receive EU money will lean towards support for European integration, while citizens in countries that are net contributors to the EU will tend to be against it (p. 416). These explanations can be measured objectively, but the way in which people perceive European integration to affect their socio-economic status and future is also important (Hooghe and Marks, 2004, p. 416). Thus, subjective economic evaluations also matter. Hooghe and Marks (2004) explain that “citizens

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who feel confident about the economic future -personally and for their country- are likely to regard European integration in a positive light” (p. 416). On the other hand, they explain that “those who are fearful will lean towards Euroskepticism” (p. 416). The last factor that Hooghe and Marks take into account is the influence of institutions. The authors argue that it is costly to change the institutions of a country. Thus, when the institutions of a country differ from the EU median, EU legislation imposes great costs (p. 416). Additionally, there is an interaction between the political-economic institutions and the citizens’ preference to support or oppose economic distribution. Hooghe and Marks (2004) conclude that “in social democratic systems, the left will be opposed to European integration and the right will be supportive” (p. 416). Adversely, in liberal market systems, it is the other way around (p. 416).

2.1.1.2 National identity as an explanation for public support for European integration

Having described the economic explanations for public opinion on European integration, Hooghe and Marks (2004) continue to examine the relationship between national identity and public support for European integration. Looking back in history, it is not surprising to theorize that national identity can influence the public support for European integration. Citrin et al., Massey, and Sears put it as follows: “Humans and their ancestors evolved an emotional capacity for intense group loyalty long before the development of rational faculties, and such loyalties can be extremely powerful in shaping views towards political objects.” (as cited in Hooghe and Marks, 2004, p. 416).

To understand the effects of national identity on public support for European integration, it is essential to acknowledge that the effect of national identity on public opinion for European integration can be both positive and negative (Hooghe and Marks, 2004, p. 416). The positive effect has been found in multiple research projects into this topic and has been described by various scholars. The territorial community one identifies with, is not exclusive. Individuals can identify themselves with multiple communities simultaneously. Research even found positive associations between certain identities and European identities. Risse, Van Kersbergen, and Citrin and Sides (as cited in Hooghe and Marks, 2004, p. 416) are among the various scholars who have shown the positive relationship between national identity and public support for European integration. However, this is not always the case. A negative attitude towards European integration is often portrayed as “defense of the nation” (Hooghe and Marks, 2004, p. 416). This sentiment is used by radical right-wing parties, that speak to feelings of nationalism. For example, Christin and Trechsel have found that “the stronger the national

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attachment and national pride of Swiss citizens, the less likely they are to support membership of the European Union” (as cited in Hooghe and Marks, 2004, p. 416). Carey (as cited in Hooghe and Marks, 2004, p. 416) has researched the effect of national attachment and national pride and concludes that there is a significant negative relation.

The relationship is thus paradoxical and country-specific. Nevertheless, it is possible to generalize about the relationship between national identity and public support for European integration to some extent (Hooghe and Marks, 2004, pp. 416-417). The results from Hooghe and Marks (2004, p. 417) show that the relationship between national identity and support for European integration is Janus-faced. Whether it has a negative or a positive effect, depends on “the extent to which national identity is exclusive or inclusive” (p. 417). If respondents view themselves as having an exclusive national identity, the effect on their support for European integration is negative. However, the relative explanatory power of national identity is higher than that of the economic explanation (Hooghe and Marks, 2004, pp. 418).

2.1.2 The impact of the Euro crisis on drivers for public support for European integration

Braun & Tausendpfund (2014) describe how the Euro crisis is theoretically expected to impact public opinion on the European Union and further integration (p. 233). The authors identify the European economic crisis as “one of the most far-reaching events in the last decades” (p. 231). Their main finding is “that the Euro crisis has undeniably an important impact on citizens’ support for the EU” (Braun and Tausendpfund, 2014, p. 242). During the Euro crisis, public support for the EU has declined. More interestingly for this specific research project, is the following argument made by Braun and Tausendpfund. They argue that “the crisis has strengthened the explanatory power of economic approaches” (Braun and Tausendpfund, 2014, p. 232). Whereas previous scholars, such as Hooghe and Marks (2004), Carey, and McLaren (as cited in Braun and Tausendpfund, 2014, p. 233) showed that identity-based approaches diminished the relevance of economic explanations, Braun and Tausendpfund show a change in this pattern.

Hobolt and Wratil (2015) also see this change in the drivers of public support for the Euro. Public support for the Euro is not the same as public support for European integration, but their article provides us valuable insights in how public opinion is shaped and the role of utilitarian considerations and national identity in this dynamic. They acknowledge the “ongoing debate between two alternative perspectives on public support for European integration: a utilitarian

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and an identity-based approach” (Hobolt and Wratil, 2015, p. 240). In their conclusion, the authors find that utility considerations have become more important to people in the EU during the EU crisis and that this change has taken place at the expense of identity-based drivers (Hobolt and Wratil, 2015, p. 252). They note that this an important addition to the ongoing debate about the drivers of public support for European integration, and that their findings oppose the postfunctionalist theory posed by Hooghe and Marks (as cited in Hobolt and Wratil, 2015, p. 252).

2.2 Hypotheses

Based on the literature review, this part of the chapter identifies the hypotheses that will be tested in this research project.

As described in the literature review, there has been an ongoing debate about the relative explanatory power of economic or utilitarian considerations and identity-based explanations of public support for European integration. In 2004, Hooghe and Marks showed the importance of identity-based explanations. At the height of the crisis, when economic issues became more salient, Braun and Tausendpfund (2014) showed that the explanatory power of utilitarian or economic considerations increased. Now that the crisis has ended and economic issues are less salient, I expect this to revert back to the “old situation”. In other words, looking at the drivers for public support of the European Union during the crisis and after the crisis, I expect the effect of economic considerations to decrease and the effect of national identity to increase. This leads to the following hypothesis:

H1: The explanatory power of identity-based drivers of public support for European integration on the individual level has increased, and the explanatory power of economic rationality-based drivers has decreased in the period since the crisis has ended.

For people who live in countries that have been hit hard by the crisis, the personal consequences have been more severe. If people for instance have lost their job, their house, or experienced a significant downfall in wealth, it is likely that economic considerations have a big effect in those countries specifically. This leads to the following hypothesis:

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H2: The strength of the relation between economic rationality-based considerations and public support for the European Union is relatively bigger for people who live in countries that have been more severely affected by the Euro crisis than in countries that have been affected by the Euro crisis less severely. The strength of this relationship thus correlates with the severity of the crisis.

As economics have become less salient, I thus expect the importance of economic considerations for public support for the EU to decline relatively to identity-based drivers. I expect identity-based drivers to have a bigger effect in countries that have seen the highest degrees of populist party popularity. Populist parties speak to feelings of nationalism and national identity and I expect this to make these issues more salient and thus a bigger consideration for people. Additionally, the political elites in these countries are often divided and research has shown that a division of the political elite increases the power of national identity to explain public support for the EU.

H3: The strength of the relation between national-identity based considerations and public support for the European Union is relatively bigger for people who live in countries that have a high degree of populist party popularity than in countries where these parties are less popular. The strength of this relationship thus correlates with the popularity of populist parties.

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Ch. 3: Research design and methodology

In this chapter, the research design and methodology of this research project will be described and justified. First, the research design will be described. I will explain why Eurobarometer survey waves are suitable datasets to answer this research question. I will explain the relevant variables that together form the model that is used in this research project to explain public support for the EU. Second. I will elaborate on the research methodology by explaining in detail the regression analysis that is used in this thesis.

3.1 Research design

3.1.1 Case selection: Eurobarometer survey waves

The European Commission started carrying out the Standard Eurobarometer survey waves in 1974. Approximately 1000 respondents per country answer the survey, making it a very large dataset that contains valuable information of all EU Member States. Every year, two Standard Eurobarometer surveys are carried out, providing us with the opportunity to study effects over time in a longitudinal study. Other scholars have also pointed out several advantages of using Eurobarometer survey data. Braun and Tausendpfund (2014, p. 235) note that the Eurobarometer provides recent data for all Member States, which is a big advantage in this field of research.

In order to see the effects over time, two Eurobarometer survey waves have been selected. The first one is Eurobarometer 73.4, from May 2010. This Eurobarometer was taken at the height of the economic crisis. Selecting this Eurobarometer has two advantages. First, it allows us to look at the drivers of public support for European integration during the crisis, which is part of the scope of this research project. Second, it will allow us to check the previous findings by other scholars. The second Eurobarometer that has been selected is Eurobarometer 83.3. This Eurobarometer was taken in May 2015, after the Euro crisis had ended. This allows us to look at changes in the period since the crisis has ended. Additionally, Eurobarometer 83.3 was taken after the European Parliament elections of 2014. This allows us to compare it to populist party popularity in that election. Taking these considerations into account, I deem this Eurobarometer highly appropriate for this research project. By using the Eurobarometer from 2010 and 2015, I will be able to compare the results and see the changes in the dynamic of drivers of public support for European integration. This will allow me to test the hypotheses and answer the research question.

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3.1.2 The model

Based on the theory, the following conceptual model is constructed. Public support for the EU is expected to be impacted by identity-based drivers and economic- and utilitarian-based drivers. These effects are expected to interact with the country in which respondents live, because the country of residence affects a person’s economic situation and feelings of national identity. Visually, the expected causal relationships between the variables are presented in figure 1.

Figure 1: Conceptual model identifying the expected causal relationships between identity based-drivers, economic- and utilitarian-based drivers and public support for the European Union.

3.1.2.1 The dependent variable

In this research project, the impact of economic rationality-based drivers and national identity-based drivers for public support for European integration is examined. In order to test this, public support for the European Union has to be operationalized. After operationalization, the concept can be measured in the data. Unfortunately, this is not straightforward using Eurobarometer data. We need indicators to distinguish between different types of EU support, as EU support is multidimensional (Boomgaarden et. al; Tausendpfund, as cited in Braun and Tausendpfund, 2014, p. 235). However, such indicators are not asked in a consistent manner,

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preventing us from comparing the different Eurobarometer survey waves. Therefore, public support for the EU is operationalized in this project by using the following question from the Eurobarometer: “In general, does the European Union conjure up for you a very positive, fairly positive, neutral, fairly negative, or very negative image?” (European Commission, 2012). This question is answered on a 5-point scale: “(1) Very positive; (2) Fairly positive; (3) Neutral; (4) Fairly negative; (5) Very negative” (European Commission, 2012). The exact same question was asked in both Eurobarometer 73.4 and Eurobarometer 83.3 (European Commission, 2012; European Commission, 2018).

This is not a perfect, multi-dimensional indicator of public support for the EU, but as it is consistently available in the selected survey waves, this question is used in this research project as “a proxy for citizens’ general support for the EU” (Braun and Tausendpfund, 2014, p. 235).

3.1.2.2 The independent variables

In the theoretical framework, two drivers of public support for the EU have been identified: economic rationality-based drivers and national identity-based drivers. Both of these concepts need to be operationalized in order to be measured in the data.

To operationalize national identity, the following question from the Eurobarometer is used: “In the near future, do you see yourself as...?” The respondents can answer this question on a 4-point scale: “(1) NATIONALITY only; (2) NATIONALITY and European; (3) European and NATIONALITY; (4) European only” (European Commission, 2012). A question that is almost the same is also asked in Eurobarometer 83.3 (European Commission, 2018). The only difference is that Eurobarometer 83.3 leaves out “in the near future”. As I don’t expect this to affect the results in any meaningful way, I believe this question is suitable to be used as a proxy for ‘national identity’ and can be used to compare the two Eurobarometer survey waves. This question is widely used and considered to be “the gold standard for measuring national identity by many scholars” (e.g. Hooghe and Marks, as cited in Hobolt and Wratil, 2015, p. 247). The second concept that needs to be operationalized is ‘economic rationality-based drivers’. To operationalize this, the following question from Eurobarometer 73.4 is used: “How would you judge the current financial situation of your household?” This question can be answered on a 4-point scale: “(1) Very good; (2) Rather good; (3) Rather bad; and (4) Very bad” (European Commission, 2012). The advantage of using this variable is that, just like national identity, it is

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answered on a 4-point scale. By using two variables that are both measured at a 4-point scale, it is possible to compare the strength of the coefficients. As I am interested in the relative explanatory power of these variables, this is necessary to interpret the results. It is also measured on the individual level. The question is asked in 2010 and in 2015 (European Commission, 2018).

3.1.2.3 Interaction effect of country

In order to take into account that the effect of economic and utilitarian considerations and national identity-based drivers may differ per country, the model includes the interaction effect of these variables.

3.1.2.4 Control variables

To interpret the relationship correctly and confirm that the relationship holds with the inclusion of additional variables, age and sex are used as control variables. The inclusion of these variables allows us to gather additional information about the relationship. According to (Healey, 2012, p. 407), multivariate techniques will increase information about the relationship and enhance our understanding of that relationship.

3.2 Research method

3.2.1 Multiple regression

“Multiple regression is a statistical method for studying the relationship between a single dependent variable and one or more independent variables” (Allison, 1999, p. 1). A multiple regression can be used for prediction and causal analysis. In this thesis, multiple regression will be used as a method for causal analysis. In a causal analysis, “the independent variables are regarded as causes of the dependent variable” (Allison, 1999, p. 2). The goal of this study is to find out whether the independent variables identified in the previous chapter affect the dependent variable. Additionally, we will look at the strength of this effect (Allison, 1999, p. 2).

The benefit of using a multiple regression for this study, is that the method “separates the effects of independent variables on the dependent variable so that you can examine the unique contribution of each variable” (Allison, 1999, p. 3). This allows us to look at economic considerations and national identity and distinguish between the effect of these two factors.

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Allison argues that it is reasonable to use a linear equation when the true form of a relationship is unknown (Allison, 1999, p. 6). Strictly speaking, the variables used in a multiple regression should be measured at the interval scale. However, variables measured at the ordinal scale are often used in a multiple regression (Allison, 1999, p. 10).

A multiple regression enables us to control for other variables, which will be done in the models in this thesis project to ensure that the effect of the independent variable is not caused by a different variable. For sex, a dummy variable is created. Age is also included in the regression. Furthermore, the model controls for the country a respondent lives in. In order to incorporate country as a category in our model, we use a Generalized Linear Model.

3.2.2 Pearson Correlation

In the analysis, we will also test the relationship between economic considerations and the severity of the crisis by examining the correlation coefficient. To do so, we will make use of scattergrams and regression lines (Healey, 2012, p. 368). If these indicate a possible relationship, the correlation coefficient will be tested. Pearson’s r is a suitable test for association between variables measured at the interval-ratio level (Healey, 2012, p. 378).

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Ch. 4: Results

In this chapter, the results of the multiple regression analyses and correlation tests will be discussed. Different parts of the model will be displayed and highlighted in order to answer the hypotheses systematically. The full models and results are included in the appendixes.

4.1.1 Hypothesis 1: Change in economic considerations and national-identity based considerations in 2010 – 2015

To look at the effects of economic considerations and national-identity based considerations on publics support for the European Union, I first present the results of a simplified model. This model includes the main effect of the two independent variables: financial situation of household and national identity. Age, sex, and country are included as control variables. For clarity, I only present the coefficients of the independent variable in this table. For ease of interpretation and comparison, the results in the table are rounded off to two decimals. The full results of the regression are included in appendix A.

Table 1: Simple regression model including the two independent variables, 2010 – 2015.

All effects Eurobarometer survey

year

2010 2015

Variable B B

intercept 2.43 2.71

Financial situation of household .24*** .24***

National identity -.29*** -.37*** Age _✔ ✔ Sex ✔ ✔ Country ✔ ✔ NOTE: B = coefficient N = 25076 N = 26564 * p < .05; **p < .01; *** p <.001

The results show that both independent variables are significantly related to public support for the European Union. Furthermore, the direction of the relation is as expected. The coefficient for ‘financial situation of household’, that is being used as a proxy for economic considerations is 0.24 in 2010. This is a positive relation, meaning that an increase in the score on ‘financial situation of household’ leads to an increase in the score of public support for the European Union. As both variables are ranked from low (bad) to high (good), this means that when one’s financial situation declines, their opinion on the EU is estimated to be more negative. For

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national identity, the coefficient in 2010 is -0.29. This relation is also significant. An increase in the score for national identity, means a decrease in the score of public support for the European Union. In other words, when one considers themselves to be more European, their opinion on the EU is estimated to be more positive. These results hold when they are being controlled for confounding variables, in this case: age, sex, and country. As both independent variables show a significant relationship, I reject the null-hypothesis and conclude that in 2010 economic considerations and national-identity-based considerations both have an effect on a person’s public support for the European Union.

To see whether the strength of this relationship has changed between 2010 and 2015, we compare the coefficients of both years. Both financial situation of household and national identity show a significant relation to public support on the European Union. The direction of the relationship is the same, meaning that these results can be interpreted in the same was as described in the previous paragraph. Interestingly, and in line with what I have theorized before, the strength of the coefficient of national identity has become bigger in 2015 than it was in 2010. It has increased from -0.29 (2010) to -0.37 (2015). The strength of financial situation of household has remained the same. Hypothesis 1 read: The explanatory power of identity-based

drivers of public support for European integration on the individual level has increased, and the explanatory power of economic rationality-based drivers has decreased in the period since the crisis has ended. We can thus accept this hypothesis partially. First of all, both

identity-based drivers of public support for the European Union and economic rationality-identity-based drivers have a significant effect. This accounts for 2010 and 2015. The strength of identity-based drivers of public support for the EU has indeed increased in the period since the crisis has ended. The strength of economic rationality-based drivers has not decreased but rather remained the same.

4.1.2 Hypothesis 2: The interaction effect of economic considerations per country

To look at the effects of economic considerations and national-identity based considerations on publics support for the European Union per country, I will now present the results of a more complicated model including the interaction effect of independent variables per country. The model includes the interaction effect of the two independent variables: financial situation of household and national identity with country. Age, sex, and country are included as control variables. For clarity, I will now only present the coefficients of the interaction effect of

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financial household situation and country in table 2 to examine the second hypothesis. In the next chapter, I will show the coefficients for the other independent variable: national identity. For ease of interpretation and comparison, the results in the table are rounded off to two decimals. The full regression model is included in appendix B.

Table 2: Regression model with the interaction effect for country and the financial situation of household, 2010 – 2015.

year

2010 2015

Variable B B

Austria * Financial Situation of Household .21*** .31***

Belgium * Financial Situation of Household .18*** .18***

Bulgaria * Financial Situation of Household .26*** .22***

Cyprus * Financial Situation of Household .25*** .28***

Croatia * Financial Situation of Household .27***

Czech Republic * Financial Situation of Household .32*** .28***

Germany East * Financial Situation of Household .30*** .28***

Germany West * Financial Situation of Household .34*** .23***

Denmark * Financial Situation of Household .12** .16***

Estonia * Financial Situation of Household .19*** .20***

Spain * Financial Situation of Household .24*** .25***

Finland * Financial Situation of Household .13** .18***

France * Financial Situation of Household .29*** .19***

Great Britain * Financial Situation of Household .09* .17***

Northern Ireland * Financial Situation of Household .22* .29**

Greece * Financial Situation of Household .26*** .24***

Hungary * Financial Situation of Household .23*** .21***

Ireland * Financial Situation of Household .32*** .33***

Italy * Financial Situation of Household .33*** .43***

Lithuania * Financial Situation of Household .23*** .20***

Luxembourg * Financial Situation of Household .26*** .18**

Latvia * Financial Situation of Household .15*** .22***

Malta * Financial Situation of Household .46*** .22**

The Netherlands * Financial Situation of Household .13** .23***

Poland * Financial Situation of Household .26*** .21***

Portugal * Financial Situation of Household .35*** .21***

Romania * Financial Situation of Household .20*** .11**

Sweden * Financial Situation of Household .15*** .17***

Slovenia * Financial Situation of Household .24*** .25***

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Age _✔ ✔

Sex ✔ ✔

Country ✔ ✔

NOTE: B = coefficient N = 25076 N = 26564

* p < .05; **p < .01; *** p <.001

The table shows that the interaction effect per country is significant in all countries. This is the case for both 2010 and 2015. Furthermore, the results hold when they are being controlled for age, sex, and country. There is a lot of variation in the strength of the coefficients for the various countries. In this chapter, we will explore whether these differences are related to the severity of the crisis. First, we will look whether the coefficients of 2010 and 2015 are correlated. Table 3 shows the results of the Pearson correlation that has been applied to the results of the regression.

Table 3: Correlation for coefficients of financial household, 2010 – 2015.

Table 3 shows that there is a correlation between the coefficients of financial situation of household in 2010 and 2015. This correlation is 0.455 and significant.

In order to see whether the strength of the coefficients of the financial situation of the household is related to the severity of the crisis in a particular country, data from The World Bank (2019a; 2019b). has been gathered. The data represents the annual growth (or decline) of the GDP. Data has been collected for 2009 and 2014 and is presented in table 4.

Correlations Coefficients financial situation household 2010 Coefficients financial situation household 2015 Coefficients financial situation household 2010 Pearson Correlation 1 .455* Sig. (2-tailed) .013 N 29 29 Coefficients financial situation household 2015 Pearson Correlation .455* ₁ Sig. (2-tailed) .013 N 29 29

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Table 4: GDP growth (% annually), 2009 – 2014.

Country GDP growth 2009 GDP growth 2014

Austria -3.8% +0.7% Belgium -2.3% +1.3% Bulgaria -3.6% +1.8% Cyprus -2.0% -1.3% Croatia -7.3% -0.1% Czech Republic -4.8% +2.7% Germany East -5.6% +2.2% Germany West -5.6% +2.2% Denmark -4.9% +1.6% Estonia -14.7% +2.9% Spain -3.6% +1.4% Finland -8.3% -0.6% France -2.9% +1.0% Great Britain -4.2% +2.9% Northern Ireland -4.2% +2.9% Greece -4.3% +0.7% Hungary -6.6% +4.2% Ireland -4.6% +8.8% Italy -5.5% +0.1% Lithuania -14.8% +3.5% Luxembourg -4.4% +4.3% Latvia -14.4% +1.9% Malta -2.5% +8.1% The Netherlands -3.8% +1.4% Poland +2.8% +3.3% Portugal -3.0% +0.9% Romania -5.9% +3.4% Sweden -5.2% +2.6% Slovenia -7.8% +3.0% Slovakia -5.4% +2.8%

Table 4 shows the GDP growth in 2009 and 2014. The data for 2009 shows the situation before the Eurobarometer survey wave of 2010 that is being used in this thesis. As expected, the growth rates in 2009 are negative for almost all countries. This was during the height of the Euro crisis. In 2014, before the Eurobarometer survey wave of 2015 that is used in this research project, almost all countries show a positive growth rate. By testing whether there is a relation between these growth rates and the coefficients for economic considerations, I will examine whether the severity of the crisis is related to the strength of the relationship between economic

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considerations and public support for the European Union. Table 5 shows the coefficient for the interaction effect of financial situation of household per country in 2010 and the GDP growth in that country in 2009. Table 6 shows the results of the Pearson correlation test.

Table 5: Coefficient for the interaction effect of financial situation of household and GDP growth per country, 2009.

Eurobarometer survey 2010

Country Coefficient for the interaction effect of financial situation of household per country GDP growth in 2009 Austria .21*** -3.8% Belgium .18*** -2.3% Bulgaria .26*** -3.6% Cyprus .25*** -2.0%

Croatia No information available in

Eurobarometer survey wave. -7.3%

Czech Republic .32*** -4.8% Germany East .30*** -5.6% Germany West .34*** -5.6% Denmark .12** -4.9% Estonia .19*** -14.7% Spain .24*** -3.6% Finland .13** -8.3% France .29*** -2.9% Great Britain .09* -4.2% Northern Ireland .22* -4.2% Greece .26*** -4.3% Hungary .23*** -6.6% Ireland .32*** -4.6% Italy .33*** -5.5% Lithuania .23*** -14.8% Luxembourg .26*** -4.4% Latvia .15*** -14.4% Malta .46*** -2.5% The Netherlands .13** -3.8% Poland .26*** +2.8% Portugal .35*** -3.0% Romania .20*** -5.9% Sweden .15*** -5.2% Slovenia .24*** -7.8% Slovakia .32*** -5.4%

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Table 6: Correlation for coefficients of financial household and GDP growth, 2009 – 2010. Correlations Coefficients financial situation of household GDP growth Coefficients financial situation of household Pearson Correlation 1 .269 Sig. (2-tailed) .158 N 29 29 GDP growth Pearson Correlation .269 1 Sig. (2-tailed) .158 N 29 29

Table 6 shows that the results of the Pearson correlation test are not significant. We can thus

not reject the null-hypothesis. We have not found evidence for a relationship between the

severity of the crisis and the strength of the coefficient for economic considerations in 2010. We will now test whether this has changed since the crisis has ended. Table 7 shows the coefficient for the interaction effect of financial situation of household per country in 2015 and the GDP growth in that country in 2014. Table 8 shows the results of the Pearson correlation test.

Table 7: Coefficient for the interaction effect of financial situation of household and GDP growth per country, 2014.

Country Coefficient for

the interaction effect of financial situation of household per country GDP growth in 2014 Austria .31*** +0.7% Belgium .18*** +1.3% Bulgaria .22*** +1.8% Cyprus .28*** -1.3% Croatia .27*** -0.1% Czech Republic .28*** +2.7% Germany East .28*** +2.2%

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Germany West .23*** +2.2% Denmark .16*** +1.6% Estonia .20*** +2.9% Spain .25*** +1.4% Finland .18*** -0.6% France .19*** +1.0% Great Britain .17*** +2.9% Northern Ireland .29** +2.9% Greece .24*** +0.7% Hungary .21*** +4.2% Ireland .33*** +8.8% Italy .43*** +0.1% Lithuania .20*** +3.5% Luxembourg .18** +4.3% Latvia .22*** +1.9% Malta .22** +8.1% The Netherlands .23*** +1.4% Poland .21*** +3.3% Portugal .21*** +0.9% Romania .11** +3.4% Sweden .17*** +2.6% Slovenia .25*** +3.0% Slovakia .34*** +2.8%

Table 8: Correlation for coefficients of financial household and GDP growth, 2014 – 2015. Correlations Coefficients financial situation of household GDP growth Coefficients financial situation of household Pearson Correlation 1 -.063 Sig. (2-tailed) .742 N 30 30

GDP growth Pearson Correlation -.063 1

Sig. (2-tailed) .742

N 30 30

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relationship between the severity of the crisis and the strength of the coefficient for economic considerations in 2015.

4.1.3 Hypothesis 3: The interaction effect of national identity per country

This part of the analysis is employing the regression model as the previous part, but for clarity, I will now only present the coefficients of the interaction effect of national identity and country in table 9 to examine the third hypothesis. For ease of interpretation and comparison, the results in the table are rounded off to two decimals. The full regression model is included in appendix B.

Table 9: Regression model with the interaction effect for country and national identity, 2010 – 2015.

year

2010 2015

Variable B B

Austria * National Identity -.56*** -.46***

Belgium * National Identity -.19*** -.26***

Bulgaria * National Identity -.43*** -.67***

Cyprus * National Identity -.25*** -.50***

Croatia * National Identity -.49***

Czech Republic * National Identity -.35*** -.49***

Germany East * National Identity -.39*** -.33***

Germany West * National Identity -.32*** -.34***

Denmark * National Identity -.29*** -.24***

Estonia * National Identity -.20*** -.20***

Spain * National Identity -.16*** -.18***

Finland * National Identity -.25*** -.35***

France * National Identity -.43*** -.39***

Great Britain * National Identity -.56*** -.57***

Northern Ireland * National Identity -.33*** -.45***

Greece * National Identity -.41*** -.82***

Hungary * National Identity -.33*** -.49***

Ireland * National Identity -.26*** -.22***

Italy * National Identity -.27*** -.29***

Lithuania * National Identity -.17*** -.45***

Luxembourg * National Identity -.21*** -.23***

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Malta * National Identity -.34*** -.18***

The Netherlands * National Identity -.24*** -.42***

Poland * National Identity -.36*** -.44***

Portugal * National Identity -.23*** -.36***

Romania * National Identity -.13*** -.43***

Sweden * National Identity -.38*** -.39***

Slovenia * National Identity -.25*** -.32***

Slovakia * National Identity -.32*** -.48***

Age _✔ ✔

Sex ✔ ✔

Country ✔ ✔

NOTE: B = coefficient N = 25076 N = 26564

* p < .05; **p < .01; *** p <.001

The table shows that the interaction effect per country is significant in all countries. This is the case for both 2010 and 2015. Furthermore, the results hold when they are being controlled for age, sex, and country. There is a lot of variation in the strength of the coefficients for the various countries. In this chapter, we will explore whether these differences are related to popularity of populist parties in each country. First, we will look whether the coefficients of 2010 and 2015 are correlated. Table 10 shows the results of the Pearson correlation that has been applied to the results of the regression.

Table 10: Correlation for coefficients of national identity, 2010 – 2015. Correlations Coefficients national identity 2010 Coefficients national identity 2015 Coefficients national identity 2010 Pearson Correlation 1 .434* Sig. (2-tailed) .019 N 29 29 Coefficients national identity 2015 Pearson Correlation .434* ₁ Sig. (2-tailed) .019 N 29 29

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Table 3 shows that there is a correlation between the coefficients of national identity in 2010 and 2015. This correlation is 0.434 and significant.

In order to see whether the strength of the coefficients of national identity is related to the popularity of populist parties, the coefficients are compared with data about populist party popularity in each country. The populist party popularity is expressed as a percentage of votes for populist parties in the 2009 and 2014 European Parliament elections. This is suitable, because these elections took place before the Eurobarometer survey waves that are used in this research project. This data is acquired from a dataset constructed by Luengo-Cabrera (2018). The author categorized populist parties and gathered the election results from the European Election Database. The results were then plotted for 2009 and 2014. I digitized this plot to derive the vote share percentages. This method is fairly accurate, but it must be noted that these numbers are estimations nonetheless. The results are shown in table 11.

Table 11: Populist party popularity in the 2009 and 2014 European Parliament elections per country.

Country Populist party vote share

in 2009 EP elections

Populist party vote share in 2014 EP elections Austria 17.3% 19.7% Belgium 14.1% 4.0% Bulgaria 36.2% 47% Cyprus 34.8% 33.6% Croatia 5.6% 3.3% Czech Republic 15.3% 35.3% Germany East 7.5% 15.3% Germany West 7.5% 15.3% Denmark 22.5% 34.4% Estonia 26.5% 26.4% Spain 3.5% 17.8% Finland 15.5% 22% France 23.6% 35.3% Great Britain 16.4% 27.5% Northern Ireland 16.4% 27.5% Greece 20.1% 45.3% Hungary 70.9% 66.6% Ireland 13.8% 16.8% Italy 13.6% 34.9% Lithuania 12% 20.8% Luxembourg 3.3% 5.8%

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Latvia 7.3% 14.1% Malta The Netherlands 24.7% 29.7% Poland 27.7% 39.8% Portugal 22.4% 19.2% Romania 8.6% 2.7% Sweden 8.8% 15.9% Slovenia 2.8% 9.4% Slovakia 5.4% 12.6%

Table 11 shows that there is a lot of variation in the popularity of populist parties in the different countries. Both in 2009 and 2014 there are countries with very high percentages of populist parties and very low percentages of populist parties. By testing whether there is a relation between these percentages and the coefficients for national identity, I will examine whether the popularity of populist parties is related to the strength of the relationship between national identity and public support for the European Union. Table 12 shows the coefficient for the interaction effect of national identity per country in 2010 and the popularity of populist parties in that country in 2009. Table 13 shows the results of the Pearson correlation test.

Table 12: Coefficients for the interaction effect of national identity and populist party popularity per county, 2009 – 2010.

Country Coefficient for the

interaction effect of national identity per country Populist party vote share in 2009 EP elections Austria -.56*** 17.3% Belgium -.19*** 14.1% Bulgaria -.43*** 36.2% Cyprus -.25*** 34.8% Croatia 5.6% Czech Republic -.35*** 15.3% Germany East -.39*** 7.5% Germany West -.32*** 7.5% Denmark -.29*** 22.5% Estonia -.20*** 26.5% Spain -.16*** 3.5% Finland -.25*** 15.5% France -.43*** 23.6% Great Britain -.56*** 16.4%

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Northern Ireland -.33*** 16.4% Greece -.41*** 20.1% Hungary -.33*** 70.9% Ireland -.26*** 13.8% Italy -.27*** 13.6% Lithuania -.17*** 12% Luxembourg -.21*** 3.3% Latvia -.12** 7.3% Malta -.34*** The Netherlands -.24*** 24.7% Poland -.36*** 27.7% Portugal -.23*** 22.4% Romania -.13*** 8.6% Sweden -.38*** 8.8% Slovenia -.25*** 2.8% Slovakia -.32*** 5.4%

Table 13: Correlation for coefficients of national identity and populist party popularity, 2009 – 2010. Correlations Coefficients national identity Populist party popularity Coefficients national identity Pearson Correlation 1 -.198 Sig. (2-tailed) .312 N 28 28

Populist party popularity Pearson Correlation -.198 1

N 28 28

not reject the null-hypothesis. We have not found evidence for a relationship between the

popularity of populist parties and the strength of the coefficient for national identity in 2010. We will now test whether this has changed since the crisis has ended and now that populist parties have become more popular. Table 14 shows the coefficient for the interaction effect of national identity per country in 2015 and the popularity of populist parties in that country in 2014.

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Table 14: Coefficients for the interaction effect of national identity and populist party popularity per county, 2014 – 2015.

Country Coefficient for the

interaction effect of national identity per country Populist party vote share in 2014 EP elections Austria -.46*** 19.7% Belgium -.26*** 4.0% Bulgaria -.67*** 47% Cyprus -.50*** 33.6% Croatia -.49*** 3.3% Czech Republic -.49*** 35.3% Germany East -.33*** 15.3% Germany West -.34*** 15.3% Denmark -.24*** 34.4% Estonia -.20*** 26.4% Spain -.18*** 17.8% Finland -.35*** 22% France -.39*** 35.3% Great Britain -.57*** 27.5% Northern Ireland -.45*** 27.5% Greece -.82*** 45.3% Hungary -.49*** 66.6% Ireland -.22*** 16.8% Italy -.29*** 34.9% Lithuania -.45*** 20.8% Luxembourg -.23*** 5.8% Latvia -.19*** 14.1% Malta -.18*** The Netherlands -.42*** 29.7% Poland -.44*** 39.8% Portugal -.36*** 19.2% Romania -.43*** 2.7% Sweden -.39*** 15.9% Slovenia -.32*** 9.4% Slovakia -.48*** 12.6%

Looking at the results in table 14, there seems to be a correlation between the strength of the coefficients for national identity and the popularity of populist parties. To examine this relationship further, I provide a scatterplot of the data with the popularity of populist parties on

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the X-axis and the coefficients for national identity on the Y-axis. To interpret these results more easily, the coefficients of the interaction effect have been made positive for the next analysis. This does not affect the strength of the correlation, but it allows us to visualize and describe the relationship between the strength of the coefficients for national identity and populist party popularity better.

Figure 2: Scatterplot of the coefficients for national identity in 2010 and populist party popularity in 2014.

The scatterplot in figure 2 shows that there indeed seems to be a relationship between the strength of the coefficients for national identity and populist party popularity. After adding a regression line to the scatterplot, it becomes clear that this relationship is linear. To examine the relationship further, table 15 provides the results of a Pearson Correlation test for these two variables.

Table 15: Correlation for coefficients of national identity and populist party popularity, 2014 – 2015. Correlations Coefficients national identity Populist party popularity Pearson Correlation 1 .473**

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Coefficients national identity

N 29 29

Populist party popularity Pearson Correlation .473** ₁

N 29 29

**. Correlation is significant at the 0.01 level (2-tailed).

Table 15 confirms that there is a correlation between the coefficients of national identity and the popularity of populist parties in 2015. This correlation is 0.473 and significant at the 0.01 level. There is a positive relationship between the percentage of people that vote for populist parties and the strength of national-identity in shaping public support for the European Union. We can thus reject the null-hypothesis and accept alternative Hypothesis 3: The strength of the

relation between national-identity based considerations and public support for the European Union is relatively bigger for people who live in countries that have a high degree of populist party popularity than in countries where these parties are less popular. The strength of this relationship thus correlates with the popularity of populist parties.

4.2 Summary

In this chapter, the results of two regression models and a number of correlation tests have been discussed. The simple regression model provided evidence for an effect of both national identity and economic considerations on public support for the European Union in 2010 and 2015. The effect of economic considerations remained the same, while the strength of the effect of national identity is larger in 2015 than it was in 2010.

Examining this relationship in more detail, a second regression model has been discussed which includes the interaction effect at the country level. We first looked at economic considerations. The second model does not provide evidence for a relationship between the strength of the coefficients for economic considerations in shaping public support for the European Union and the severity of the crisis in that country.

Second, we examined whether there is a relationship between populist party popularity and the strength of the coefficient of national identity in shaping public support for the European Union. We found no evidence of that relationship in 2010, but we found a significant correlation in 2015.

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Ch. 5: Conclusion

5.1 Answer to the research question

This thesis set out to make a contribution to the ongoing debate about drivers of public support for the European Union. It identified two main explanations of public support for the European Union: economic or utilitarian-based drivers and national identity-based drivers. Observing fluctuations in the relative importance of these two explanations over the years, I wanted to look at more recent years and see which circumstances are related to these fluctuations. This led to the following research question: ‘How has the relative explanatory power of

identity-based and economic rationality-identity-based drivers of public support for European integration changed in the years after the Euro crisis ended?’

To answer this research question, I provided a literature review with the current academic views on this topic. This literature review was used to theorize that both economic considerations and national identity are important explanations of public support for the European Union. However, based on the theory we expected the strength of these explanations to change relatively to each other over the years. We identified the Euro crisis and the rise of populist parties as circumstances that could possibly be related to the strength of the relationship between economic considerations and national identity and public support for the European Union.

The analysis found evidence to partially accept the first hypothesis. As expected, both economic considerations and national identity are related to public support for the European Union. This accounts for both 2010 and 2015. Furthermore, the strength of the relationship between national identity and public support for the European Union has indeed increased. In 2015, the effect is larger than it was in 2010. However, we also found that the strength of economic considerations remained the same. Contrary to what was expected, the effect of economic considerations has not become smaller after the economy started doing better.

We then looked at the effect in more detail by including an interaction effect at the country level. The analysis has found no evidence to accept the second hypothesis. The correlation test shows no significant relationship between the severity of the crisis and the strength of economic considerations in shaping public support for the European Union.

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Interestingly, we did find evidence for the third hypothesis. The importance of national identity in shaping public support for the European Union has grown between 2010 and 2015. In 2015, the strength of this relationship correlates significantly with the popularity of populist parties in a country.

5.2 Relation of the research findings to the existing body of knowledge

As expected, economic-based and national identity-based considerations are both important explanators of public support for the EU. This confirms previous findings by other scholars as described in the literature review. However, contrary to what was hypothesized, the strength of these explanations has not changed in the way that was expected. The analysis shows that the importance of national identity has grown, while the strength of economic considerations remained the same. In the literature, these two explanations are often portrayed as rivals. In 2004, Hooghe and Marks argued that national identity was a relatively more important explanation of public support for the European Union. Hobolt and Wratil argued in 2015 that economic considerations had become more important at the cost of national identity because of the crisis. This thesis made a contribution to this debate by including more recent data and by finding that the importance of economic considerations has remained stable, even years after the crisis, while the importance of national identity has grown.

Based on previous research, I hypothesized that the importance of economic considerations and national identity-based considerations would correlate with respectively the severity of the crisis and the popularity of populist parties. This correlation has not been found for the severity of the crisis and economic considerations, but national identity and populist party popularity correlate in 2015. Interestingly, national identity has become a more important explanation for public support for the European and now significantly correlates with populist party popularity. This resonates with findings from Hooghe and Marks (2004) that a division of the political elite increases the explanatory power of national identity for public support for the EU.

5.3 Limitations of this research

There are also some limitations to this research project. The variables that are used as proxies for economic-based considerations and national identity-based considerations are limited. They are based on one Eurobarometer survey question. Although the choice of these questions is

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founded in theory, the indicators could have been stronger if they would have included more questions to capture economic considerations and feelings of national identity. Ideally, one would construct an index or more complex variables consisting of more Eurobarometer questions to operationalize these concepts. Additionally, the analysis is now based on two points in time. The analysis could have profited from more points in time to capture more nuanced changes in the drivers of public support for the European Union.

5.4 Possibilities for further research

The relative importance of economic-based considerations and national identity-based considerations in shaping public support for the EU remains contested. It is therefore a highly interesting subject for further research. Further research could use new Eurobarometer data to examine this relationship further and in more detail by including more variables. Additionally, one could pay special attention to the rise of populist parties and the importance of national identity in shaping public support for the European Union. This thesis found a significant relationship between the two and it is interesting to see how this develops over time.

Economic considerations and national identity as drivers of public support for the European Union: a comparison including the economic and political context in 2010 and 2015

ECONOMIC CONSIDERATIONS AND NATIONAL IDENTITY AS

DRIVERS OF PUBLIC SUPPORT FOR THE EUROPEAN UNION:

A COMPARISON INCLUDING THE ECONOMIC AND POLITICAL

CONTEXT IN 2010 AND 2015

by M.R.M. Soomers

Abstract

Acknowledgements

Table of contents

Ch. 1: Introduction

Ch. 2: Literature review

Ch. 3: Research design and methodology

Ch. 4: Results

Ch. 5: Conclusion