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Transnational solidarity in the European sovereign debt crisis. Combined
evidence of the European Election Survey and laboratory experiments
Theresa Kuhn, University of Amsterdam
Hector Solaz, University of Birmingham
Erika van Elsas, University of Amsterdam
Abstract. The political turf wars surrounding the European sovereign debt crisis have underlined
both the high political relevance and the fragile state of transnational solidarity in the European
Union. This paper combines evidence from the cross-national European Election survey 2014
and from an original laboratory experiment conducted in the UK and Germany in 2013 to study
transnational solidarity among European citizens. More precisely, we analyse the determinants of
public support for institutional redistribution and of individuals’ actual willingness to share across
borders. Our analyses provide strong support for the hypothesis that transnational solidarity in
the EU is structured by cosmopolitan vs nationalist attitudes rather than by pure economic selfinterest or political ideology. Our paper has important implications for the political economy of
the sovereign debt crisis and for the research on foreign aid support.
Preliminary draft. Please don’t cite nor circulate.
Corresponding author:
Dr. Theresa Kuhn, Assistant Professor, Department of Political Science, University of
Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands
[email protected] www.theresakuhn.eu
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Introduction
The European sovereign debt crisis and the political turf wars it entailed have underlined both
the political relevance and the fragile state of transnational solidarity in the European Union.
Policy makers are confronted with a dilemma. In view of increased international
interdependence, the call for transnational redistribution has become more vocal. However,
citizens do not necessarily adapt their allegiances to the transnationalization of their realm
(Burgoon 2009). To the contrary, globalization also triggers counter-reactions such as
ethnocentrism and parochialism (Margalit 2012; Roudometof 2005).
Therefore, this paper seeks to understand transnational solidarity among European citizens. More
precisely, it analyses the determinants of public support for transnational redistribution using crossnational data of the European Election Survey (EES) 2014, and it studies people’s actual
redistributive behaviour in laboratory experiments conducted in the UK and Germany in 2013.
Our results provide strong evidence for the hypothesis that transnational solidarity in the EU is a
question of cosmopolitan vs nationalist attitudes rather than of utilitarian evaluations or political
ideology. The main finding of the analyses of EES data is that while self-interest, captured by
socio-economic status, has some effect on support for transnational redistribution, this
relationship seems to be mainly mediated by cosmopolitan values and identity. Moreover, the
laboratory experiments show that these values are not mere lip service, but that people
subscribing to cosmopolitan values put their money where their mouth is when deciding whether
to share money with other Europeans. They don’t discriminate between national and European
recipients, whereas people who oppose immigration and European integration give significantly
less to European recipients.
The contribution of this paper is twofold. First, the project joins the debate (Bechtel,
Hainmueller, and Margalit 2014; Beckert et al. 2004) on a crucial, but understudied question,
namely to what extent Europeans’ solidarities extend beyond the nation-state by analysing
people’s readiness to redistribute at the European level. While existing research has focused on
single countries such as Germany (Bechtel, Hainmueller, and Margalit 2014), our study provides
empirical evidence of the entire European Union. Second, research on redistributional
preferences at the European (Burgoon 2009) and national level (Amat and Wibbels 2009; Fong
2001; Rehm, Hacker, and Schlesinger 2012) has mainly relied on survey data. This approach
captures declared preferences, which do not necessarily translate into real behaviour. We solve
this problem by combining observational and experimental data, and we show that the factors
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related to support for institutional redistribution in the EU are also significantly related to
people’s actual willingness to share with other Europeans
This paper has important implications for current policy debates, as highlighted in the economic
crisis and in the controversy around bailouts for member states such as Greece. Moreover, it
places itself in the wider scholarly discussion on the tension between community and scale in
multi-level governance (Hooghe and Marks 2009). Beyond the European realm, its findings are
highly relevant for research on support for redistribution (Alesina and Glaeser 2004; Iversen and
Soskice 2001; Kenworthy and McCall 2008) and support for foreign aid (Milner and Tingley
2013; Paxton and Knack 2012; Prather 2014). Finally, it provides empirical support for the
expectation of Kriesi and colleagues (2008) that we are witnessing the emergence of a new
political divide among an integration-demarcation cleavage that is related to cultural rather than
economic attitudes.
The paper is organized as follows. First, we summarize the state of the art on redistributional
preferences and on transnational solidarity in the EU and then develop the hypothesis guiding
our analysis. We then discuss the research design, methods and results of the cross-national
survey analysis before turning to the set up and results of the laboratory experiments.
Implications and avenues for further research are discussed.
Transnational solidarity in the EU
We borrow Stjerno’s definition of solidarity as ‘the preparedness to share resources with others by
personal contribution to those in struggle or in need and through taxation and redistribution
organised by the state’ (Stjerno 2012: 2). This definition underlines that solidarity goes beyond
mere empathy and implies the readiness to give up part of one’s own resources for the sake of
others. Therefore, two aspects seem to be of prime interest here. First, the question is to what
extent people support institutionalized economic transfers from their own member state to other
member states in dire economic times. Second, it is relevant to know to what extent Europeans
are ready to personally share resources with other Europeans. In this study, we assess both
aspects of solidarity. Transnational solidarity implies that people are willing to share their resources
with members of other national communities.
Consequently, the object under study has two relevant dimensions. The first one relates to
people’s readiness to redistribute and their redistributional preferences. The second dimension
relates to the territorial scope of solidarity. In the present paper, we analyse the European scope
of solidarity.
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With respect to the first dimension, ample research exists on people’s redistributional preferences
(Alesina and Giuliano 2011; Amat and Wibbels 2009; Fong 2001; Rehm 2009; Rehm, Hacker,
and Schlesinger 2012; Svallfors 1997). According to Paskov and Dewilde, solidarity can be
motivated by calculating considerations: by helping others, people improve their own welfare
(Paskov and Dewilde 2012: 417). Similarly, people’s position in society, and their likelihood to
mainly benefit from, or contribute to, the welfare state seems to be a strong predictor of
redistributional preferences (Iversen and Soskice 2001; Rehm 2009).On the other hand, Paskov
and Dewilde speak of “affective solidarity”, which is based on feelings of sympathy and moral
duty (Paskov and Dewilde 2012: 417). In fact, a couple of factors, such as religion (Stegmueller et
al. 2012), perceptions of deservingness (Van Oorschot 2006) and reciprocity as well as beliefs
about the causes of income inequality (Fong 2001) seem to impact people’s feeling of solidarity
and support for redistribution. Equally, (racial) group loyalties influence redistributional
preferences (Alesina and Glaeser 2004; Luttmer 2001). How these redistributional preferences
translate into behaviour is an open question, however.
Second, scholars have investigated to what extent solidarity exists beyond the borders of the
nation state (Beckert et al. 2004; Ellison 2012; Fenger and Van Paridon 2012). As Beckert and
colleagues (2004: 13) note, transnational solidarity is lagging behind and much more difficult to
establish than transnational politics and economy. Citizens still see the national community as the
predominant reference frame for social inequality (Whelan and Maître 2009). This is partly due to
the fact that nation states have long been the main providers of social welfare and therefore
could influence people’s understanding of who should be in or out. Moreover, solidarity is more
easily achieved in culturally homogenous societies. In the context of large-scale immigration,
research on welfare state chauvinism (Crepaz and Damron 2009; Van der Waal, De Koster, and
Van Oorschot 2013) has shown that certain members of Western societies hold generally
egalitarian values but nonetheless think that welfare state services should not be granted to
immigrants. Such an opposition to welfare service provision to immigrants is often rooted in the
feeling that migrants don’t deserve it, they have not (yet) contributed enough to the welfare state
themselves, and it is hard to predict whether they will actually stay long enough to “pay it back”.
In short, many people seem to be “parochially” altruistic (Bernhard, Fischbacher, and Fehr 2006)
– they behave altruistically towards members of their own group but less so towards people
outside their group.
This raises the question of which factors help overcome the national boundaries of solidarity. Put
differently, which individual characteristics make people more willing to redistribute
transnationally in the European Union? We propose two sets of factors that are deemed to
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influence people’s willingness to redistribute EU-wide: People’s socio-economic status, their
attitudes towards inequality, their political ideologies and their support for European integration.
First, support for national redistribution is a question of self-interest (Iversen and Soskice 2001;
Rehm 2009). People who expect to profit from redistribution - generally those with lower socioeconomic positions - tend to be more supportive of national redistribution than others. By
contrast, people with higher socio-economic status generally have to pay higher taxes and
therefore have an incentive to oppose large social expenditures. In the context of our study, this
relationship is more complex: Redistribution from one’s own country to another EU member
state in economic difficulties results in fewer resources for one’s own welfare state. Moreover,
existing research has shown that people with lower socio-economic status tend to be more
eurosceptical (Gabel 1998; Hakhverdian et al. 2013; Kuhn 2012) and more critical towards and
international cooperation (Hainmueller and Hiscox 2006). Therefore, people with lower socioeconomic position should be less supportive of transnational redistribution in the EU.
H1: People with higher socio-economic status are more supportive of transnational redistribution in the EU, and
more willing to share with people from other European member states.
Next, there are good reasons to expect that people who have a more cosmopolitan mind-set are
more supportive of transnational redistribution in the European Union. Rather than representing
a conventional political issue, European redistribution is likely to be part and parcel of a greater
public divide along an integration-demarcation divide that is structured by cultural rather than
purely economic aspects (Kriesi et al. 2008). A considerable share of Europeans has developed a
sense of European collective identity (Kuhn 2015; Risse 2010). In contrast to the “exclusive
nationalists”, they do not only see themselves as part of their national community, but also
identify as European. These people might see other Europeans as equally deserving of
redistribution as citizens of their own country. If group identity is high, then collective and
individual interest becomes interchangeable. It is to be expected that these people are more
willing to redistribute across borders than people who hold a purely national identity. Existing
research supports this claim, Kuhn and Stoeckel (2014) find that European identity is strongly
related to people’s support for European economic governance in the sovereign debt crisis. In
more general terms, a more cosmopolitan identity seems to be associated with preferences for
transnational redistribution. In an experiment with nested public good provision games in several
countries, Buchan and colleagues (2011) have shown that people with more cosmopolitan
identities are more likely to cooperate on a global level and are more willing to contribute to
global common goods. Bechtel and colleagues (2014) find in a survey experiment conducted in
Germany that support for economic bailouts is structured by cosmopolitan vs nationalist
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attitudes rather than by political ideology. In an online survey among Latino Americans, Prather
(2014) finds that support for foreign trade is question of cosmopolitanism rather than collective
interest.
Moreover, people who are more supportive of European integration might see the European
sovereign debt crisis as a negative side effect of an overall positive project that they endorse.
Showing transnational solidarity might be perceived as the bitter pill that needs to be swallowed
in order save the European integration process. In contrast, for people who have had
reservations against European integration from the outset, the current crisis might confirm their
critical position and they might be more reluctant to share resources across borders. We therefore
propose the following hypothesis:
H2: The more cosmopolitan an individual, the more supportive they are of transnational redistribution in the EU,
and the more willing they are to share with people from other European member states.
Research design
To test our hypotheses empirically, we combine evidence from the EES 2014 and an original
laboratory experiment conducted in the UK and Germany in 2013. This research strategy allows
us to maximize the generalizability of our results and to assess actual behavior in addition to
stated preferences. We start by reporting the cross-national survey analysis before turning to the
experimental data.
Cross-national survey analysis
The EES 2014 was conducted in all 28 EU member states in the month following the European
Parliament elections of 22-25 May 2014. It includes a question on financial aid to other EU
countries in economic difficulties, as well as other attitudinal items required for testing the
hypotheses.
Variables
The dependent variable, support for transnational redistribution in the EU, is measured by
respondents’ agreement with the following statement: “In times of crisis, it is desirable for [our
country] to give financial help to another EU Member State facing severe economic and financial
difficulties.” A 4-point scale is used to distinguish between strong and moderate (dis)agreement.
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Respondents were also offered a ‘don’t know’ option, which a total of 1.268 (or 4%) of the
respondents opted for. These respondents are left out of the analysis.
As indicators of socio-economic positions we include education and social class. Level of education
is measured by the age at which a respondent finished full-time education, separated into three
categories: 15 or younger, 16-19, and 20+. Respondents who reported that they were still in
education were classified on the basis of their age: those of 20 years or older fall into the 20+
category, whereas those younger than 20 are excluded from the analysis (since we cannot
determine the age at which they will eventually finish). To measure social class, we use a subjective
measure, which asks respondents to locate themselves on an 11-point scale, where 1 corresponds
to the lowest and 10 to the highest level in society.
Three measures are used to empirically test the second hypothesis. First, attitudes towards
immigration are measured by support for restrictive immigration policy. On an 11-point scale,
answer categories range from “You are fully in favour of restrictive policy on immigration” to
“You are fully opposed to a restrictive policy on immigration”. General EU-support is measured as
evaluations of one’s country’s EU membership as good, bad, or neither good nor bad. This is a
standard and widely used measure of EU support. European identity is measured by agreement with
the statement that “You feel attached to Europe” (from “not at all” to “yes, definitely”, 1-4).
Also this item has been widely used to operationalize European identity. It is worth noting that
this item refers to Europe rather than the EU, and therefore has a primarily cultural rather than
political connotation.
Moreover, we include a number of control variables that are informed by existing research on
support for redistribution and attitudes towards European integration. Support for national
redistribution of wealth is measured on an 11-point scale ranging from fully opposed (0) to fully in
favour (10). Support for transnational redistribution might also be structured by political
ideology. We use the 11-point scale of left-right self-placement. Given that support for European
integration is orthogonal to the left-right dimension in some member states, we also include its
square. All models control for gender as women have been shown to be slightly more
eurosceptical (Nelson and Guth 2000) and more protectionist (Burgoon and Hiscox 2004). At
the country level, we include a control variable for GDP per capita in 2013, and a dummy
variable for whether a country is Eurozone member. In additional models that are not shown
here, we also included a dummy variable for the new member states that joined in 2004-2013 and
for net contributor status. These variables did not change the effect of our independent variables.
Due to high collinearity they are not included in the final models. Missing values were treated by
list-wise deletion.
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Method of estimation
The ordinal nature of the dependent variable requires ordered logistic regression analysis. The
data have a clustered structure with individuals nested in countries. To avoid type-I errors due to
this clustering, the regression models are run with robust standard errors (clustered at the country
level). To prevent spurious relationships due to composition effects at the country level, we
include macro level control variables. Additionally, we check whether these macro controls
sufficiently tease out composition effects by running a model including country dummies, which
takes out all country level variance. This model leaves the individual level results unaffected (see
table 1, model 7).
Results
Table 1 presents the multivariate models. Model 1 includes the two variables relating to socioeconomic status as well as macro-level control variables. Social class has a significant positive
effect on support for transnational redistribution (b=.12). Moreover, people with higher levels of
education are significantly more likely to support transnational redistribution. The effect of socioeconomic status remains robust also when including a set of political attitudes in model 2. So far,
the analyses provide support for hypothesis 1 that people with higher socio-economic status are
more supportive of transnational redistribution.
[Table 1 about here]
Models 3-5 include the three variables to test the hypothesis that more cosmopolitan individuals
are more supportive of transnational redistribution. In model 3 we see that a more restrictive
stance on immigration policy has a strong negative effect on support for transnational
redistribution, providing strong evidence in favour of our hypothesis (b=-.38). Figure 1 displays
this relationship for the four categories of the dependent variable (based on model 3). These
graphs give an insight in the size of the effects. Going from least to most in favour of
immigration restriction, the likelihood to fully agree with transnational redistribution to other EU
member states increases with .14 (for a change of one standard deviation this is .05). A similar
increase occurs for the likelihood of tending to agree. As we would expect, the inverse
relationship is visible for the lower two categories of the dependent variable: as support for
immigration decreases, people become more likely to oppose transnational redistribution. This is
in line with the hypothesis that support for transnational redistribution is a question of
cosmopolitan vs nationalist attitudes.
[Figure 1 about here]
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The analyses provide further support for hypothesis 2 by showing that attitudes towards
European integration are strongly correlated with support for transnational redistribution. The
effects of attachment to Europe (b=.53, model 4) and EU membership support (b=.59, model 5)
are of a similarly large size, and both variables by themselves explain more variance (with a
respective pseudo R2 of .05 and .06) than the set of political issue attitudes in model 2 (pseudo R2
of .03). The effects are robust to the inclusion of other attitudes. Their positive effect remains
when including both simultaneously, indicating that they explain different parts of the variance.
Figure 2 displays the predicted probabilities of support for transnational redistribution by EU
attachment (based on model 4). Going from minimal to maximal EU attachment, the average
change in the predicted probability is .20 (and .06 for one standard deviation change in EU
attachment).
[Figure 2 about here]
With respect to the control variables, support for national redistribution of wealth does not
increase the likelihood of supporting transnational redistribution. The coefficient is even negative,
though insignificant, and remains insignificant throughout different model specifications.
Additional analyses show that a significantly negative effect exists only when we do not control
for both class and education (not shown here). Either of these socio-structural factors fully
accounts for the effect of support for redistribution, indicating that support for national and
transnational redistribution are related only spuriously. The effect of left-right placement is
significant but very small. Turning to the country-level control variables, we find that in countries
with a higher GDP per capita, support for transnational redistribution is higher. A possible
interpretation is that citizens of less affluent EU member states feel that their country is less
capable of aiding other countries. Eurozone member countries demonstrate clearly lower support
for transnational redistribution. This effect appears only when we control for GDP, indicating
that comparing two equally affluent EU member states, the one that is Eurozone member is less
supportive of transnational redistribution.
So far, the analyses provide support for both hypotheses, but which one is more convincing?
Model 6 shows that the effect of education and class decreases once accounting for the
cosmopolitan variables, while the effect of the latter remains robust. Moreover models 3-5
explain more variance than model 1, as shown by the pseudo-r2. Finally, it is instructive to
consider the substantive effect sizes by inspecting the change in the predicted probability of
support for transnational redistribution induced by the independent variables in table 2. An
increase of 0,5 standard deviations of class increase the likelihood of support for transnational
redistribution by 1 per cent, and people with high level of education have a 3 per cent higher
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likelihood of supporting transnational redistribution. On the other hand, an increase of 0,5
standard deviations of immigration attitudes and of European attachment increase the likelihood
by 4 per cent, and a 0.5 standard deviation increase of EU membership support does so by 5 per
cent. All in all these findings suggest that cultural values beat self interest in the explanation of
support for transnational redistribution.
[Table 2 about here]
Laboratory experiment
So far, our analyses provide strong evidence in line with the hypothesis that support for
transnational redistribution in the EU is mainly linked to people’s attitudes about immigration
and European integration rather than motivated by self-interest or political left-right ideology.
However, critics may argue that our dependent and independent variables simply measure the
same latent trait, and that support for transnational redistribution might be mere lip service that
does not translate into actual behavior. In other words, are these cosmopolitan, pro-European
people simply responding in a socially desirable way or are they really willing to give up a piece of
their cake?
To answer this question empirically, we conducted laboratory experiments in four locations in
Germany and the United Kingdom. Experiments are highly beneficial to examine the present
question because they allow analysing actual rather than reported behaviour or opinions on
redistribution, which might be heavily influenced by social desirability. Not only for this reason,
they have become increasingly popular in political science research (Druckman et al. 2006).
Due to the nature of the question, the laboratory experiments had to involve citizens of different
countries and take place in different EU member states. Participants were linked to each other
across locations. Only by doing so, we could analyse people’s redistributive behaviour across
countries without deceiving experimental subjects. Fieldwork took place in four locations in April
and May 2013: Oxford (n=63), Edinburgh (n=43), Berlin (n=68) and Munich (n=43). We opted
for Germany and the United Kingdom because they differ with respect to public opinion
towards European integration. We chose the respective cities because they represent the national
core (Berlin, Oxford) and regions with strong subnational identities (Edinburgh for Scotland and
Munich for Bavaria). The computer assisted experiments were conducted using the software ztree (Fischbacher 2007) and took place in experimental laboratories at academic institutions.
The experiments took place in experimental economics laboratories at academic institutions.
Experimental participants were recruited by the laboratories among university students of all
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disciplines. Only German and UK citizens were allowed to participate in the German and UK
locations, respectively. They received a show-up fee of 5€1 and could keep the pay-offs they had
earned in the games. On average, participants earned 20€ in total. Due to the fact that
participants were matched across locations and their earnings were hence dependent on the
behaviour of people participating elsewhere, payoffs could only be determined and paid out after
three weeks. Participants were informed about the payment procedures ahead of the experiments.
The experiments are based on standard experimental procedures in experimental economics, but
enriched with a multi-level design that reflects the multi-level politics in the European Union.
Experiments consisted of four decision games, two of which form the empirical basis for the
analysis here: Dictator Games as well as Public Goods Provision Games. They were followed by a 20minute questionnaire that tapped respondents’ socio-economic background, collective identities,
political attitudes, and international experiences.
Each experiment consisted of a number of decisions. In each decision, participants received an
initial endowment, which would be paid out in cash at the end of the experiment, and had to
choose whether to keep it or to allocate it to another anonymous and randomly chosen
participant. Their payoffs depended on their own decisions and on other participants’ decisions2.
Subjects were not informed about the decisions taken by their peers, nor did they know who they
were matched with. It is important to reiterate that we did not deceive subjects at any point in the
experiment.
Throughout the experiments, two decision parameters were varied. First, participants received
different information on where the recipient was from: Either from the same town, the same
country or from another EU member state3. Second, the scenario was varied: In the Dictator
Games, subjects had to decide whether to keep their endowment or to allocate part of it to
another anonymous and randomly chosen participant who had not received any endowment.
This game thus induced inequality between the donor and the recipient. In the Public Goods
Provision Games, subjects had to choose whether to allocate their endowment to a common
account that was shared with three other anonymous and randomly chosen participants or to
keep it for themselves. If they kept it, they received the full amount at the end of the game in
cash; if they allocated it, the total amount in the common account was doubled and equally
distributed among the four participants and paid out in cash. This game highlighted mutual trust
and cooperation.
Variables
1
6 GBP in the United Kingdom.
The exact wording of the instructions given to participants can be found in the appendix.
3
Note that no information about the exact member state was given.
2
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The unit of analysis refers to decisions. Each participant took part in two games with three
decisions each. Decisions referred to contributing the local, national, and European level,
respectively, and the order in which they are presented to subjects was randomly assigned. We
analyse each game separately and present pooled analyses of decisions nested in participants. We
use total contributions per decision as a dependent variable, and the different information on
whether the contributions go to a local, national, or European participant as independent
variables. We interact these dummy variables with our independent variables.
With respect to the independent and control variables relating to the respondents, we mirror the
EES as closely as possible. Orientations towards European integration are captured by EU
membership support (same wording as in EES) and by identification as European. Respondents
were asked, “Do you see yourself as [country national] only/ [country national] and European/
European and [country national] / European only?”. Attitudes towards immigration are
measured by agreement with the statement “Right now [country] is taking too many immigrants”
on an 11-point scale.
Socio-economic background usually refers to people’s class, education, and income. As the
sample is drawn among university students, participants’ educational background cannot be
varied. While we asked participants to indicate the monthly amount of money at their disposal,
these data do not seem to be reliable. We therefore exclusively refer to participants’ self-reported
class, ranging from working class to upper class.
The following item refers to inequality aversion. “Please indicate to what degree you personally
agree with the following statements: Right now, differences in incomes are too large in
[country]”. Answer categories range from absolutely agree (1) to absolutely disagree (11). People’s
political ideology is measured using the same 11-point left-right scale spectrum as in the EES.
Additionally, the models control for age and gender. Table 2 shows the descriptive statistics of
these variables.
Results
Table 3 shows the direct effect of a European cue versus a national recipient cue on
contributions in the dictator game and in the public goods provision game. We find very little
difference between contributions to national and European recipients. Thus, on average people
don’t make a difference between giving to someone form their own country or from another
European member state. However, this does not mean that the origin of the recipient does not
play a role at all. In fact, some people might actually give more if they know that the money is
going to someone in another member state, for example, because they might feel pro-European
or they might think that people in their own country might need it less.
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[Table 3 about here]
We therefore introduce interaction terms in order to test our hypotheses on socio-economic
status and cosmopolitanism. In each model in table 4, the dummy variable “European recipient”
is interacted with the independent variable of interest. We can see that only the three variables
referring to EU membership support, European identification and immigration support have a
significant interaction effect with European recipient cue, whereas class membership and general
inequality aversion don’t play a role. In model 2, when accounting for immigration attitudes, the
European recipient cue has a strong and highly significant negative effect. People who most
strongly oppose immigration give about 64 tokens less to European recipients than to recipients
from their own country. This difference decreases as immigration support increases.
[Table 4 about here]
This relationship is further clarified in figure 3: People who oppose immigration to their country
give significantly less to a European recipient than ta national recipient, while respondents in
favour of immigration don’t seem to make a difference in their contributions. The relationship is
less clear for the public goods provision game. We find a similar pattern when referring to
European identification (model 4): In the dictator game, there is strong and significant negative
direct effect of European origin cue on contribution, but it is almost entirely moderated by
European identification. People with exclusive national identity give significantly less to recipients
from another EU country, while participants who also identify as European don’t discriminate
between recipients. The very few people who primarily or exclusively identify as European seem
to give even more to European recipients, but the confidence intervals fan out, which is probably
due to the low numbers of observations. While we find a similar relationship for the public goods
provision game, this effect is not statistically different from 0. Finally, model 5 includes an
interaction effect with EU membership support, People who think that EU membership is a bad
thing contribute almost 100 tokens less in the dictator game, whereas participants who support
EU membership don’t make a difference between EU and national recipients. This pattern also
holds with respect to the public goods provision game.
[Figure 3 about here]
[Figure 4 about here]
All in all, these results support the hypothesis that transnational solidarity in the EU is mainly a
question of collective identity and attitudes towards internationalization. They also strongly
suggest that reported European identification is more than lip service but translates into real
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behaviour and renders people more willing to decrease their material welfare for the sake of other
Europeans.
Robustness checks
We estimated a number of additional models so as to ascertain whether our findings are robust
across model specification. Due to space limitations, the results are not reported here, but we
summarize the main findings. First, we also included interactions of the origin cues with political
ideology and inequality aversion. This did not yield any significant effects. Next, we used two
alternative dependent variables: The first one, “total EU redistribution”, referred to the absolute
amount of tokens transferred to participants in another EU member state in each game. To
discount the possibility that people are contributing more at the EU level than others simply
because they are generally more generous, the second operationalization, “net EU redistribution”
measured people’s contribution at the European level minus their contribution at the national
level. The results confirmed the findings reported in this paper. Moreover, we estimated
additional models that included dummy variables for each experimental location (Edinburgh,
Munich, Oxford, while Berlin served as the reference category) so as to capture potential
contextual effects. While participants in Oxford and Munich contributed significantly less in
some decisions, this effect was not robust and did not substantively change the individual effects.
Finally, as each subject had to take three decisions per game (contribution to local, national or
European subject, random order), they might understand the rationale of the experiment after
the second decision. Hence, critics might argue that while decisions were incentivized, subjects
might still have acted in a socially desirable manner and might have based their second and third
decisions on their earlier contribution. To eliminate the possibility that our findings are driven by
such an effect, we moved from a within-subject design to a purely between-subject design by
analysing the first decision only. The results confirmed the findings reported here.
Discussion and outlook
The aim of this paper was to investigate who are the Europeans that display transnational
solidarity in the European sovereign debt crisis. In line with Kriesi et al. (2008) and confirming
existing single-country studies, we expected transnational solidarity to be structured by a cultural
cosmopolitanism vs nationalism fault line rather than by political ideology or self-interest. To this
aim, we assessed public support for transnational redistribution using the EES 2014 and we
analyzed people’s readiness to redistribute to citizens from other EU member states in laboratory
experiments in the United Kingdom and in Germany. Experimental participants were given an
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endowment and were confronted with a series of decisions in which they could either keep their
endowment or give (part of) it to participants from other EU member state.
Both the cross-national survey analysis in the EU-28 and the laboratory experiment strongly
suggest that people’s orientations towards European integration and immigration are the most
powerful predictors, while self-interest played a less important role. EU membership support is
significantly associated with higher levels of redistribution towards other European participants
under all conditions analyzed, while the positive and significant effect of European identification
was slightly less robust. Equally, people holding a more restrictive stance on immigration policy
are less supportive of transnational redistribution, and they are also less generous towards other
Europeans in incentivized laboratory experiments. In contrast, respondents’ political ideology
and their attitudes towards inequality were significantly related to the dependent variables in very
few models. This suggests that transnational redistribution in the European Union is not a
“conventional” political issue that can be easily integrated in the domestic political spectrum. It
also suggests that transnational solidarity in the EU is motivated by affective solidarity rather than
by calculating considerations.
There are some limitations to this study. The analyses documented in this paper refer to
correlation rather than causation. It is impossible to assess causality in cross-sectional surveys
such as the EES, and while the great strength of experimental research lies in random assignment
to treatments, the hypotheses here related to subjects’ characteristics rather than to having been
in a certain treatment group. This limits our ability to make causal claims, as we cannot say, for
example that membership support causes redistribution.
On the other hand, the fact that findings are very similar across data and methods employed
increases our confidence in their validity. Moreover, it suggests that social scientists may be more
confident in the external validity of laboratory experiments: while based on a small sample of
university students, the relationships found in the lab are confirmed in a cross-national,
representative survey in the EU-28.
19
Tables and figures
Table 1: Ordered logit models (with clustered SE's) explaining support for financial help to other EU countries Socio-‐structural factors Age Male Class (subjective, 1-‐10) Low educated (ref: middle) High educated (ref: middle) Attitudes Support redistribution (z) Left-‐right (z) Left-‐right squared (z) Restrict immigration (z) Attachment to EU (z) EU membership support (z) Country level GDP per capita (2013) Eurozone member (0/1) 1 2 3 4 5 6 0.00 (.00)** 0.00 (.00)** 0.00 (.00)*** 0.00 (.00) 0.00 (.00) 0.00 (.00) 0.14 (.03)*** 0.14 (.03)*** 0.16 (.03)*** 0.13 (.04)*** 0.12 (.03)*** 0.14 (.04)*** 0.12 (.02)*** 0.12 (.02)*** 0.11 (.02)*** 0.08 (.02)*** 0.08 (.02)*** 0.07 (.02)*** -‐0.26 (.06)*** -‐0.26 (.06)*** -‐0.23 (.05)*** -‐0.18 (.06)*** -‐0.16 (.06)** -‐0.11 (.06)* 0.43 (.07)*** 0.42 (.07)*** 0.38 (.06)*** 0.33 (.07)*** 0.31 (.06)*** 0.24 (.06)*** -‐0.03 (.03) 0.01 (.03) -‐0.11 (.05)** -‐0.11 (.03)*** 0.01 (.02) -‐0.00 (.02) -‐0.38 (.05)*** -‐0.30 (.04)*** 0.53 (.05)*** 0.33 (.04)*** 0.59 (.04)*** 0.44 (.03)*** 0.01 (.00)*** 0.01 (.00)*** 0.01 (.00)*** 0.01 (.00)*** 0.01 (.00)*** 0.01 (.00)*** -‐0.36 (.17)** -‐0.37 (.17)** -‐0.32 (.15)** -‐0.31 (.17)* -‐0.45 (.16)*** -‐0.38 (.15)*** Constant cut1 0.03 (.30) 0.06 (.28) 0.10 (.29) -‐0.39 (.34) -‐0.39 (.31) -‐0.46 (.31) Constant cut2 1.37 (.31)*** 1.40 (.28)*** 1.47 (.30)*** 1.01 (.34)*** 1.05 (.31)*** 1.03 (.31)*** Constant cut3 3.60 (.33)*** 3.64 (.30)*** 3.76 (.32)*** 3.34 (.36)*** 3.40 (.33)*** 3.46 (.33)*** Pseudo R2 0,03 0,03 0,04 0,05 0,06 0,08 Observations 20,633 20,633 20,633 20,633 20,633 20,633 Source: EES 2014. Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05. Note: Model 7* includes country dummies 7* 0.00 (.00) 0.11 (.04)*** 0.05 (.01)*** -‐0.14 (.05)*** 0.23 (.05)*** 0.00 (.03) -‐0.10 (.03)*** 0.01 (.02) -‐0.30 (.04)*** 0.34 (.04)*** 0.44 (.03)*** -‐1.34 (.15)*** 0.18 (.14) 2.67 (.14)*** 0,10 20,633 20
Table 2 Substantive effect sizes: effect of change in X on change in predicted outcome Socio-‐structural factors Age Male Class (subjective, 1-‐10) Low educated (ref: middle) High educated (ref: middle) Attitudes Support redistribution (z) Left-‐right (z) Left-‐right squared (z) Support immigration (z) Attachment to EU (z) EU membership support (z) Change in X Model 1 Model 6 (+/-‐ .5 SD) (0 to 1) (+/-‐ .5 SD) (0 to 1) (0 to 1) 0,01 0,02 0,03 0,03 0,05 0,01 0,02 0,01 0,01 0,03 (+/-‐ .5 SD) (+/-‐ .5 SD) (+/-‐ .5 SD) (+/-‐ .5 SD) (+/-‐ .5 SD) (+/-‐ .5 SD) 0,05 0,03 0.00 0,01 0.00 0,04 0,04 0,05 Eurozone (0 to 1) 0,05 GDP (+/-‐ .5 SD) 0,03 Source: EES 2014. Note: Average predicted changes (across 4 categories of DV) obtained through stata's prchange command, based on models 1 and 6 in table 1. Table 3: Aggregate analysis of contributions towards local, national, and European recipients in lab experiments Local recipient European recipient Constant N (decisions) Dictator game 16.908 (1.92)* -‐4.742 (0.54) 265.940 (17.13)**** 651 Public goods provision game 3.940 (2.47)** -‐0.392 (0.25) 49.452 (19.01)**** 651 Source: own laboratory experiment. Panel data analysis. Individual fixed effects. Coefficients refer to contributions in each decision. Standard errors in parentheses. 2-‐tailed test,* p<0.1; ** p<0.05; *** p<0.01; **** p<0.001 21
Table 4: Treatment effects on contributions, interacted with participant characteristics Social class Participant characteristics Age Gender Class DG Support for immigration European identity PGG DG 2.68 (3.44) -‐0.35 (0.56) 3.17 (3.46) -‐0.20 (0.55) 14.02 (33.06) -‐6.94 (5.35) 15.52 (33.04) -‐37.53 (19.04)* -‐1.86 (3.18) -‐38.75 (18.40)* PGG DG EU membership support PGG DG PGG 0.88 (3.56) -‐0.68 (0.56) 2.70 (3.98) -‐0.01 (0.65) -‐6.48 (5.29) 25.33 (35.19) -‐1.72 (5.57) 23.42 (33.18) -‐5.82 (5.37) -‐2.81 (2.95) -‐46.12 (19.21)* -‐3.42 (3.04) -‐37.67 (18.52)* -‐2.11 (3.00) Ideology 3.16 (10.25) -‐0.25 (1.66) 8.76 (11.23) 1.49 (1.80) 7.01 (10.87) 0.15 (1.72) 6.60 (10.38) 0.47 (1.68) Inequality aversion -‐1.70 (6.60) 2.93 (1.07)** -‐2.14 (6.61) 2.79 (1.06)** -‐2.96 (7.07) 3.02 (1.12)** -‐3.63 (6.63) 2.63 (1.07)* Support for immigration European identity (0-‐3) EU membership support Recipient in game Local 21.73 (28.39) European -‐27.96 (28.39) Interactions with recipient 4.14 (6.27) 2.38 (1.03)* 35.67 (28.06) 9.86 (4.57)* 15.22 (27.88) 7.26 (4.66) -‐0.89 (6.20) 10.75 (18.82) 9.65 (4.16)* -‐1.97 (14.01) 4.81 (3.04) -‐57.71 (22.87)* 3.06 (5.10) 5.73 (6.20) -‐64.38 (18.82)*** -‐3.90 (4.16) -‐31.94 (14.01)* -‐1.94 (3.04) -‐96.25 (22.87)*** -‐11.22 (5.10)* Local*Class -‐1.90 (9.15) 1.71 (2.00) EU*Class 6.36 (9.15) -‐2.02 (2.00) Local*Inequality aversion EU*Inequality aversion Local* Immi. support 0.85 (2.70) -‐0.87 (0.60) EU* Immi. support 8.77 (2.70)** 0.58 (0.60) Local*European identity 20.80 (12.75) -‐0.94 (2.76) EU*European identity 25.81 (12.75)* 2.45 (2.76) Local*EU support 44.63 (13.04)*** 0.71 (2.91) EU*EU support Constant 302.42 (125.41)* N 552 52.87 (13.04)*** 6.736 (2.907)* 44.48 (20.44)* 246.9 (137.8) 22.00 (22.13) 326.0 (131.3)* 43.73 (20.81)* 274.1 (141.4) 23.93 (23.00) 552 552 552 519 519 543 543 Source: own laboratory experiment. Panel data analysis. Individual fixed effects. Coefficients refer to contributions in each decision. Standard errors in parentheses. 2-‐tailed test,* p<0.1; ** p<0.05; *** p<0.01; **** p<0.001 22
Figure 1: Predicted probability of support for transnational redistribution (1-‐4) by support for immigration Source: EES. Note: Average predicted change (from minimum to maximum) over the four categories of dependent variable is .14. Figure 2: Predicted probability of support for transnational redistribution (1-‐4) by EU attachment Source: EES. Note: Average predicted change (from minimum to maximum) across the four categories of dependent
variable is .20 23
Figure 3: Effect of European recipient as immigration support increases in Dictator game (left) and Public Good Game (right) Figure 4: Effect of European recipient as European identity strengthens in Dictator game (left) and Public Good Game (right) 24
Appendix
Appendix table 1: Descriptive statistics of experimental data
Variable Age Gender Class Ideology EU membership support European identification Ntl. inequality is too high n 201 203 191 197 197 188 199 Mean 23.76 .43 2.96 4.34 2.64 1.88 7.93 Std. Dev. 4.62 .50 .93 1.76 .63 .67 2.96 Min 19 0 1 1 1 1 1 Max 52 1 5 10 3 4 11 25
Appendix 2
Wording of experimental instructions
General instructions:
Welcome to this experiment. This experiment is about how people make decisions. If you pay
close attention to the instructions then you could make a significant amount of money.
Feel free to ask the monitor questions as they arise. From now until the end of the session,
unauthorized communication of any nature with other participants is prohibited. Please note that
the consumption of food and beverages is not allowed during the experiment.
This experiment consists of 4 modules and one questionnaire at the end. Instructions will be
handed out at the beginning of each module. We ask that you plan on staying until the end of the
session, which will last about 90 minutes.
In this experiment you are going to be asked to take decisions that affect you and other people.
Some will be in this city, but they may not be in this room now; some will be from other cities in
the United Kingdom, and some will be from other member states of the European Union.
At this point, some people may have already participated in this experiment, and other groups are
participating in the same experiment these weeks. Your choices, and the choices by others, will
be matched with the help of some colleagues at another university once the research is finished.
You will be paid £6 in cash as a show up fee at the end of this session, and in three weeks time,
at the end of this research, you will receive an email asking you to come to be paid in cash for the
decisions that you and the people you have been matched with made.
The same instructions are being given to other people in other countries. Everyone will get the
same materials that you get, and is hearing the same thing you are, but in their own language.
All of the decisions are similar, so please pay attention to these instructions. At the outset of each
decision you will be given tokens. It will be important to keep in mind that 1000 tokens are worth
£3.25 to you. We have taken care that the tokens are worth the same value in terms of what
could be purchased with them in each participating country.
Again, keep in mind that you are being matched with other people (some of whom are from
around here, and others from other places in the UK or other European member states). Your
decisions, and the decisions of the other participants, will affect how much you make. When the
research is finished, our server will match the information about others’ choices in order to
calculate each participant’s payments. This may take a few weeks, and that’s why you will receive
your payoffs in three weeks time, but you will receive a £6 cash show up fee before you leave
today.
26
Dictator game
a) In this module you are going to make three independent decisions.
b) Half of the participants will receive an Endowment of 1000 tokens (group A), and the other
half will not (group B).
c) Each participant who receives an Endowment (group A) will be randomly paired with another
participant who has not (group B). You will not know the other person's identity, nor will
they know yours. Nor will these identities be revealed after the session is completed.
d) However, before the endowments are distributed and the pairing takes place, you may
allocate the endowment between yourself and the other person as you wish if you were to
receive this Endowment.
e) Profits in this module will be calculated in the following way:
i)
Group A: Profits = Endowment – Amount Sent
ii)
Group B: Profits = Amount Received
Decision 1
Remember that you don’t know yet whether you are in Group A or in Group B.
How many of the 1000 tokens do you send to the other participant knowing that he/she is
participating in another location in the UK?
How many of the 1000 tokens do you keep for yourself (remember that the sum of both
amounts have to be equal to 1000 tokens)?
Decision 2
Remember that you don’t know yet whether you are in Group A or in Group B.
How many of the 1000 tokens do you send to the other participant knowing that he/she might
not be in this room, but is participating in this local area?
How many of the 1000 tokens do you keep for yourself (remember that the sum of both
amounts have to be equal to 1000 tokens)?
Decision 3
Remember that you don’t know yet whether you are in Group A or in Group B.
How many of the 1000 tokens do you send to the other participant knowing that he/she is
participating in another member state in the European Union?
How many of the 1000 tokens do you keep for yourself (remember that the sum of both
amounts have to be equal to 1000 tokens)?
[NB: all participants were asked to make all three decisions; decisions were in a random order]
27
Public goods provision game
In this module you are going to make three independent decisions. You will be given 100 tokens
in each one. Your task is to decide how to allocate your tokens between two different accounts.
You can put your tokens into your “Personal” account or into, what we call now, the “Common”
account. The number of tokens you put into any account is entirely up to you.
Whatever you put into the “Personal” account is yours and will not be shared with anyone else.
In other words, every token you put into this account is independent of the other participant’s
decisions.
Any token that you, and three other people you will be grouped with, put into the “Common”
account will be doubled by me. That amount will be equally distributed among you and the three
other participants.
Before you make your decisions, I want to make sure that you understand how the amount you
obtain is determined. Therefore I am going to give you three examples. Please pay close
attention. Once I am finished with the examples we will test whether you have understood the
instructions asking you a few simple questions. Your performance in the test will not affect your
payoffs.
For example #1, suppose that you put 100 tokens in your “Personal” account and the other three
people put a total of 120 tokens in the “Common” account. In that case, the 120 tokens in the
“Common” account will be doubled (to 240) and shared equally among you and the other three
people (60 each). You would receive 100 from your “Personal” account that you kept, and 60
from your share of the “Common” account. You would end up with 160 tokens.
You
Personal Account
100
Common Account
0
Total
100
Others
120
Total
120
Increased
Your share
100
100
240
60
160
To take another simple example (#2) suppose you put 80 of your tokens in the “Common”
account and no one else put any tokens in the “Common” account. What would you receive?
You would receive 20 tokens from your “Personal” account. Given that there were 80 tokens in
the “Common” account that amount would be doubled to 160 and you would get an equal share,
which is 40 tokens. The other people in your group also get 40 tokens. You would end up with
60 tokens.
You
Personal Account
20
Common Account
80
Total
100
Others
0
Total
80
Increased
Your share
20
20
160
40
60
28
Finally, let me give one more example (#3). Suppose you put all 100 of your tokens in the
“Common” account. Suppose that the other 3 people did the same thing. That means a total of
400 tokens in the “Common” account. How much would you receive?
You
Personal Account
0
Common Account
100
Total
100
Others
300
Total
400
Increased
Your share
0
0
800
200
200
Now please answer the test
[participants were asked to pass a computerized test that checked their comprehension of the
module before making their decisions]
Decision 1
As I mentioned you are going to take a decision that affects you and three other people who
participate in your common account. These three other participants are randomly determined. All
three participants live in this local community. This is why we call the common account now the
local account.
How many of your tokens do you give to the local account (Remember that the remaining
amount goes into your private account)?
Decision 2
As I mentioned you are going to take a decision that affects you and three other people who
participate in your common account. These three other participants are randomly determined. All
three participants live in the United Kingdom. This is why we call the common account now the
UK account.
How many of your tokens do you give to the UK account (Remember that the remaining
amount goes into your private account)?
Decision 3
As I mentioned you are going to take a decision that affects you and three other people who
participate in your common account. These three other participants are randomly determined. All
three participants live in the European Union. This is why we call the common account now the
EU account.
How many of your tokens do you give to the EU account (Remember that the remaining amount
goes into your private account)?