Trust Thy Institutions: Importance of Trust in Political institutions in Mediating Public

Attitudes Towards European Integration and Immigration

Elif Naz Kayran

PhD. Candidate, IHEID - Graduate Institute Geneva

Draft Prepared for Presentation in session 6.1 “The European Project and European Values:

Convergence or Divergence II” at the 3rd ESS Conference, 13-15 July 2016, Lausanne,

Switzerland

ABSTRACT

What are the determinants of the growing Euroscepticism and anti-immigration attitudes in

European societies? The aim of this study is to answer this important societal question by

using European Social Survey data from waves 4, 6 and 7. This is a crucial and timely

question to ask, as the apparent lack of harmonization in key areas of EU governance is

argued to be the cause for some of the biggest crises facing Europe such as the financial and

refugee crises. In the post Eurozone crisis context, policy-proposals from the EU level are

facing strong resistance from the member states in a wide range of issue areas. In addition to

national level opposition, there is an emerging anti-EU voting group within the European

Parliament. There are strong negative positions taken with regards to further integration and

admission of more immigrants and humanitarian refugees. The paper will argue that trust in

European institutions is a crucial determinant factor regarding attitudes towards outwards

integration. This argument will be tested by using two types of out groups in the form of

immigrants and further Europeanization of policy areas. Overall, this study will contribute to

both the literature on public attitude towards Europeanization and immigration, but also to

European governance choices and policy-making in EU level through testing the extent of

importance of institutional trust for the future of European integration and immigration flows.

Key Words: Public Attitude; Euroscepticism; Anti-Immigration; Institutional Trust;

European Parliament.

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I. Introduction

To what extent trust in European institutions can predict individual attitudes towards

openness to outwards integration in the contexts of economic crisis and recovery? This is a

timely question to ask as the lack of motivation for openness to integration with European

Union (EU) and other countries in key areas of governance is arguably one of the most

important hurdles facing European member states with regards to finding durable solutions to

crises such as financial control, fiscal convergence, lagging growth and labour market

shortages (Drudi et.al.2012). In addition to national level opposition and the increased voting

behaviour for radical right parties or parties that encompass agendas that include Eurosceptic

politics and policies that target out-groups (i.e. immigrants) negatively, there is an emerging

anti-EU voting group within the European Parliament pushing forward right-wing politics

(Treib 2014).

The puzzle of this research paper stems from the observation that there has been a

steep increase in Euroscepticism and anti-immigration attitude in Europe after the Eurozone

crisis (Serricchio et.al. 2013). Interestingly though, studies have shown that there is a

recovery of positive feelings towards EU integration and immigration taking off from 2013

and keeping on an increasing trend through 2015 (de Vries and Hoffman 2016). It has been

shown that much of the blame for the negative externalities of the crisis has been placed to

European institutions and to their inability to contain the crisis and the following austerity

measures that caused serious societal consequences in several EU member countries (Arnold

et.al. 2012; Armingeon and Guthmann 2014; Torcal 2014). Recently Dotti Sani and Magistro

found that the worst declines in trust in European institutions have been experienced in

countries that experienced the most economic and social problems from the Eurozone crisis

and the subsequent recovery plans (2016). Accordingly, there is more increase in negative

attitudes towards openness (both integration and immigration) in countries where the effects

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of the crisis have been felt the most (Freedman 2012). Therefore, the context of crisis and

recovery of the Eurozone crisis present a fruitful instance to see how trust in European

institutions could be affecting individual attitudes towards openness to outwards integration.

The main explanatory variable of this study will be trust in European institutions.

Trust in other political institutions will, also, be controlled for using ESS data. Response

variables will be public attitude towards immigration and public attitude towards further

European integration. The paper will begin with a discussion of its conceptual framework,

theory and lay out the hypotheses. Next, a brief analytical review of the literature will be

presented, followed the methodology employed in this paper. Descriptive and statistical

results are presented in two separate sub sections, which will focus on the two outcome

indicators of the outwards integration. Finally, implications of these results and future steps

that are planned for this research will be discussed.

II. Conceptual Framework and Theory

It has been shown, in the literature, that there is a robust and significant relationship between

institutions and trust (Putnam 1993; Rothstein and Uslaner 2005). In addition, it has been

found that there are different types of trust in societies that mitigate important societal

outcomes such as the strength of democracy, social capital, equality, and attitudes towards

redistribution (Uslaner 2002). Building on previous research on the topic, Crepaz shows that

the effects of generalized (universal) trust v. particularized trust stem from different

institutional and social capabilities that have important outcomes in the countries and regions

they appear in (2008, 93-133). Taking stock from this literature on trust, institutions, and

attitudes towards the “other” relative to the natives, the theory of this paper posits that trust in

EU institutions have a significant effect on attitudes towards outwards integration in

European countries.

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An important issue to resolve in openness is how to capture this concept. The most

common two indicators of testing for individual attitudes for openness within member states

can argued to be attitudes towards European integration which will be named here “openness

to Europe” and attitudes towards accepting more foreigners in the form of immigration which

will be named here “openness to non-Europe”. For the purpose of this research it is important

to make two clarifications on the definitions of these concepts. Firstly, “openness to non-

Europe” targets attitudes towards immigration, not immigrants. Anti-immigrant sentiment

raises issues regarding ethnic saliency, discrimination, immigrant integration and access to

rights of immigrants in the country (Quillian 2006; Kunovich 2002). Attitudes towards

immigration more aptly focus on questions regarding openness in the sense that is used in the

paper as admission (Ceobanu and Escandell 2010, 313).

Secondly, the attitudes towards European integration have been a contested field as

well within the literature of Euroscepticism. Several authors have argued that attitudes

towards further European integration encompass attitudes towards the European project itself,

individual resentment to European citizens or negative opinions towards the values and

structure of the European Union (Boomgarden et.al. 2010; Kopecky and Mudde 2002). This

definition has been referred to as “hard Euroscepticism” whereas the definition of attitudes

towards European integration as “soft- Euroscepticism” captures opposition or dissatisfaction

with policy directions taken and the Europeanization of policies that should have been kept

nationalized (Leconte 2015; Taggart 1998). It is argued here that a soft Euroscepticism

conceptualization would target how individuals feel about openness towards Europe more

aptly than the alternatives in the literature.

III. Hypotheses

Here, it will be argued that trust in European institutions is a significant determinant of

individual level attitudes towards openness conceptualized as attitudes towards immigration

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and EU integration. The paper will attempt to evaluate the effect of trust in European

institutions on individual attitudes towards openness in Europe from an approach that aims to

target both of these points to be able to reach robust conclusions. Through this, the research

will be an original conceptualization of the outcome of individual attitudes towards openness

to outwards integration in Europe and highlight some of the common trajectories of individual

attitudes towards EU integration and integration with other countries in the form of accepting

more foreigners.

In this paper, the argument will put forward that trust in European institutions predicts

individual attitudes towards openness, conceptualized in two ways of (1) attitudes towards

further European integration and (2) attitudes towards further immigration. The unit of

analysis of the study is micro level individual attitudes. The institutional trust is argued to

mitigate feelings towards openness and will be able to predict a relationship for the outcome

of attitudes towards further European integration and further immigration. Lower

institutional trust will be a predictor of non-favourable opinion towards openness in both

points.

Hypothesis 1: The more individuals in a country trust European institutions; the more they are

expected to be favourable to further European integration. The less trusting the individuals

are, the less favourable to further European integration they are expected to be.

Hypothesis 2: The more individuals in a country trust European institutions, the more they

will be favourable to immigration into the country. The less trusting the individuals are, the

less favourable to immigration they are expected to be.

IV. Analytical Overview of the Literature

Turning to the literature that could explain what could be the determinants of attitudes

towards openness to outwards integration, the aim is not to present an analytical critique but

to look for alternative explanations to consider for controlling in the research. On the side of

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openness towards non-EU in the form of immigration, previous theories that aimed to explain

individual level attitudes towards immigration have looked for answers in both macro and

micro levels. In the micro levels it has been argued that socio-demographic factors such as

age, gender, education and income could be predictors of immigration attitude (Quillian 1995;

Raijman et.al. 2003; Mayda 2006).

Some have also argued that contact with immigration and immigrants as well as

different configurations of values and identifications of individuals, namely citizenship,

belonging to a minority, having someone close with an immigration experience or general

values of pro-immigration and placement on the left in the political scale can explain

immigration attitudes (Ceobanu and Escandell 2010; Gorodzeisky and Semyanov 2009). On

the macro levels, cultural threat theories and macroeconomic indicators of a country in the

form of GDP and unemployment have been put forward as predictors (Hjerm 2007; Kunovich

2004). Finally, overall trust in the society and national institutions have been argued to be a

predictor of openness towards non-nationals (Crepaz 2008; Crepaz and Damron 2009;

Espenshade and Hempstead 1996).

Looking at the other side, openness towards EU, for predicting attitudes of soft

Euroscepticism, similar arguments regarding micro factors in terms of socio-demographics,

identities, values and subjective perceptions on individual economic and social wellbeing

have been put forward (Gabel 1998; Loveless and Rohrschneider 2011). Additionally,

democratic deficit theory, referring to individual perceptions of non-democratic functioning

of European Union, and periphery oriented approaches arguing that nationals from certain

countries are more Eurosceptic, present alternative explanations in the literature (Hansen and

Weaver 2002; Leconte 2010). Another plausible explanation in the field is individual trust in

national institutions in determining individual attitudes towards openness to European

integration (Anderson 1998; Sanchez-Cuenca 2000).

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V. Methodology

The research question asked in this paper is aiming to explore to what extent trust in

European institutions can predict attitudes towards openness to outwards integration in the

form of (1) attitudes to further European integration and (2) attitudes to further immigration in

the context of economic crisis and recovery. Therefore, the theory tested here has a temporal

aspect that covers parameter years before, during and after a crisis. In this case, for theory

testing I am using the 2010 Eurozone crisis context and taking ESS waves 4, 6 and 7

conducted for 2008, 2012 and 2014 respectively.1 Considering the time lag of conducting the

survey, these years are able to capture the before, during and after crisis contexts. The spatial

parameter of the theory covers all European Union and EFTA countries that are influenced by

EU integration and migration dynamics as much as the EU member states (Lavanex 2011). In

terms of data used in the research, I have dropped individual respondents from countries that

are not surveyed in all three waves as the theory tested requires observations for all three

years, at least from the same country. 2

The unit of analysis of the research is individuals. Both the explanatory and outcome

variables, as well as the control variables introduced in the model will be at the individual

level. The theory of the paper is at the micro level and in this paper country level control

variables will not be introduced. However, based on the theories and the literature review on

the subject of attitudes towards European integration and further immigration, I argue that the

individual responses at the micro level are influenced by the country they are from. In

addition to this, I have argued that the year of the survey matters for the respondent as well,

since the theory was framed in a “crisis context”. The ESS waves allow me to have this multi-

level or nested model specification as each individual level id number also is identified with

1 ESS wave 5 released in 2010 is excluded because it does not include the key variable of interest on

EU integration in the questionnaire. 2 The countries are Belgium, Switzerland, Denmark, Germany, Finland, France, Ireland, Netherlands,

Norway, Poland, Sweden, Slovenia, Czech Republic and Estonia.

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which country the respondent is from. I will be using different model specifications for each

of the two main outcome variables.

Measurement & Operationalization of Variables

The dependent variable of the paper is attitudes towards openness to outwards integration,

which is a concept that will be measured by looking at (1) attitudes towards further European

integration and (2) attitudes towards immigration. The individual attitudes towards further

unification will be taken from the European Social Survey (ESS) item that asks, “…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?” The scale of responses varies

from 0 to 10, 0 being “unification already gone too far” and 10 indicating that unification

should go further.

The individual attitudes towards immigration will also be operationalized through an

ESS question item that asks whether the respondent prefers many or no immigrants let into

the country. The variable item asks the respondents whether or not many or few migrants of

different race/ethnic group from majority should be allowed into the country to live. The

answer scale is from 1 to 4, 1 indicating allowing for many to came and 4 being allowing no

immigration.

The robustness and validity of this operationalization for immigration will be

controlled with two other survey items. First, another question targets the same issue with the

difference in question being “allowing people with the same race/ethnic group” with the

majority to control for framing of the question and to see if that would significantly affect the

results. The choice of different race/ethnic group operationalization is based on the

consideration that the theory overall targets openness towards non-EU, but the control for the

same ethnicity, will allow the research to also see to what extent race and ethnic factor in the

same question may influence the results. Second, an alternative measurement of this variable

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for another robustness check will be the question item “Allow many/few immigrants from

poorer countries outside Europe” in order to see if the additional factor of economic condition

significantly alters the results. All of these variables are ordinal survey items that are ranked

in a meaningful way.

The independent variable of the paper is trust in European institutions and it will be

operationalized with the ESS item, which scores trust on a 0-10 scale as follows “… please

tell me on a score of 0-10 how much you personally trust each of the institutions I read out. 0

means you do not trust an institution at all, and 10 means you have complete trust. Firstly... ...

the European Parliament?” Out of all the other institutions of European Union, it is

appropriate to measure trust through European Parliament (EP) based on several

considerations.

First, it is the only institution with democratic representation of the citizens. Although

some may argue that it is the institution with the least amount of power over decisions, EP is

the biggest governing body in the EU in terms of accountability and representativeness of all

political ideologies and nationalities equally. Additionally, EP is closest to a national level

institution and a governance mechanism such as the national parliament or other democratic

bodies that can mitigate societal attitudes. Arnold et.al have shown that EP is the EU

institution that enjoys the highest level of trust both from both new and old member states

(2012, 20).3 It is neither an extensively contested institution with relatively lowest trust levels

such as the Council of Ministers nor like ECB where its perception is often dependent on

highly volatile economic and financial circumstances that are often outside of EU governance.

Therefore, it is plausible to argue that trust in EP would reflect trust in the general governance

of European institutions.

3 Using data from the Eurobarometer, the study also shows that the trust levels between EP and the

European Commission do not significantly differ from each other (Arnold et.al. 2012).

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Alternative Explanations and Control Variables

Based on the literature review, as outlined above, several control variables are selected to test

and control for alternative explanations on the outcome tested in this paper. The first control

variable is trust in national institutions. Using ESS standard item on this variable, it will be

operationalized with trust in the national parliament. This variable is on an ordinal scale from

0 to 10. O being no trust at all and 10 being complete trust, identical to the operationalization

of the independent variable. Second control will be trust in general to control for individual

values and beliefs operationalized with the item “most people can be trusted or you can’t be

too careful”, varying from 0 to 10 on an ordinal scale, 10 indicating that most people can be

trusted. These are the most commonly found operationalizations for these concepts in the

literature, therefore the threats to internal validity are considerably low with these two

variables.

The next two variables are also from ESS and will control for satisfaction with

country’s economy and satisfaction with country’s democracy. Operationalized with the

following questions that ask “on the whole how satisfied are you with the present state of the

(1) economy/ (2) the way democracy works in [country]?” on two separate questions where

responses vary from 0 to 10, 0 being extremely dissatisfied with the economy/democracy of

the country. To account for political values, placement in the left-right scale will be controlled

for using the ESS item “…where would you place yourself on this scale, where 0 means the

left and 10 means the right.” Citizenship of the country and belonging to a minority group

will be controlled for with two dummy variables with yes/no answers.

Finally, demographic controls will be introduced. The ESS is the data source where

these variables are going to be taken from as well. Age as a numerical variable and total

household income as an ordinal scale of income deciles will be used. Additionally,

satisfaction with the household income will also be controlled for as income and perception of

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economic standing are argued to be crucial factors for the dependent variable of the study.

This will be operationalized with the question “…how (do) you feel about your household’s

income nowadays” that has answers on an ordinal scale from 1 to 4, 1 being “living

comfortably”. Gender (dummy) will also be controlled for. Education will be controlled as

years in education as a numerical variable. Religiosity will be controlled as “…how religious

would you say you are?” on an ordinal scale of 0 being not at all religious and 10 being very

religious. Main activity in the last seven days (unemployed/paid work/education etc.) will be

controlled for as a categorical variable for labour market status.

It is important here to highlight that the model specifications will not have variables

that are not on the individual level. For instance, typical controls such as unemployment rate

or the percentage of immigrant populations will not be included. This is due to theoretical

approach of the paper that argues an individual level prediction for the outcome of outwards

integration. However, through the use of time as a control variable in the models, as well as

model specifications that can account for the country level (within and between countries), the

paper aims to account for these country level fixed variables.

Model Specifications and Estimation Methods

For the first outcome variable of attitudes towards European integration, I will specify a

mixed effects regression model and a multilevel regression with individuals nested in

countries. An ordered logit estimation model with clustered standard errors for countries with

a categorical variable for time will be used for robustness test. Since this outcome variable has

10 response categories, I am specifying an ordered logit, but this model will also be specified

as a generalized ordered logit estimation for further robustness checks.

For the attitudes towards immigrants, I will specify a multinomial logit estimation

model with clustered standard errors of countries with a categorical variable for time. This

outcome variable only has four response categories and based on both theory and the

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statistical tests for parallel regression assumption (proportional odds assumption) – Brant test

and Wolfe Gould test - it is argued here that the better model likelihood estimation would be

a multinomial logit model (Long and Freese 2014, 329). Since, the paper predicts a nested

structure for the individuals, a multi-level country panel set model will also be specified. As a

robustness check over the measurement of the immigration attitudes, I will use the two other

question items that frame the issue in different ways; immigrants from the “same ethnic and

religious background as the majority” and immigrants from “poor countries outside of

Europe” as opposed to the original operationalization of immigrants from different ethnic and

religious backgrounds from the natives. For final robustness checks, models for both

outcomes are also ran as non-multi-level models and as regressions with clustered standard

errors for country and time variables.

VI. Descriptive Results

Table 1 presents the descriptive statistics for the variables of interest in the paper. Outcome

variables; attitudes towards further immigration and attitudes towards further European

integration are not interval variables, and are specified as categorical for immigration and

ordinal for European integration. Trust in European parliament is also on an ordinal scale with

10 choices, which will be treated as a continuous variable. All variables with a range of 10

choices are treated as continuous. Citizenship of the country, belonging to a discriminated

group and the gender control variables are dummy variables. All variables have adequate

variation for statistical tests.4

Figure 1 shows the frequency distribution calculated as percentage of attitudes

towards European integration by each response to trust in European parliament. It can be seen

4 I have changed the directionality of all the variables to match a certain pattern for interpretation

purposes from their original ESS form. For instance, the attitude towards immigration variables have

been recoded to match the trust in European parliament. Higher numbered categories mean the

respondent chooses further immigration, paralleling higher trust in higher number categories in the

trust in European parliament variable.

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that highest percentage of “unification already gone too far” is from the “No Trust at All”

choice at all as predicted and the “unification should go further” is from the individuals that

responded as having “Complete Trust” in the European Parliament. Figure 2 and Figure 3

present the frequency distributions of the two dependent variables by each ESS wave and

country. It is visible in these two figures that, as expected, there is variation of individual

responses influenced by the year of the ESS wave conducted and the country they are from.

These also show that there is no extreme skewedness in any category of answers for either of

the two outcome variables. Finally, Table 2 presents the power correlations of key variables

of interest. The table shows that there is significant correlation between all of these variables

tested, particularly between the two outcome and one response variables as argued in the

paper.

VII. Statistical Results

DV: Attitudes towards further European integration

The first model specified is an ordered logit model with clustered standard errors. I have

added a control categorical variable for the ESS waves to see the effect of the years. In

addition to the IV, trust in European Parliament (EP), I have done a stepwise addition of

variables into the model based on the alternative explanations put forward in the literature.

Table 3 presents the results of this ordered logit model with clustered standard errors for

countries. In Model 1, trust in EP, satisfaction with country’s democracy and ESS years were

found statistically significant. In Model 2, in addition to the previous three, years of education

completed also has a significant effect for predicting attitudes towards further European

integration. In Model 3, out of the newly included variables household income and

respondent’s main activity have significant effects. The main activity variable is a categorical

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variable and the baseline used is paid work, so for this baseline the significant predictor

categories were being in education, unemployed and looking for a job and doing housework.

The final Model 4 introduced three new variables. For the two dummy variables,

being female and belonging to a minority group discriminated in the country were statistically

significant. One last observation for Model 4 is that, from Model 3 to Model 4 the statistical

significance of household income variable was lost. This is probably because in model 4 I

have introduced a variable that measures respondent’s perception of their net income.

Looking at the standard errors, none of the models significantly improved any of the

standard errors, as is the case for the residuals of the models specified. The AIC and BIC

statistics show that Model 4 is the better fit. I also ran a likelihood ratio and proportional

reduction in error (PRE) test which showed that Model 4 is the best model specification out of

all four. Therefore, I am choosing Model 4 as the model fit for this ordered logit for

predicting attitudes towards further EU integration.

Table 4 presents the same four models, but with odds ratios instead of log likelihood

in order to see the estimate of the effects of these variables. Based on the model chosen

(Model 4), one-unit increase of trust in European parliament increases the odds of choosing a

response more in favour of further EU integration by 34%. This effect is illustrated in Figure

4 using predicted probabilities. The predicted probability of responding integration has gone

too far is less for choices of complete trust in the EP.

Looking at the variables for alternative explanations, one-unit increase in satisfaction

with the democracy in the country increases the odds of choosing a response more in favour

of further EU integration by 4%. One-year increase in years spent in full time education

increases the odds of choosing a response more in favour of further EU integration by 2%.

Regarding the main activity of the individual, compared to the baseline activity of being in

paid work, being education (by 16%), being retired (by 19%) and being in housework (by

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18%) increases the odds of choosing a response more in favour of further EU integration.

Being a woman decreases the odds of choosing a response favouring more integration by 14

% and belonging to a group discriminated in that country decreases by 18%. Finally,

compared with the 2008 (ESS 4) the odds of favouring further EU integration is decreased by

18% in 2012 and by 16% in 2014.

For diagnostics of this model, I did a Brant test. Brant test results, presented in Table

5, show that the proportional odds assumption has been violated as a model and for almost all

the variables. In order to make sure that the statistically significant effect I have for my

hypothesized IV, I ran the same model specification as a generalized ordered logit (results

presented in Table 6) and as a multinomial logit with clustered standard errors (results

presented in Table 7). The significance of the trust in EP was robust across all models. More

importantly, as seen in Table 7, trust in EP is the only variable that is statistically significant

in all response categories (when the baseline for estimation is the choice 5). I also ran this

model as a simple multivariate OLS, as an OLS with country and ESS round clustered

standard errors, and as an ordered logit with clustered errors for time; the significance of trust

in EP has been robust across all models I specified.

As a second model specification, which can be argued to fit the data structure better

than the above mentioned method, I used a mixed effects model with three levels: individual

score on attitude towards EU integration, country, and time (ESS round), using the same

individual level predictors in the model as above.5 The model fit used in this mixed effects

model is a linear fit and since the outcome variable was on an ordinal scale of 10 choices,

making it suitable for this specification. The results of the mixed effects models are presented

in Table 8. I have tried stepwise variable addition strategy and conducted the model fit test as

mentioned above. The best model fit was the full model (Model 2). The log likelihood test

5 I have used STATA Reference Manual and Leckie (2013) as main reference points for this

interpretation and model specification.

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showed that this model is a better fit for the model than a linear single level fit model. Table 9

reports the between and within level variances for each level in the model, which supports this

argument. Based on this, Figure 5 illustrates the magnitude of the country effects on

respondent’s attitude towards EU integration. It is seen from the predicted effects that being

from Poland and Slovenia affects the attitude more than the average, whereas being from

Finland and Norway affects less. Same plot for ESS round showed the effect of time moving

around the average for all three years.

Looking at individual level predictors, trust in European parliament is statistically

significant in this model too. One-unit increase in trust in EP, increases the attitude towards

European integration by 0.326 units towards a favourable opinion. Unit increases in the

education, left right scale placement, and household income all have increasing effect on

favourable opinion towards EU integration (by 0.22, 0.02 and 0.02 respectively).6 For the

main activity categorical variable, compared to being in a paid work, being in education,

being unemployed and looking for a job, being retired, and being in housework all have

increasing effect on the favourable opinion. In terms of diagnostics, outlier observations are

not an issue here based on the descriptive statistics and the large number of observations in

the sample. Figure 7 presents the plotted residuals of this model to test for heteroscedasticity.

There seems to be some clustering especially towards the middle, which is potentially due to

the ordinal scale nature of the variable, but there seems to be some variation on the residuals.

Finally, I have also set the three wave merged panel data and used fixed effects and

random effects model. You can see the results of these model specifications in Table 18 for

the outcome of European integration. The effect of trust in EP is significant in all model

6 Other statistically significant effects are; One-unit increase in general trust, increases the attitude

towards European integration by 0.06 units towards a favourable opinion. One-unit increase in

satisfaction with the economy in the country increases the attitude towards European integration by

0.09 units and satisfaction with the democracy by 0.06 towards a favourable opinion. Being a citizen

(by 0.18), being a woman (by 0.13 units) and belonging to a discriminated group (by 0.08) decreases

the favourable opinion towards further EU integration.

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specifications, as well as the effect of the surveyed year. As a last robustness check, I have set

each individual survey wave with the same countries nested individual observations as a panel

and did regression estimations using both fixed effects and random effects model

specifications. In all three waves individually, the effect signs and significance of trust in EP

was robust and showed that an increase in trust in EP predicts favourable opinion towards EU

integration.

DV: Attitudes towards further Immigration

Firstly, I have specified a multinomial logit estimation with country clustered standard errors.

The model specification of variables is the same as the previous outcome studied, since the

over-arching aim is to look at these two outcomes as a concept of outwards integration. Table

10 reports the log likelihood coefficients and Table 11 has the odds ratios (relative risk ratios)

of the model estimations. The estimation shows that trust in EP does not have a statistically

significance odds relationship with the outcome for any category when the baseline is set at

“allow many”.

I, then, plotted the predicted probabilities of this estimation as seen in Figure 6. This

figure shows that although the effect of trust in EP is not statistically significant presented as

in Table 11, there is in fact an effect on the predicted probabilities at the lower trust

respondents. In order to understand this, I have changed the baselines to all possible

categories and when the baseline is set to “allow none” as presented in table 12, there was a

statistically significant effect of trust in EP on attitude towards further immigration. The odds

of choosing to allow some immigrants rather than no immigrants at all is 7% higher for those

respondents that are in one-unit higher trust in EP. In addition to this, when baseline was

allowing some, trust in EP was statistically significant for choosing to allow none rather than

some by decreasing the odds by 7%.

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Next, I tried two alternative measurements for the attitude towards further

immigration. Table 13 and Table 14 presents these results. Trust in EP, does not have a

significant effect on attitudes towards immigration. I have tried both of these results with all

possible baselines, for the both the first and second alternative measurements. None of the

baselines had any significant effects for the trust in EP. For an alternative robustness test on

the results, I did different types of OLS regressions (results are presented in Table 15). Trust

in EP is statistically significant in a multivariate linear regression, but loses significance in the

clustering standard errors.

The next specification I tried was a multinomial logit estimation with clustered errors,

this time by year (results presented in Table 16). This model estimated significant effects for

trust in EP as well as many other control variables specified in the model that were not

statistically significant in those model estimates. I ran this model with different baselines and

the significance of trust in EP remained robust. Clustering by each ESS round year also

showed significance for each country as well, which was expected as the theory predicted that

the individuals are nested in their home countries. However, this way I can also say that there

is significant within country between time variance for this variable.

Lastly based on the results from above, I have set the data as panel with country level

clusters for individual observations and used likelihood estimation. The results from this

model specification can be found in Table 17 in the Appendix. Here, in model specifications

with or without the time variable included, the effect of trust in EP has come out as significant

with a positive coefficient. A similar procedure to the EU integration dimension has been

followed here as well for additional robustness checks and for each survey wave set as

country panels have showed robust significant results for trust in EP.

18

VIII. Implications of Results and Conclusion

Overall the results show that there is significant evidence to support the first hypothesis

regarding the effect of trust in EP on attitudes towards EU integration. All models specified to

test this hypothesis show robust and significant results. The specified mixed effects, random

effects and fixed effects models all predict that increasing trust in EP have a statistically

significant relationship with increasingly favourable attitudes towards EU integration. This is

an important finding and a robust evidence for the institutional trust theories in the literature.

This also may help in understanding increasing Euroscepticism with decreasing levels of trust

in European institutions as seen from the recent trends in European countries.

Aside from the effect of trust in EP, the individual’s satisfaction with the national

democracy has been shown to be a significant predictor as well. Increases in both satisfactions

with the democracy and the years in education spent increases favourable opinion towards EU

integration. Conversely, being female and belonging to a minority group discriminated in the

country decreases the support for EU integration. 7 An interesting finding has been the

differences in country effects in the mixed effects model. Being from certain countries have

been found to be more influential than other in mitigating attitudes towards EU integration.

This result is puzzling in the sense that it potentially requires further questions in order to

understand the reasons underpinning this outcome.8

For the second hypothesis, I can neither confirm nor reject this hypothesized

relationship between attitudes towards further immigration and trust in EP. Although the

effect of trust in EP is statistically significant in multilevel likelihood estimation models, the

multinomial logit model specification showed mixed results for the significance of the trust in

7 There is an odd change in sign between random and fixed effects models for trust in national

parliament, which I have not been able to fully explain. I am looking more into this issue in order to

understand why that happened (See Table 18). 8 I will look for further into this effect using design weights in model estimations to check if these

varieties of country effects are still present.

19

EP. However, I believe this might potentially be due to misspecification of this outcome

variable. As shown in the results and argued in the beginning, a multi-level model

specification that includes both time and country level is required for this. There are issues of

serial autocorrelation, which can be resolved in a hierarchical structure that can account for

the time dimension as well. For the future of this research, I will be working on specifying a

generalized linear latent and mixed model, which is suited for multilevel latent variable

models where the outcome is non-linear such as in this case (Zheng and Rabe-Hesketh 2007).

Connected to the point made above, another important caveat to the results is the issue

with time, measured very broadly with the survey waves. Time is a significant variable in

almost all specifications for EU integration attitudes, so the argument that the crisis context

matters on its effect on attitudes towards outwards integration was supported. For the

immigration attitudes, the categorical time variable has not been robust predictor, and lost

significance in the hierarchical specification. A more substantive evaluation of the effect of

time is required to conclude anything for the matter of crisis context, perhaps using

interaction effects of time with the explanatory variables. Despite its many shortcomings, I

believe this study enlarges the debate on European attitudes towards outwards integration and

perhaps even make a case for strengthening the public’s relationship with European

institutions for a harmonious societal interaction with the proverbial “others” in European

societies.

20

REFERENCES

Anderson, C. 1998. “When in Doubt Use Proxies: Attitudes towards Domestic Politics and

Support for European Integration.” Comparative Political Studies 31 (5): 569-601.

Armingeon, K.and K. Guthmann. 2014. “Democracy in crisis? The declining support for

national democracy in European countries, 2007–2011.” European Journal of Political

Research 53(3): 423–442.

Arnold, C., E. V. Sapir and G. Zapryanova. 2012. “Trust in the institutions of the European

Union: A cross-country examination” in Beyond Euro-scepticism: Understanding attitudes

towards the EU edited by L. Beaudonnet and D. Di Mauro. European Integration Online

Papers (EIoP), Special Mini-Issue 2, Vol. 16, Article 8.

Available at: http://eiop.or.at/eiop/texte/2012-008a.html.

Boomgaarden, H.G., A.R.T Schuck, M. Elenbaas and C.H. de Vreese. 2010. “Mapping EU

attitudes: Conceptual and empirical dimension of Euroscepticism and EU support.” European

Union Politics 12(2): 241-266.

Ceobanu, A.M. and X. Escandell. 2010. “Comparative Analyses of Public Attitudes Toward

Immigrants and Immigration Using Multinational Survey Data: A Review of Theories and

Research.” Annual Review of Sociology 36: 309- 328.

Crepaz, M. 2008. Trust Beyond Borders Immigration, the Welfare State, and Identity in

Modern Societies. Ann Arbor: The University of Michigan Press.

Crepaz, M. L. and R. Damron. 2009. “Constructing Tolerance: How the Welfare State Shapes

Attitudes about Immigrants.” Comparative Political Studies, 43(3): pp. 437-463.

de Vries, C. and I. Hoffmann. 2016. “Border Protection and Freedom of Movement -What

people expect of European asylum and migration policies.” Bertelsmann Stiftung EU

Opinions 2016/1. Available at: https://www.bertelsmann-

stiftung.de/fileadmin/files/user_upload/EZ_eupinions_2016_01_ENG.pdf

Drudi, F., A. Durré and F. P. Mongelli. 2012. “The Interplay of Economic Reforms and

Monetary Policy: The Case of the Eurozone.” Journal of Common Market Studies 50(6):

881–898.

Dotti Sani, G.M. and B. Magistro. .2016. “Increasingly unequal? The economic crisis, social

inequalities and trust in the European Parliament in 20 European countries.” European

Journal of Political Research. (early view).

Espenshade, T. J. and K. Hempstead. 1996. “Contemporary American Attitudes Towards

U.S. Immigration.” International Migration Review 30(2): 535-570.

Freedman, M. 2012. “Changes in Attitudes towards Immigration: Evidence from the

European Debt Crisis.” Konrad Adenauer Stiftung Working Paper 115/2012. Available at:

http://www.ef.huji.ac.il/publications/Adenauer-Freedman-Clean%20-%20for%20web.pdf

21

Gabel, M. 1998. “Public support for European integration: An empirical test of five theories.”

Journal of Politics 60(2): 333-354.

Gorodzeisky, A., and M. Semyonov. 2009. “Terms of Exclusion: Public Views towards

Admission and Allocation of Rights to Immigrants in European Countries.” Ethnic and Racial

Studies 32(1): 401-423.

Hansen, L. and O. Weaver. 2002. European Integration and National Identity: The Challenge

of the Nordic States. London: Routledge.

Hjerm, M. 2007. “Do Numbers Really Count? Group Threat Theory Revisited.” Journal of

Ethnic and Migration Studies 33(8): 1253-1275.

Kopecky P. and C. Mudde. 2002. “The Two Sides of Euroscepticism: Party Positions on

European Integration in East and Central Europe.” European Union Politics 3(3): 297-326.

Kunovich, R. M. 2002. “Social Structural Sources of Anti-Immigrant Prejudice in Europe.”

International Journal of Sociology 32(1): 39-57.

Kunovich, R. M. 2004. “Social Structural Position and Prejudice: An Exploration of Cross-

national Differences in Regression Slopes.” Social Science Research 33: 20-44.

Lavanex, S. 2011. “Concentric Circles of Flexible ‘EUropean’ Integration: A typology of EU

External Governance Relations.” Comparative European Politics 9 (4-5): 372-393.

Leckie, G. 2013. Three-Level Multilevel Models – Stata Practical. LEMME VLE Module 11,

1-52. University of Bristol. Available at: http://www.bristol.ac.uk/cmm/learning/course.html.

Leconte, C. 2010 Understanding Euroscepticism Houndmills: Palgrave McMillan.

Leconte, C. 2015. “From pathology to mainstream phenomenon: Reviewing the

Euroscepticism debate in research and theory.” International Political Science Review 36(3):

250-263

Long, S. and J. Freese. 2014. Regression Models for Categorical Dependent Variables Using

Stata. Third Edition. College Station, TX.: STATA Press.

Loveless, M. and R. Rohrschneider. 2011. “Public Perceptions of the EU as a system of

governance.” Living Reviews in European Governance 6(2): 5-28.

Mayda, A. M. 2006. “Who is Against Immigration? A Cross-Country Investigation of

Individual Attitudes toward immigrants.” Review of Economics and Statistics 88 (3): 510-

530.

Putnam, R. 2003. Making Democracy Work: Civic Traditions in Modern Italy. Princeton,

New Jersey: Princeton University Press.

Quillian, L. 1995. “Prejudice as a Response to Perceived Threat: Population Composition and

Anti-immigrant and Racial Prejudice in Europe.” American Sociological Review 60(4): 586–

611.

22

Quillian, L. 2006. “New Approaches to Understanding Racial Prejudice and Discrimination.”

Annual Review of Sociology 32:299–328.

Raijman, R., M. Semyonov, and P. Schmidt. 2003. “Do Foreigners Deserve Rights?

Determinants of Public Views Towards Foreigners in Germany and Israel.” European

Sociological Review 19(4): 379-392.

Rothstein, B. and E. Uslaner. 2005. “All for All. Equality, Corruption and Social Trust”

World Politics 58 (1): 41-72.

Sanchez-Cuenca, I. 2000. “The Political Basis of Support for European Integration.”

European Union Politics 1(2): 147-171.

Serricchio, F., M. Tsakatika and L. Quaglia. 2013.“Euroscepticism and the Global Financial

Crisis.” Journal of Common Market Studies 51(1): 51-64.

Stata Corp. (2011). STATA Multilevel Mixed Effects Reference Manual. RELEASE 13.

College Station, TX: Stata Press.

Taggart, P. 1998. “A Touchstone of Dissent: Euroscepticism in Contemporary Western

European Party Systems.” European Journal of Political Research 33(3): 363-388.

Treib, O. 2014. “The voter says no, but nobody listens: causes and consequences of the

Eurosceptic vote in the 2014 European elections.” Journal of European Public Policy 21(10):

1541-1554.

Torcal, M. 2014. “The decline of political trust in Spain and Portugal: Economic performance

or political responsiveness.” American Behavioral Scientist 58(12): 1542–1567.

Uslaner, E. 2002. The Moral Foundations of Trust. New York: Cambridge University Press.

Zheng, X. and S. Rabe-Hesketh, 2007."Estimating Parameters of Dichotomous and Ordinal

Item Response Models with gllamm," Stata Journal, StataCorp 7(3): 313-333.

APPENDIX

Table 1: Summary Statistics

Variable Obs Mean Std. Dev. Min. Max. with Value Label

Outcome Variables

Attitudes towards further Immigration 69,113 1.70635 .8186974 0 3 Allow Many

Attitudes towards further European Integration 69,113 5.044044 2.480413 0 10 Should go further

Trust in European Parliament 69,113 4.635799 2.264302 0 10 Complete Trust

General trust 69,113 5.571021 2.253791 0 10 Trust All

Trust in National Parliament 69,113 4.989814 2.442867 0 10 Complete Trust

Economic Satisfaction (national) 69,113 5.058889 2.424542 0 10

Democratic Satisfaction (national) 69,113 5.904794 2.318363 0 10

Left Right Scale 69,113 4.84547 2.155952 0 10

Citizenship 69,113 .957461 .2018169 0 1 Yes

Discriminated Group 69,113 .0630706 .2430917 0 1 Yes

Age (years) 69,113 49.30313 31.76638 14 999

Income Feeling 69,113 2.181297 .7825983 0 3 Lives Comfortably

Income (deciles) 69,113 5.703905 2.743898 1 10

Gender 69,113 .4886346 .4998744 0 1 Female

Education (years) 69,113 13.54929 5.332921 0 99

Religion 69,113 4.276229 3.014736 0 10 Very Religious

Main activity 69,113 2.956246 2.537631 1 9 Other

Table 2: Power Correlations of Key Variables (with 4 other control variables)

Attitude

towards

further EU

integration

Attitude

towards further

immigration

Trust in EP General

Trust

Trust in

National

Parliament

Left Right

Scale

Attitude towards

further EU

integration

1

Attitude towards

further immigration

0.237*** 1

Trust in EP

0.352***

0.169***

1

General Trust 0.127*** 0.211*** 0.263*** 1

Trust in Nat.

Parliament

0.214*** 0.217*** 0.559*** 0.400*** 1

Left Right Scale 0.00260* 0.154*** -0.0578*** -0.0275*** -0.0653*** 1 * p < 0.05, ** p < 0.01, *** p < 0.001

Table 3: Ordered Logit Maximum Likelihood Estimation with Clustered Standard Errors (by Country) DV: Attitudes towards

European Integration

Variables

Model (1) Model (2) Model (3) Model (4)

Trust in the EP 0.29***

(0.031)

0.29***

(0.032)

0.29***

(0.031)

0.30***

(0.031)

Trust in country's parliament -0.026 -0.029 -0.032 -0.034

(0.028) (0.027) (0.027) (0.026)

General trust 0.018

(0.022)

0.013

(0.022)

0.010

(0.022)

0.0088

(0.022)

Satisfaction with Country’s

Economy

0.035

(0.026)

0.038

(0.026)

0.037

(0.026)

0.032

(0.026)

Satisfaction with Country’s

Democracy

0.043***

(0.011)

0.042***

(0.011)

0.042***

(0.011)

0.039***

(0.010)

ESS round=6 -0.21*** -0.21*** -0.20** -0.19**

(0.062) (0.061) (0.063) (0.063)

ESS round=7 -0.17* -0.18* -0.17** -0.17**

(0.072) (0.069) (0.067) (0.066)

How religious are you 0.0047 0.0070 0.011

(0.013) (0.013) (0.013)

Age of respondent,

calculated

0.000015 -0.00033 -0.00039

(0.00083) (0.00053) (0.00051)

Years of full-time education

completed

0.022** 0.021** 0.022**

(0.0072) (0.0071) (0.0073)

In Education 0.15** 0.15***

(0.047) (0.046)

Unemployed, looking 0.099* 0.12**

(0.045) (0.043)

Unemployed, not looking -0.014 0.019

(0.10) (0.091)

Permanently sick or

disabled

-0.063 -0.025

(0.080) (0.083)

Retired 0.18** 0.17**

(0.061) (0.059)

Community or military

service

0.065

(0.31)

0.011

(0.31)

Housework, looking after

children, others

0.11*

(0.091)

0.17**

(0.090)

Household's income 0.033***

(0.0087)

0.024

(0.013)

Left right scale 0.029

(0.022)

0.032

(0.023)

Citizenship -0.048 -0.066

(0.12) (0.12)

Belonging to Discrim.Group -0.19***

(0.055)

Female -0.14***

(0.037)

Feeling about household's

income nowadays

0.064

(0.060)

Observations (individuals) 69113 69113 69113 69113

Num. of Clusters (country) 14 14 14 14

Pseudo R2 0.033 0.034 0.035 0.035

AIC 300028.12 299741.99 299446.20 299249.52

BIC 300146.98 299860.86 299565.07 299368.38

Log Likelihood -150001.06 -149858.00 -149710.10 -149611.76

Coefficients are log likelihood. Robust standard errors in parentheses. * p < 0.05, ** p < 0.01, *** p < 0.001

Table 4: Odds Ratios – Ordered Logit MLE with Clustered Standard Errors (by Country) DV: Attitudes towards

European Integration

Variables

Model (1) Model (2) Model (3) Model (4)

Trust in the EP 1.35***

(0.042)

1.34***

(0.042)

1.34***

(0.042)

1.34***

(0.041)

Trust in country's

parliament

0.98 0.97 0.97 0.97

(0.27) (0.25) (0.26) (0.25)

General trust 1.02

(0.022)

1.01

(0.022)

1.01

(0.022)

1.01

(0.022)

Satisfaction with Country’s

Economy

1.04

(0.026)

1.04

(0.026)

1.04

(0.026)

1.032

(0.026)

Satisfaction with Country’s

Democracy

1.04*** 1.04*** 1.04*** 1.04***

(0.011) (0.011) (0.011) (0.01)

Religion 1.005 1.006 1.01

(0.013) (0.013) (0.013)

Age 1.000 0.999 0.999

(0.00083) (0.00053) (0.0005)

Years of education 1.023**

(0.0072)

1.022**

(0.0071)

1.022**

(0.0074)

Main Activity Category

In Education 1.16** 1.16***

(0.05) (0.053)

Unemployed, looking 1.10* 1.13**

(0.04) (0.05)

Unemployed, not looking 0.99

(0.10)

1.01

(0.093)

Permanently sick or

disabled

0.94

(0.08)

0.97

(0.081)

Retired 1.20** 1.19**

(0.07) (0.07)

Community or military

service

1.07

(0.33)

1.01

(0.31)

Housework (looking after

children, others)

1.121*

(0.064)

1.18**

(0.067)

Household's total net

income, all sources

1.034***

(0.0089)

1.025

(0.013)

Left right scale 1.029

(0.022)

1.03

(0.023)

Citizenship 0.953 0.94

(0.11) (0.11)

Belonging to a

Discriminated Group

0.82***

(0.044)

Feeling household income

1.06

(0.063)

Female 0.86***

(0.031)

ESS 6 (2012) 0.81*** 0.81*** 0.82** 0.82**

(0.05) (0.05) (0.05) (0.05)

ESS 7 (2014) 0.85* 0.83* 0.84** 0.84**

(0.06) (0.057) (0.055) (0.055)

Observations (individuals) 69113 69113 69113 69113

Num. of Clusters (country) 14 14 14 14

Log Likelihood -150001.06 -149858.00 -149710.10 -149611.76 * p < 0.05, ** p < 0.01, *** p < 0.001 Robust standard errors in parentheses.

Table 5: Brant test of parallel regression assumption (for Model 4 in Table 4)

| chi2 p>chi2 df

All | 2790.21 0.000 216

trustep | 287.79 0.000 9

trustparl.| 25.09 0.003 9

genrealtrust | 40.45 0.000 9

satisfaction eco. | 56.26 0.000 9

stfdem | 19.58 0.021 9

religion | 24.44 0.004 9

age | 104.95 0.000 9

education | 30.40 0.000 9

2.mainactivity | 53.37 0.000 9

3.mainactivity | 4.17 0.900 9

4.mainactivity | 27.41 0.001 9

5.mainactivity | 21.58 0.010 9

6.mainactivity | 54.58 0.000 9

7.mainactivity | 19.20 0.024 9

8.mainactivity | 7.98 0.537 9

9.mainactivity | 16.10 0.065 9

income | 58.63 0.000 9

left right | 79.45 0.000 9

citizenship | 38.69 0.000 9

discriminated | 130.02 0.000 9

gender | 744.15 0.000 9

Income feeling | 18.54 0.029 9

6.essround | 45.13 0.000 9

7.essround | 14.25 0.114 9

Table 6: Generalized Ordered Logit Estimations for (cluster se by country)

DV: Attitudes towards Coef. Std. Err. z P>|z| [95% Confidence Interval]

further EU Integration

0 Trust EP | .4006803 .0435619 9.20 0.000 .3153005 .48606011

1 Trust EP | .3797452 .0405656 9.36 0.000 .3002382 .4592523

2 Trust EP | .3456419 .0367126 9.41 0.000 .2736864 .4175973

3 Trust EP | .318789 .0303997 10.49 0.000 .2592068 .3783712

4 Trust EP | .2897716 .0292037 9.92 0.000 .2325333 .3470099

5 Trust EP | .2682868 .0283708 9.46 0.000 .212681 .3238925

6 Trust EP | .2546969 .029999 8.49 0.000 .1959 .3134938

7 Trust EP | .2471968 .0293391 8.43 0.000 .1896931 .3047005

8 Trust EP | .2447615 .0310655 7.88 0.000 .1838741 .3056488

9 Trust EP | .2395238 .0329851 7.26 0.000 .1748742 .304173

Table 7: Multinomial Logit Results for European Integration (main activity variable results

omitted) – Clustered standard errors by country –Baseline category 5 omitted.

Variables

0

10 (futher)

trstep 0.650*** 0.728*** 0.794*** 0.859*** 0.940*** 1.090*** 1.131*** 1.174*** 1.226*** 1.231***

(0.0340) (0.0342) (0.0244) (0.0163) (0.0123) (0.0119) (0.0237) (0.0294) (0.0367) (0.0435)

trstprl 1.033 1.023 1.050** 1.033*** 1.041*** 1.010 1.001 0.999 0.984 0.971

(0.0300) (0.0252) (0.0205) (0.0116) (0.0121) (0.0150) (0.0198) (0.0300) (0.0348) (0.0424)

ppltrst 0.988 1.003 0.991 1.003 1.004 1.019 1.030 1.023 1.007 0.973

(0.0174) (0.0190) (0.00764) (0.0116) (0.00935) (0.0128) (0.0198) (0.0294) (0.0396) (0.0353)

stfeco 0.909*** 0.942*** 0.955*** 0.974* 0.969*** 0.994 0.996 0.996 1.007 0.985

(0.0197) (0.0193) (0.00980) (0.0136) (0.0112) (0.0241) (0.0355) (0.0455) (0.0505) (0.0555)

stfdem 0.949** 0.964** 0.972* 0.979** 0.981* 1.020 1.018 1.023 1.010 0.989

(0.0214) (0.0144) (0.0167) (0.00954) (0.0110) (0.0159) (0.0139) (0.0153) (0.0190) (0.0340)

religion 0.989 1.000 0.999 0.995 1.000 1.017* 1.015 1.016 1.023 0.993

(0.0146) (0.0112) (0.0105) (0.00865) (0.00672) (0.00940) (0.0122) (0.0179) (0.0205) (0.0220)

agea 1.002 1.002** 1.002 1.001 1.000 0.999 0.999 1.001 1.002* 1.002

(0.00120) (0.000925) (0.00115) (0.00143) (0.000858

)

(0.00124) (0.00201) (0.00165) (0.00112) (0.00146)

education 0.992 0.986 0.978*** 0.989** 0.997 1.002 1.016** 1.021** 1.024*** 1.026***

(0.00867) (0.00964) (0.00530) (0.00485) (0.00551) (0.00525) (0.00720) (0.00950) (0.00950) (0.00945)

income 0.991 1.007 1.014 1.006 0.995 1.016* 1.034*** 1.053*** 1.068** 1.024

(0.0162) (0.0171) (0.0147) (0.00987) (0.0147) (0.00832) (0.0128) (0.0199) (0.0293) (0.0224)

rc_leftright 0.965 0.973* 0.978 0.976*** 0.987 0.977** 0.989 1.025 1.024 1.078**

(0.0269) (0.0154) (0.0158) (0.00937) (0.00967) (0.0110) (0.0156) (0.0209) (0.0361) (0.0378)

1.citizenship_rc

0.943 0.831 0.908 1.175** 1.162* 1.091 1.047 0.936 0.832 0.716**

(0.0827) (0.173) (0.0654) (0.0764) (0.0931) (0.100) (0.124) (0.142) (0.167) (0.117)

1.rc_discri

minated

1.730*** 1.605*** 1.338*** 1.124 1.012 0.823 0.922 1.070 1.275*** 1.484***

(0.130) (0.177) (0.0989) (0.0920) (0.114) (0.0995) (0.0695) (0.128) (0.106) (0.198)

1.gender 0.578*** 0.686*** 0.731*** 0.805*** 0.944 0.902** 0.721*** 0.574*** 0.491*** 0.448***

(0.0394) (0.0446) (0.0281) (0.0414) (0.0419) (0.0416) (0.0314) (0.0408) (0.0561) (0.0406)

rc_incomef

eeling

0.912 0.901 0.929* 0.965 0.982 0.970 1.060 1.033 0.972 1.083

(0.0513) (0.0632) (0.0376) (0.0357) (0.0530) (0.0374) (0.0690) (0.0844) (0.0871) (0.110)

6.essround 1.387** 1.170* 1.141** 1.136*** 1.123*** 0.912** 0.836*** 0.858* 0.901 1.024

(0.182) (0.100) (0.0598) (0.0441) (0.0388) (0.0369) (0.0571) (0.0799) (0.0995) (0.0936)

7.essround 1.217 1.087 1.080 1.064 1.128** 0.952 0.870** 0.821** 0.815 0.913

(0.153) (0.0748) (0.0656) (0.0417) (0.0576) (0.0295) (0.0476) (0.0754) (0.105) (0.0872)

Table 8: Mixed Effects Model Estimations (1) (2) (3)

DV: Attitudes towards further

European Integration

Model

With only Trust in EP

Model 1 (without

categorization)

Model 2 (with

categorical variables)

Trust in the European Parliament 0.401*** 0.328*** 0.326***

(0.00387) (0.00481) (0.00483)

Trust in National Parliament 0.00894 0.00870

(0.00525) (0.00525)

General Trust 0.0574***

(0.00442)

0.0575***

(0.00442)

How satisfied with present state

of economy in country

0.0865***

(0.00507)

0.0866***

(0.00507)

How satisfied with the way

democracy works in country

0.0601***

(0.00513)

0.0598***

(0.00513)

How religious are you -0.00539 -0.00517

(0.00306) (0.00307)

Age of respondent, calculated -0.000274 -0.000238

(0.000282) (0.000297)

Years of full-time education

completed

0.0216***

(0.00167)

0.0221***

(0.00168)

Household's total net income, all

sources

0.0189***

(0.00389)

0.0235***

(0.00397)

Placement on left right scale 0.0253***

(0.00411)

0.0252***

(0.00411)

Citizen of country -0.180***

(0.0434)

Member of a discr. group -0.0775*

(0.0360)

Female -0.139***

(0.0176)

Feeling about household's income 0.0742***

(0.0137)

0.0725***

(0.0139)

Main activity (baseline: paid

work)

0.0225***

(0.00372)

In Education 0.177***

(0.0354)

Unemployed, looking for job 0.185***

(0.0478)

Unemployed, not looking for job 0.0672

(0.0760)

Permanently sick or disabled 0.0553

(0.0550)

Retired 0.178***

(0.0243)

Community or military service 0.433

(0.305)

Housework, looking after

children, others

0.112**

(0.0365)

Citizenship -0.183***

(0.0434)

Discriminated Group member -0.0754*

(0.0360)

Female -0.130***

(0.0178)

Constant 3.246*** 1.981*** 1.956***

(0.0804) (0.120) (0.120)

Observations 69113 69113 69113

AIC 309519.22 307745.08 307717.41

BIC 309564.94 307909.66 307955.14

Standard errors in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001

Table 9: Random-effects Parameters for Mixed Effects Model for Model2 in Table8

Estimate Std. Err. [95% Conf. Interval]

essround: Identity (Between time level variance)

4.99e-12

countryID: Identity (Within time between country variance)

3958026 .0886143 2552157 .6138327

var(Residual) (Within country between respondent variance)

5.010543 .0269619 4.957977 5.063667

LR test vs. linear model: chi2(2) = 3766.88 Prob > chi2 = 0.0000

Table 10: Multinomial Logit Estimations with Clustered Errors by Country

DV: Attitudes towards further Immigration (from different race/religion)

(1)

Allow None

(2)

Allow a Few

(3)

Allow Some

(4)

Allow Many

Trust in the European Parliament -0.07 -0.04 -0.00

(0.040) (0.035) (0.021)

Trust in country's parliament -0.13* -0.05 -0.01

(0.054) (0.052) (0.029)

Most people can be trusted or you can't be too

careful

-0.22*** -0.15*** -0.11***

(0.041) (0.036) (0.022)

How satisfied with present state of economy in

country

-0.09** -0.04 -0.02

(0.034) (0.022) (0.018) BASELINE

How satisfied with the way democracy works in

country

-0.07 -0.02 0.00

(0.039) (0.030) (0.022)

How religious are you -0.02 0.01 0.02

(0.042) (0.030) (0.015)

Age of respondent, calculated 0.01 0.01 0.00

(0.004) (0.004) (0.003)

Years of full-time education completed -0.10** -0.05* -0.02**

(0.036) (0.021) (0.006)

Main activity In Education -1.02*** -0.55*** -0.35***

(0.147) (0.096) (0.064)

Main activity, Unemployed, looking for job -0.21 -0.23* -0.06

(0.158) (0.090) (0.099)

Main activity, Unemployed, not looking for job 0.23 -0.24 -0.10

(0.294) (0.193) (0.101)

Main activity, Permanently sick or disabled 0.10 -0.17 -0.10

(0.238) (0.147) (0.100)

Main activity, , Retired 0.53*** 0.35*** 0.22**

(0.096) (0.085) (0.084)

Main activity, 7, Community or military service 0.25 -0.42 -0.36

(0.719) (0.493) (0.529)

Main activity, Housework, looking after children,

others

0.18 0.01 0.08

(0.160) (0.106) (0.062)

Household's total net income, all sources -0.08*** -0.05* -0.03**

(0.022) (0.018) (0.010)

lrscale (Placement on left right scale) -0.30*** -0.28*** -0.15***

(0.053) (0.039) (0.021)

ctzn (Citizen of country) = 1, Yes 0.40 0.48* 0.17

(0.263) (0.232) (0.146)

Member of a discriminated group -0.45*** -0.44*** -0.30***

(0.132) (0.110) (0.076)

(Gender) = 1, Female -0.13 -0.06 -0.01

(0.106) (0.088) (0.050)

(Feeling about household's income nowadays) -0.36** -0.27* -0.07

(0.126) (0.110) (0.059)

ESS round = 6 -0.11 -0.13 -0.03

(0.086) (0.082) (0.049)

ESS round = 7 -0.21 -0.26* -0.12*

(0.163) (0.120) (0.058)

Constant 5.77*** 4.70*** 2.98***

(0.821) (0.713) (0.500)

Observations 69,113 69,113 69,113 69,113

Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05

Table 11: Multinomial Logit Estimations (RRR) with Clustered Errors by Country

DV: Attitudes towards further

Immigration

(from different race/religion)

(1) (2) (3) (4)

Allow

None

Allow A

Few

Allow Some Allow Many

Trust in the European Parliament 0.93 0.96 1.00

(0.037) (0.034) (0.021) BASELINE

Trust in country's parliament 0.88* 0.95 0.99

(0.047) (0.049) (0.029)

General Trust 0.80*** 0.86*** 0.90***

(0.033) (0.031) (0.020)

How satisfied with present state of

economy in country

0.91** 0.96 0.98

(0.031) (0.021) (0.017)

How satisfied with the way democracy

works in country

0.93 0.98 1.00

(0.036) (0.030) (0.022)

How religious are you 0.98 1.01 1.02

(0.041) (0.030) (0.016)

Age of respondent, calculated 1.01 1.01 1.00

(0.004) (0.004) (0.003)

Years of full-time education completed 0.91** 0.95* 0.98**

(0.033) (0.020) (0.006)

Main activity =In Education 0.36***

(0.053)

0.57***

(0.055)

0.70***

(0.045)

Unemployed, looking for job 0.81

(0.127)

0.79*

(0.071)

0.94

(0.093)

Unemployed, not looking for job 1.26 0.78 0.91

(0.372) (0.151) (0.092)

Permanently sick or disabled 1.10 0.84 0.91

(0.262) (0.124) (0.091)

Retired 1.70*** 1.42*** 1.24**

(0.164) (0.121) (0.104)

Community or military service 1.29 0.65 0.70

(0.926) (0.323) (0.371)

Housework, looking after children, others 1.20 1.01 1.08

(0.192) (0.107) (0.067)

Household's total net income, all sources 0.92*** 0.95* 0.97**

(0.020) (0.017) (0.009)

Placement on left right scale

0.74***

(0.039)

0.75***

(0.029)

0.86***

(0.018)

Citizenship (Yes) 1.49 1.61* 1.19

(0.392) (0.373) (0.174)

Member of a group discriminated 0.64***

(0.084)

0.65***

(0.071)

0.74***

(0.056)

Gender = Female 0.88 0.94 0.99

(0.093) (0.082) (0.049)

Feeling about household's income 0.70** 0.76* 0.93

(0.088) (0.084) (0.055)

ESS round = 6 0.90 0.88 0.97

(0.077) (0.072) (0.047)

ESS round = 7 0.81 0.77* 0.89*

(0.132) (0.092) (0.051)

Constant 321.76*** 110.01*** 19.70***

(264.103) (78.430) (9.853)

Observations 69,113 69,113 69,113

AIC

BIC

Number of Clusters

Log likelihood (model)

Log likelihood (null)

154530

154648.9

14

-77252.2

-82967.92

Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05

Table 12: Multinomial Logit Estimation with Different Baseline

DV: Attitudes towards

further Immigration

(1) (2) (3) (4)

(from different

race/religion) Allow None Allow Few Allow Some Allow Many

Trust in EP 0.03 0.07* 0.07

(0.017) (0.028) (0.040)

Trust in Nat.Par. 0.08*** 0.12*** 0.13*

(0.014) (0.028) (0.054)

General Trust 0.08*** 0.11*** 0.22***

(0.015) (0.023) (0.041)

Satisfaction with Economy BASELINE 0.05* 0.08* 0.09**

(0.023) (0.034) (0.034)

Satisfaction with

Democracy

0.05** 0.08** 0.07

(0.018) (0.026) (0.039)

Religion 0.03 0.04 0.02

(0.014) (0.029) (0.042)

Age 0.00 -0.00* -0.01

(0.000) (0.001) (0.004)

education 0.04** 0.08* 0.10**

(0.016) (0.031) (0.036)

Main activity= 2, Education 0.47*** 0.67*** 1.02***

(0.087) (0.113) (0.147)

= 3, Unemployed, looking

for job

-0.02 0.15 0.21

(0.119) (0.129) (0.158)

= 4, Unemployed, not

looking

-0.48* -0.33 -0.23

(0.219) (0.243) (0.294)

5, Permanently sick or

disabled

-0.27 -0.19 -0.10

(0.156) (0.198) (0.238)

= 6, Retired -0.18** -0.32*** -0.53***

(0.065) (0.089) (0.096)

= 7, Community or military

service

-0.68 -0.61 -0.25

(0.703) (0.641) (0.719)

= 8, Housework -0.17 -0.11 -0.18

(0.114) (0.136) (0.160)

Household's total net

income, all sources

0.04*** 0.06*** 0.08***

(0.010) (0.014) (0.022)

Left Right Scale 0.02 0.15*** 0.30***

(0.022) (0.039) (0.053)

Citizen 0.08 -0.22 -0.40

(0.105) (0.170) (0.263)

Discriminated group

member

0.02 0.16 0.45***

(0.071) (0.097) (0.132)

Female 0.07 0.13 0.13

(0.067) (0.075) (0.106)

Feeling about household's

income

0.09* 0.29*** 0.36**

(0.041) (0.083) (0.126)

ESS round = 6 -0.02 0.08 0.11

(0.050) (0.059) (0.086)

ESS round = 7 -0.05 0.09 0.21

(0.087) (0.128) (0.163)

Constant -1.07*** -2.79*** -5.77***

(0.249) (0.456) (0.821)

Observations 69,113 69,113 69,113

Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05

Table 13: Alternative DV Measurement (1) - Multinomial Logit Estimations with Clustered Errors by

Country

DV: Attitudes towards further

immigration from same race/religion as

majority

(1) (2) (3) (4)

Allow None Allow Few Allow Some Allow Many

Trust in the European Parliament -0.06 -0.04 -0.01

(0.036) (0.028) (0.015)

Trust in country's parliament -0.13*** -0.07 -0.01

(0.037) (0.041) (0.022)

General Trust -0.20*** -0.12** -0.08***

(0.041) (0.036) (0.019)

Satisfaction with economy -0.15* -0.05 -0.03 BASELINE

(0.060) (0.034) (0.022)

Satisfaction with democracy -0.06 -0.04* -0.01

(0.038) (0.022) (0.014)

Religion -0.03 -0.01 0.01

(0.049) (0.027) (0.012)

Age 0.00 0.00 0.00

(0.001) (0.001) (0.001)

Years of full-time education -0.07 -0.05* -0.02*

(0.041) (0.025) (0.008)

Main activity: In Education -1.10*** -0.63*** -0.33***

(0.162) (0.117) (0.052)

Unemployed, looking for job -0.10 -0.23** -0.03

(0.211) (0.086) (0.078)

Unemployed, not looking for job 0.41 -0.09 0.09

(0.247) (0.195) (0.102)

Permanently sick or disabled 0.16

(0.242)

-0.05

(0.138)

-0.10

(0.097)

Retired 0.21 0.04 0.02

(0.145) (0.118) (0.078)

Community or military service 0.09

(0.662)

-0.26

(0.767)

-0.28

(0.287)

Housework, looking after children, others 0.19

(0.380)

-0.11

(0.290)

-0.04

(0.217)

Household's total net income, all sources -0.12*** -0.06*** -0.04***

(0.027) (0.015) (0.008)

lrscale (Placement on left right scale) -0.20*** -0.21*** -0.13***

(0.046) (0.037) (0.021)

ctzn (Citizen of country) = 1, Yes 0.57* 0.52* 0.23

(0.283) (0.238) (0.136)

Member of a discriminated group -0.44** -0.37* -0.24**

(0.164) (0.164) (0.078)

(Gender) = 1, Female -0.07 -0.05 0.03

(0.084) (0.077) (0.045)

Feeling about household's income -0.35** -0.29** -0.05

(0.133) (0.101) (0.059)

ESS round = 6 0.02 -0.09 0.02

(0.133) (0.111) (0.049)

ESS round = 7 -0.05 -0.16 -0.05

(0.151) (0.133) (0.062)

Constant 3.84*** 3.83*** 2.61***

(0.718) (0.586) (0.469)

Observations 69,113 69,113 69,113

Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05

Table 14: Alternative DV Measurement (2) Multinomial Logit Estimations w/ Clustered Errors by

Country

DV: Attitudes towards further

immigration from poor

countries

(1) (2) (3) (4)

Allow None Allow Few Allow Some Allow Many

Trust in Europe. Par. -0.05 -0.03 0.01

(0.043) (0.035) (0.022)

Trust in National Par. -0.09 -0.03 -0.01

(0.056) (0.052) (0.029)

General Trust -0.18*** -0.11*** -0.09***

(0.043) (0.034) (0.021) BASELINE

Satisfaction with Country’s

Economy

-0.09** -0.04 -0.02

(0.028) (0.019) (0.017)

Satisfaction with Country’s

Democracy

-0.08* -0.01 0.01

(0.032) (0.031) (0.021)

Religion -0.04 -0.01 0.01

(0.040) (0.031) (0.015)

Age 0.01* 0.01* 0.01

(0.004) (0.004) (0.003)

Years of education -0.07** -0.03* -0.01**

(0.021) (0.014) (0.004)

Main activity, Education -0.95*** -0.42*** -0.26***

(0.110) (0.085) (0.063)

Main activity Unemployed,

looking

-0.11 -0.12 -0.11

(0.134) (0.091) (0.086)

Unemployed, not looking 0.17 -0.31 -0.15

(0.191) (0.207) (0.101)

Permanently sick or disabled -0.14 -0.24 -0.19

(0.200) (0.166) (0.139)

Retired 0.57*** 0.35** 0.16

(0.098) (0.108) (0.092)

Community or military service 0.53 -0.06 0.05

(0.576) (0.465) (0.328)

Housework, looking after

children, others

-0.07 -0.08 -0.06

(0.159) (0.147) (0.088)

Household's income -0.06* -0.03 -0.01

(0.027) (0.020) (0.010)

left right scale -0.32*** -0.28*** -0.16***

(0.054) (0.040) (0.024)

Citizen of country 0.33 0.36 0.20

(0.285) (0.202) (0.121)

Member of discriminated group -0.29

(0.153)

-0.34**

(0.127)

-0.23**

(0.075)

(Gender) = 1, Female -0.20 -0.13 -0.08

(0.103) (0.083) (0.045)

(Feeling about household's

income

-0.31* -0.21* -0.03

(0.125) (0.108) (0.052)

ESS round = 6 0.00 -0.06 0.00

(0.088) (0.072) (0.052)

ESS round = 7 0.17 -0.05 -0.08

(0.168) (0.098) (0.063)

Constant 5.20*** 4.04*** 2.55***

(0.723) (0.650) (0.487)

Observations 69,113 69,113 69,113

Robust standard errors in parentheses

*** p<0.001, ** p<0.01, * p<0.05

Table 15: Robustness Checks with OLS

DV: Attitudes towards further Immigration (from different race/religion)

Variables Model 1 (no cluster) Model 2 (clustered countries) Model 3 (with clustered years)

Trust EP . 01653021*** .01653021 .01609993

Trust National Parl. .02175507 *** .02175507 .02213643

General Trust .0390611*** .0390611*** .0349342

Satisfaction with

Country’s Economy .01576052*** .01576052 .02006403

Satisfaction with

Country’s Democracy .01446984*** .01446984 .0160643

Religion .00239945 .00239945 .00081343

Age -.00077441*** -.00077441 ** -.00070391

Education (years) .01401777*** . 01401777 ** .0140926

Main activity

In Education .17159217*** .17159217 *** .16310532

Unemployed (looking) .05795801*** .05795801 .04091082

Unemployed (not looking) -.02522065 -.02522065 -.02208662

Permanently disabled -.01486653 -.01486653 -.02193073

Retired -.10987906*** -.10987906 - .10673813

Community service .02188429 .02188429 .02887125

Housework -.01826439 -.01826439 -.00993676

Household income .01497591*** .014975910 ** .01675671

Left right scale .0666775*** .0666775 *** .06983584

Citizenship (Yes) -.11231272*** -.11231272 -.15013011

Discriminated Group Member .1010411*** .1010411 .09021006

Female .02749321*** .02749321 .0279425

Income Perception .08615318*** .08615318 . 06979353

ESS 6 .03031585*** .03031585

ESS 7 .05656428*** .05656428

Country ID . 03377155

cons .45070719*** .45070719** .28088265

Observation 69,113 69,113 69,113

R2 0.1390 0.1390 0.1626

Root MSE 0.75979 0.75979 0.74931

AIC 158187.5 158163.5 156222

BIC 158416.1 1 58282.4 156240.3

*** p<0.001, ** p<0.01, * p<0.05

Table 16: Multinomial Logit Estimations with Clustered Errors by Year (ESS round)

(1) (2) (3) (4)

DV: Attitudes towards further Immigration

(from different race/religion)

Allow None Allow

Few

Allow Some Allow Many

Trust in the European Parliament -0.11*** -0.06*** -0.02*

(0.012) (0.013) (0.008)

Trust in country's parliament -0.12*** -0.06*** -0.02

(0.014) (0.011) (0.008) BASELINE

Most people can be trusted or you can't be too careful -0.26*** -0.19*** -0.12***

(0.016) (0.005) (0.005)

How satisfied with present state of economy in country -0.07*** -0.03** -0.00

(0.007) (0.012) (0.015)

How satisfied with the way democracy works in country -0.09*** -0.03*** 0.01

(0.020) (0.008) (0.007)

How religious are you 0.01 0.02*** 0.02***

(0.008) (0.003) (0.002)

Age of respondent, calculated 0.00*** 0.01*** 0.00***

(0.000) (0.000) (0.001)

Years of full-time education completed -0.11*** -0.06*** -0.02***

(0.007) (0.004) (0.002)

Main activity, 2, Education -0.98*** -0.54*** -0.33***

(0.135) (0.045) (0.053)

3, Unemployed, looking for job -0.07 -0.14*** -0.03

(0.083) (0.029) (0.043)

4, Unemployed, not looking for job 0.26 -0.27*** -0.13

(0.255) (0.066) (0.118)

5, Permanently sick or disabled 0.16 -0.08 -0.08

(0.117) (0.071) (0.064)

6, Retired 0.56*** 0.39*** 0.24***

(0.019) (0.037) (0.042)

7, Community or military service 0.03 -0.78** -0.50

(0.907) (0.298) (0.340)

8, Housework, looking after children, others 0.18*** 0.04 0.05

(0.041) (0.039) (0.077)

Household's total net income, all sources -0.10*** -0.04*** -0.02***

(0.008) (0.004) (0.004)

Placement on left right scale -0.32*** -0.28*** -0.16***

(0.013) (0.018) (0.012)

Citizen of country = Yes 0.61*** 0.59*** 0.29***

(0.176) (0.085) (0.052)

Member of Discriminated Group -0.49*** -0.51*** -0.31***

(0.059) (0.029) (0.022)

(Gender) = 1, Female -0.20*** -0.10*** -0.01

(0.058) (0.024) (0.018)

Feeling about household's income -0.21*** -0.19*** -0.08**

(0.027) (0.051) (0.030)

Country = 2, CH -0.56* 0.13 0.02

(0.226) (0.088) (0.091)

Country = 3, CZ 1.37*** 1.27*** 0.43

(0.358) (0.304) (0.256)

Country = 4, DE -1.72*** -1.02*** -0.77***

(0.298) (0.233) (0.167)

Country = 5, DK -0.41* 0.24 -0.23*

(0.162) (0.196) (0.114)

Country = 6, EE -0.33 -0.14 -0.55***

(0.327) (0.282) (0.138)

Country = 7, FI -0.20 0.48*** -0.34*

(0.117) (0.143) (0.150)

Country = 8, FR -0.89*** -0.32 -0.12

(0.260) (0.332) (0.216)

Country = 9, IE -0.95*** -0.66** -0.58**

(0.202) (0.219) (0.189)

Country = 10, NL -0.70*** -0.36 -0.26

(0.165) (0.222) (0.171)

Country = 11, NO -1.52*** -0.51 -0.51*

(0.246) (0.342) (0.239)

Country = 12, PL -2.73*** -1.83*** -1.22***

(0.291) (0.241) (0.188)

Country = 13, SE -3.36*** -2.44*** -1.27***

(0.279) (0.154) (0.137)

Country = 14, SI -1.75*** -0.88* -0.49*

(0.416) (0.367) (0.194)

Constant 6.56*** 5.20*** 3.50***

(0.599) (0.422) (0.257)

Observations 69,113 69,113 69,113

Robust standard errors in parentheses

*** p<0.001, ** p<0.01, * p<0.05

Table 17: Multi-level Logistic Regression for Predicting Immigration Attitudes

Model (1) Model (2)

Trust in the EP 0.057*** 0.057***

(0.0100) (0.0100)

Trust in national parl. 0.12*** 0.12***

(0.011) (0.011)

General Trust 0.11*** 0.11***

(0.0088) (0.0088)

Economic Satisfaction 0.053*** 0.052***

(0.010) (0.010)

Democracy Satisfaction 0.081*** 0.082***

(0.010) (0.010)

How religious are you 0.012 0.012

(0.0067) (0.0067)

Age -0.0011* -0.0011*

(0.00044) (0.00044)

Education 0.062*** 0.061***

(0.0058) (0.0058)

Main activity -0.047*** -0.047***

(0.0079) (0.0079)

Household Income 0.058*** 0.058***

(0.0088) (0.0088)

Left Right Scale 0.11*** 0.11***

(0.0089) (0.0089)

Citizenship -0.33** -0.34**

(0.11) (0.11)

Member of discr.group 0.16* 0.16*

(0.076) (0.076)

Female 0.14*** 0.14***

(0.039) (0.039)

Income Feeling 0.16*** 0.16***

(0.027) (0.027)

ESS Round (base=4)

ESS Round 6 -0.0021

(0.052)

ESS Round 7 0.040

(0.057)

Constant -0.73*** -0.74***

(0.21) (0.21)

Observations 45484 45484

AIC 20765.79 20768.98

BIC 20914.11 20934.76

Log Likelihood -10365.89 -10365.49

CHI2 2216.282 2216.515

Pr > CHI2 0.000 0.000

Standard errors in parentheses. * p < 0.05, ** p < 0.01, *** p < 0.001.

Table 18: Random and Fixed Effects Models for Predicting Attitudes towards EU Integration

Standard errors in parentheses . * p < 0.05, ** p < 0.01, *** p < 0.001.

(1) FE Model (2) RE Model (3) FE Model w/waves (4) RE Model w/waves

Trust in EP 0.332*** 0.360*** 0.328*** 0.356***

(0.00589) (0.00585) (0.00590) (0.00587)

Trust in national parl. 0.0153* -0.0307*** 0.0151* -0.0327***

(0.00643) (0.00636) (0.00643) (0.00636)

General Trust 0.0493*** 0.0165** 0.0518*** 0.0155**

(0.00542) (0.00537) (0.00541) (0.00536)

Economic Satisfaction 0.0455*** 0.0394*** 0.0530*** 0.0456***

(0.00593) (0.00566) (0.00596) (0.00570)

Democracy Satisfaction 0.0628*** 0.0410*** 0.0644*** 0.0450***

(0.00624) (0.00627) (0.00625) (0.00629)

Religiosity -0.00571 0.0130*** -0.00704 0.0125***

(0.00380) (0.00375) (0.00380) (0.00374)

Age -0.000210 -0.000562 -0.0000806 -0.000487

(0.000370) (0.000377) (0.000370) (0.000377)

Education 0.0212*** 0.0242*** 0.0219*** 0.0248***

(0.00205) (0.00207) (0.00204) (0.00207)

Main Activity (paid work baseline)

Education 0.114** 0.183*** 0.127** 0.189***

(0.0437) (0.0445) (0.0436) (0.0445)

Unemployed, looking 0.215***

(0.0606)

0.194**

(0.0617)

0.229***

(0.0604)

0.210***

(0.0616)

Unemployed,not looking 0.128 0.113 0.137 0.123

(0.0953) (0.0970) (0.0951) (0.0969)

Sick or disabled 0.0454 -0.0554 0.0621 -0.0522

(0.0695) (0.0707) (0.0694) (0.0706)

Retired 0.146*** 0.166*** 0.147*** 0.168***

(0.0301) (0.0306) (0.0300) (0.0305)

Comm./military service 0.283 0.172 0.298 0.149

(0.366) (0.373) (0.366) (0.373)

Housework 0.160*** 0.207*** 0.162*** 0.209***

(0.0449) (0.0455) (0.0449) (0.0455)

Household's Income 0.0193*** 0.0332*** 0.0189*** 0.0313***

(0.00481) (0.00476) (0.00480) (0.00476)

Left right scale 0.0405*** 0.0486*** 0.0386*** 0.0483***

(0.00513) (0.00517) (0.00512) (0.00517)

Citizenship -0.157** -0.0769 -0.161** -0.0777

(0.0532) (0.0537) (0.0530) (0.0536)

Discriminated Group Memb. -0.0750 -0.183*** -0.0578 -0.179***

(0.0454) (0.0461) (0.0453) (0.0460)

Female -0.153*** -0.190*** -0.148*** -0.190***

(0.0221) (0.0225) (0.0221) (0.0225)

Income Feeling 0.131*** 0.0928*** 0.127*** 0.0872***

(0.0168) (0.0168) (0.0167) (0.0168)

ESS Round (Base: wave 4)

ESS 6 -0.389*** -0.268***

(0.0310) (0.0254)

ESS 7 -0.398*** -0.197***

(0.0341) (0.0279)

Constant 1.904*** 2.149*** 2.117*** 2.290***

(0.0843) (0.0842) (0.0856) (0.0851)

Observations 45484 45484 45484

26

Figure 1: Bar Graphs of Trust in European Parliament by Attitudes Towards European

Integration (all waves and countries)

27

Figure 2: Histogram of Attitudes Towards Further European Integration by ESS wave and

country

28

Figure 3: Histogram of Attitudes Towards Further Immigration by ESS wave and country

29

Figure 4: Predicted Probabilities for Attitudes towards Further EU Integration

(based on Model 4 in Table 4)

30

Figure 5: Bar Graph of Country Effects (for Mixed Effect Model 2 in Table 8)

31

Figure 6: Predicted Probabilities for Attitudes Towards Further Immigration (based on Model

in Table 10) by Trust in European Parliament

32

Figure 7: Plotted Residuals against Trust in EP (For the Mixed Effects Model)