Measuring country level support for European integration: A median voter approach
Christopher Prosser
University of Oxford, UK
[email protected]
Abstract
Scholars of European have frequently examined questions about the role public opinion toward
European integration plays in domestic and European politics and policy. Existing approaches to
measuring aggregate level opinion toward integration are overly simplistic and problematic. Using
existing Eurobarometer data, this paper proposes a new way of estimating aggregate level support
that utilises a median voter approach to the problem and estimates median position and
polarisation over European integration for each country in a Eurobarometer wave. It then
demonstrates why this approach is superior to existing measures by reanalysing three previously
published studies.
Paper prepared for presentation at the 2012 Elections, Public Opinion, and
Parties Conference, University of Oxford, UK, September 7-9, 2012.
1
What do Europeans think about European integration and what impact does this have on domestic
and European politics? The earliest examination of these questions was concerned with the decline
of support for the European Communities during the period of ‘eurosclerosis’ and its consequences
for further integration.1 This was followed by work which examined the stabilisation of attitudes at a
highly supportive position towards during the 1980’s.2 As the Cold War ended and the European
project picked up speed these feelings began to cool.3 Most recently Hooghe and Marks have argued
that this shift in public attitudes towards European integration has been from a ‘permissive
consensus’ to a ‘constraining dissensus.’4 Many scholars have turned their attention to explaining
these attitudes: Some have focused on the role of economic performance and the perceived
benefits of membership.5 Others have examined the role social and cultural attitudes.6 A different
set of research has turned to questions of the role public opinion toward European integration plays
in politics. Some have examined whether voter attitudes towards integration plays a role in domestic
elections.7 Whilst others have looked at the role of public opinion towards integration plays in
1
David H. Handley, “Public Opinion and European Integration: The Crisis of the 1970s,” European Journal of
Political Research 9, no. 4 (1981): 335–364.
2
Ronald Inglehart, Jacques-Rene Rabier, and Karlheinz Reif, “The Evolution of Public Attitudes Toward
European Integration: 1970-1986,” Journal of European Integration 10, no. 2–3 (1987): 135–155.
3
Mark Franklin, Michael Marsh, and Lauren McLaren, “Uncorking the Bottle: Popular Opposition to European
Unification in the Wake of Maastricht,” Journal of Common Market Studies 32, no. 4 (1994): 455–472; Richard
C. Eichenberg and Russell J. Dalton, “Post-Maastricht Blues: The Transformation of Citizen Support for
European Integration, 1973-2004,” Acta Politica 42 (2007): 128–152.
4
Liesbet Hooghe and Gary Marks, “Calculation, Community and Cues: Public Opinion on European
Integration,” European Union Politics 6 (2005): 419–443; Liesbet Hooghe and Gary Marks, “A Postfunctionalist
Theory of European Integration: From Permissive Consensus to Constraining Dissensus,” British Journal of
Political Science 39 (2009): 1–23.
5
Christopher J. Anderson and Karl C. Kaltenthaler, “The Dynamics of Public Opinion Toward European
Integration, 1973-93,” European Journal of International Relations 2, no. 2 (1996): 175–199; Richard C.
Eichenberg and Russell J. Dalton, “Europeans and the European Community: The Dynamics of Public Support
for European Integration,” International Organization 47, no. 4 (1993): 507–534; Matthew Gabel, “Public
Support for European Integration: An Empirical Test of Five Theories,” Journal of Politics 60, no. 2 (1998): 333–
354; Matthew Gabel and Guy D. Whitten, “Economic Conditions, Economic Perceptions, and Public Support for
European Integration,” Political Behavior 19, no. 1 (1997): 81–96.
6
Joseph H. Janssen, “Postmaterialism, Cognitive Mobilization, and Support for European Integration,” British
Journal of Political Science 21 (1991): 443–68; Lauren McLaren, “Public Support for the European Union:
Cost/Benefit Analysis or Perceived Cultural Threat?,” Journal of Politics 64, no. 2 (2002): 551–566; Adam
Luedtke, “European Integration, Public Opinion and Immigration Policy: Testing the Impact of National
Identity,” European Union Politics 6, no. 1 (2005): 83–112.
7
Clifford J. Carrubba, “The Electoral Connection in European Union Politics,” The Journal of Politics 63, no. 1
(2001): 141–158; Geoffrey Evans, “Europe: A New Electoral Cleavage?,” in Critical Elections: British Parties and
Voters in Long-term Perspective (London: Sage, 1999), 207–222; Geoffrey Evans, “European Integration, Party
2
turnout and voting in European elections.8 Recently efforts have also turned to the more direct link
between public opinion European level policy output.9 Some of these research questions examine
individual attitudes towards integration, but others can only be examined at the aggregate level.
These questions present scholars with the challenge of how to measure attitudes to European
integration at the country level. Despite being a well-established research area and a plethora of
data, existing measures of public opinion to integration have been unsophisticated and have several
problems. This paper outlines these issues and proposes a new way of estimating country level
public opinion towards European integration that draws on spatial models of politics to transform
the existing Eurobarometer data.
Previous measures
Measuring country level public opinion on European integration is almost a unique problem in
political science in the sheer quantity of data available. The Eurobarometer survey series has asked
citizens of the European Union and its predecessors for their opinions towards integration at regular
intervals for almost 40 years.10 Almost all measures of public opinion towards European integration
based on the Eurobarometer survey series (including the current proposal) are based on a question
Politics and Voting in the 2001 Elections,” Journal of Elections, Public Opinion & Parties 12 (2002): 95–110;
Peter Mair, “The Limited Impact of Europe on National Party Systems,” West European Politics 23, no. 4
(2000): 27–51; Cees Van der Eijk and Mark N. Franklin, “Potential for Contestation on European Matters at
National Elections in Europe,” in European Integration and Political Conflict (Cambridge: Cambridge University
Press, 2004), 32–50; Catherine E. de Vries, “Sleeping Giant: Fact or Fairytale?: How European Integration
Afffects National Elections,” European Union Politics 8 (2007): 363.
8
Sara Binzer Hobolt, J.J. Spoon, and James R. Tilley, “A Vote Against Europe? Explaining Defection at the 1999
and 2004 European Parliament Elections,” British Journal of Political Science 39, no. 1 (n.d.): 1–23; Daniel
Stockemer, “Citizens’ Support for the European Union and Participation in European Parliament Elections,”
European Union Politics 13, no. 1 (2012): 26–46; Peter Van Aelst and Jonas Lefevere, “Has Europe Got Anything
to Do with the European Elections? A Study on Split-ticket Voting in the Belgian Regional and European
Elections of 2009,” European Union Politics 13, no. 1 (2012): 3–25; Daniele Caramani, “Is There a European
Electorate and What Does It Look Like? Evidence from Electoral Volatility Measures, 1976-2004,” West
European Politics 29, no. 1 (2006): 1–27.
9
Dimiter Toshkov, “Public Opinion and Policy Output in the European Union: A Lost Relationship,” European
Union Politics 12, no. 2 (2011): 169–191.
10
European Commission, “Eurobarometer”, 1973-2012, http://ec.europa.eu/public_opinion/index_en.htm.
3
that asks survey respondents whether they “think [their country’s] membership of the European
Union is a good thing/bad thing/neither a good or bad thing?”11
Some previous measures of individual attitudes have used multiple questions to create an index of
support for European integration, such as the measure of individual level opinion developed by
Gabel.12 This measure combines the common question with a second Eurobarometer question which
asked whether they were “Very much for/to some extent for/to some extent against/very much
against efforts to unify Western Europe”. Unfortunately however, this second question was only
asked between 1978 and 1994. Similar questions, asking whether people thought their country had
benefited from membership, how happy they were with the speed of integration, or how sorry they
would be if the European Union was scrapped, are also faced with the problem of only being asked
for part of the survey period. That most measures are based on a single question is a matter of
practicality rather than design: the ‘membership’ question is the only one that asks a respondent for
their general attitudes towards integration that has been asked across the entire span of the
Eurobarometer survey series.
In the existing literature, several scales have been constructed from the good/bad/neither good or
bad thing question. The three most common measures differ as to what they do with the
respondents that answer ‘a bad thing’ and ‘neither a good or bad thing’. The simplest, gross support,
is simply the percentage of respondents who answer a ‘good thing’ and does not count the other
two answers. The second measure, first proposed by Inglehart and Rabier, net support, subtracts the
percentage of respondents answering ‘a bad thing’ from the percentage answering ‘a good thing’,
and ignores those answering neither.13 The third, which I term total net support, subtracts the
percentage of respondents answering both ‘a bad thing’ and ‘neither a good or bad thing’ from the
11
Previously ‘European Union’ would have been replaced by the relevant predecessor: the European
Communities, Common Market etc.
12
Matthew Gabel, “Public Support for European Integration: An Empirical Test of Five Theories,” Journal of
Politics 60, no. 2 (1998): 333–354.
13
Ronald Inglehart and Jacques-Rene Rabier, European Community Study 1973, n.d.; Eichenberg and Dalton,
“Europeans and the European Community: The Dynamics of Public Support for European Integration.”
4
percentage answering ‘a good thing’. An immediate issue with all three measures is how they treat
those who are neutral and hostile towards European integration. Is the absence of explicit support
for European integration (neither a good nor a bad thing) the same as opposition to it (a bad thing?)
or is absence if explicit condemnation the same as support? Or, as is the case with net support
should neutrality simply be ignored?
Rather than justify their choices on theoretical grounds most scholars have taken a pragmatic
approach to this problem. Eichenberg and Dalton deal with this issue by arguing that empirically
there is little difference between the measures as they are very highly correlated.14 Although this is
true, it is an artefact of the data and not a structural feature of the measures and the high
correlation overstates the similarity between the measures. The percentage of respondents
answering ‘a good thing’ is generally high (mean = 56.47%), whilst those answering ‘neither a good
or bad thing’ is generally low (mean = 12.46%). In cases where support for European integration is
low the differences between those who are neutral to integration and those opposed will have a
greater impact on the calculation of the score.
The importance of this point is easily illustrated with an example. In case A 60% of respondents think
their country’s membership of the EU is a good thing, 20% think it is neither a good or a bad thing
and 20% think it is a bad thing. In case B 45% answer good, 50% neither good or bad, and only 5%
bad. Finally in case C 62% answer good, 3% neither good or bad, and 35% bad. For the gross support
measure the scores for A, B, and C respectively are 60, 45, and 62. For the net support measure the
scores are 40, 40, and 27. For the total net support measure the scores are 30, -10, and 24. This
illustration shows that the choice of measure can lead to substantial differences in perceived levels
of support for integration – the gross support measure ranks case C as having the highest support,
whilst the net support measure suggests it has the lowest, and the total net support measure puts it
in the middle.
14
They are only referring to net support and total net support, however the same is true for gross support.
5
This is not just an abstract, theoretical issue either. As figure 2, which plots the two net support
measures against the gross support measure illustrates quite clearly, the relationship between the
different measures is heteroscedastic: the correlation between the measures decreases and support
for integration gets lower.
Figure 1. Correlation between the two net support measures and the gross support ‘good thing’
measure. The correlation between the two net support measures (not shown) exhibits a similar
pattern.
Given that, particularly recently, research into public opinion towards European integration has been
driven by a concern with opposition towards the EU, it is important that we are clear what we are
measuring and we do not confound our results by conflating or ignoring neutrality and opposition.
6
A median voter approach
Rather than try and find answer to the question to whether respondents who think that European
integration is ‘neither a good nor a bad thing’ should be counted as opposition, support or ignored
entirely, the approach proposed here sidesteps the problem by estimating a score on an interval
level scale of support for European integration for the median respondent in each observation. Using
a measure of central tendency for each observation rather than the number of respondents who
give a particular answer brings measurement of public opinion towards European integration in line
with the standard practice of aggregated measurement. Using the median in particular fits well with
general theories of political competition, and has the additional advantage of being easily rescaled.
In order to estimate the median opinion on European integration this approach reimagines the
Eurobarometer question about European integration as a spatial model of social choice.
Spatial models of politics have long been a feature of political science, particularly in the literature
on party competition. They originated with the work of Black and Downs, who introduced and
developed the median voter model respectively.15 The detail of the various (increasingly
complicated) models that have been developed since are not important here. This approach uses the
basic theoretical model of electoral competition: In a two choice vote, if voters vote for the option
that is closest to their own views the option that is closest to the median voter’s preference, which
by definition includes the majority of the electorate, will win the election.
The approach here utilises the median voter idea in a different way but shares common assumptions
with the approach:
1) Voters can place different options along a one-dimensional continuum.
2) A voter’s preferences are single peaked. That is a voter will choose the option closest to
their actual preference.
15
Duncan Black, “On the Rationale of Group Decision-making,” Journal of Political Economy 56 (1948): 23–34;
Anthony Downs, An Economic Theory of Democracy (New York: Harper Collins, 1957).
7
3) Voters will always choose the option based on their true preferences.
These assumptions are necessary for the parsimonious conclusions of the median voter model but
they are clearly broken in political reality: politics is multidimensional and some voters will vote
strategically. In order to estimate the median attitude towards European integration it is necessary
to make similar assumptions:
1) The survey question is measuring a one-dimensional continuum.
2) Respondents will answer with the option closest to their true beliefs.
Again the assumptions are simplifications of the reality: European integration is clearly a
multidimensional issue. However given the anonymous and inefficacious nature of survey research
for the respondent, strategic ‘voting’ is likely to be less of an issue. These assumptions are
simplifications but they are given here for transparency. They are assumptions shared by any survey
approach, and more likely to resemble reality than the original median voter model.
Rather than modelling who will win an election, the approach here uses the known distribution of
respondents and responses to estimate what that median position actually is. In order to do so it
utilises an approach first develop by Kim and Fording for use on party positions estimated from
manifesto data.16 The Kim-Fording method estimates the median voter position on a policy scale by
arranging parties in the election in ascending order of their position on the policy scale and
identifying in which party the median voter lies. The interval between the previous and subsequent
parties is used to calculate the median voter position using the following formula:
16
HeeMin Kim and Richard C. Fording, “Voter Ideology in Western Democracies, 1946-1989,” European Journal
of Political Research 33 (1998): 73–97; HeeMin Kim and Richard C. Fording, “Voter Ideology in Western
Democracies: An Update,” European Journal of Political Research 42 (2003): 95–105.
8
= +
50 − × Where:
M = Median position
L = The lower end (ideological score) of the interval containing the median
C = The cumulative frequency (vote share) up to but not including the interval containing
the median
F = The frequency (vote share) in the interval containing the median
W = The width of the interval containing the median
In order to use this method estimate the median position on European integration it is first
necessary to assign scores for each option on an interval scale. The method proposed here is
compatible with any scale but for ease of interpretation and similarity with previous measures a
scale ranging from 0 to 100 is used, where 0 is the anti-integration endpoint and 100 is the prointegration endpoint. The scale assumes an even distribution of attitudes towards European
integration and so the scale is divided into thirds, as shown in figure 3: the first third representing
the area covered by hostile attitudes towards integration, the middle third representing neutral
attitudes that are a mix of good and bad, and the final third representing positive attitudes towards
integration. The survey responses are then assigned values on the scale as follows, illustrated in
figure 3:
1) ‘A bad thing’ is assigned to the intersections between hostile and neutral at one third of the
scale.
2) ‘Neither a good or a bad thing’ is assigned to the midpoint of the scale.
3) ‘A good thing’ is assigned to the intersection between neutral and positive attitudes twothirds into the scale.
9
Figure 2. Attitudes towards European integration and positions assigned on the interval scale.
In order to calculate the width (W) and lower end (L) of each interval the midpoint between the
assigned values are calculated (shown as m1 and m2 in figure 2). The bounds and widths of each
interval are shown in table 1.
Interval
Lower end
Upper end
A bad thing
0
41.66 (m1)
Neither a good or bad thing
41.66 (m1)
58.33 (m2)
A good thing
58.33 (m2)
100
Table 1. Lower and upper ends, and width of each interval
Width
41.66
16.66
41.66
The frequency portion of the equation is now calculated from the Eurobarometer survey results.
Approaching the question of what to do with respondents who answer ‘don’t know’ as if the survey
was an election provides an obvious solution to the problem of what to do with non-respondents:
they are considered as ‘non-voters’ and their abstentions not counted for the estimate of the
median. The proportion of respondents answering each category is then recalculated as the
proportion of respondents who answered one of the three categories. The median score then should
correctly be thought of as the median score of those who answered the question. If we assume a
random distribution of non-answerers than this median would be the same as the sample as a
whole, but whether non-answers are randomly or systematically distributed is outside the scope of
the present paper.
10
The results of the calculations for each country/time observation are illustrated in figure 3.
Belgium
Bulgaria
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Luxembourg
Malta
Netherlands
Poland
Portugal
Republic of Cyprus
Romania
Slovakia
Slovenia
Spain
Sweden
UK
80
70
60
50
40
80
70
60
50
2010h1
2000h1
1990h1
1980h1
1970h1
2010h1
2000h1
1990h1
1980h1
1970h1
2010h1
2000h1
1990h1
1980h1
1970h1
40
80
70
60
50
2010h1
2000h1
1990h1
1980h1
1970h1
2010h1
2000h1
1990h1
1980h1
40
1970h1
EU Median
40
50
60
70
80
40
50
60
70
80
40
50
60
70
80
Austria
year
Graphs by Country
Figure 3. Longitudinal median attitude towards European integration by country
11
The proposed median measure is highly correlated with the three previous measures discussed here:
0.9582 with gross support, 0.9790 with net support, and 0.9873 with total net support. As has
already been discussed however, high correlation should not simply be taken as substitutability. The
main improvement of the median measure over the previous measures is that it does not ignore or
equate the ‘neither good or bad thing’ and ‘bad thing’ responses and produces an estimate that is
theoretically meaningful.
Polarisation
Conceptualising the survey question as a spatial model also suggests an additional measure:
polarisation of attitudes to European integration. Measures of polarisation have long been used in
the literature on party-systems to explain a wide variety of phenomena, from political stability, and
cabinet-survival, to the ‘quality’ of a party system.17 Similarly, scholars of American politics have long
debated the extent and consequences of electorate polarisation in the United States.18 As of yet the
same is not true however of the study of European integration: although many authors have
examined the role competition over European integration might play in elections, no longitudinal
measure of voter polarisation over European integration has been developed. The measure
proposed here seeks to fill this gap.
The measure used is the weighted standard deviation of responses to Eurobarometer question on
attitudes to European integration for each observation, using the same scale as the median
measure, calculated as follows:
17
Giovanni Satori, Parties and Party Systems (Camb: Cambridge University Press, 1976); Paul Warwick,
Government Survival in Parliamentary Democracies (Cambridge: Cambridge University Press, 1994); Russell J.
Dalton, “The Quantity and the Quality of Party Systems,” Comparative Political Studies 41, no. 7 (2008): 899–
920.
18
Gary Jacobson, “Polarized Politics and the 2004 Congressional and Presidential Elections,” Political Science
Quarterly 120, no. 2 (2005): 199–218; Morris P Fiorina, Culture War? The Myth of a Polarized America, 2nd ed.
(New York: Pearson Longman, 2006); Alan I. Abramowitz and Kyle L. Saunders, “Is Polarization a Myth?,”
Journal of Politics 70, no. 2 (2008): 542–555.
12
௣ = ௕ (
̅௘ − ௕ )ଶ + ௡ (
̅௘ − ௡ )ଶ + ௚ (
̅௘ − ௚ )ଶ ௕ + ௡ + ௚
Where:
௕ , ௡ , ௚ are the number of respondents (‘votes’) answering ‘bad thing’, ‘neither good or
bad’, ‘good thing’ respectively.
௕, ௡ , ௚ are the scores assigned on the interval scale to the ‘bad thing’, ‘neither good
or bad’, ‘good thing’ positions respectively.
And, ̅௘ is the weighted mean attitude towards integration, calculated by:
̅௘ =
௕ ∙ ௕ + ௡ ∙ ௡ + ௚ ∙ ௚ ௕ + ௡ + ௚
The results of these calculations are illustrated for each country in figure 4.
Unsurprisingly given that they are calculated from the same data, the polarisation and median
measures are highly correlated (-0.8529). The polarisation measure should be considered an
alternative measure of public opinion towards European integration and not an additional measure.
Caution should be used if both were used in statistical analysis as collinearity may adversely
influence the results. The choice of appropriate measure will depend on the theory that motivates
the analysis. The results in figure 4 illustrate the value of this additional measure, compare for
example the results of the median and polarisation for the Netherlands and Luxembourg, which
show an increase in polarisation over the last 20 years, whilst the median measure has relatively
stable at a highly supportive position.
13
Belgium
Bulgaria
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Luxembourg
Malta
Netherlands
Poland
Portugal
Republic of Cyprus
Romania
Slovakia
Slovenia
Spain
5
15
10
5
15
10
5
1970h1
1980h1
1990h1
2000h1
2010h1 1970h1
1980h1
1990h1
2000h1
2010h1 1970h1
1980h1
1990h1
2000h1
2010h1
UK
10
15
Sweden
5
EU Polarisation
10
15
5
10
15
5
10
15
Austria
1970h1
1980h1
1990h1
2000h1
2010h1 1970h1
1980h1
1990h1
2000h1
2010h1
year
Graphs by Country
Figure 4. Longitudinal polarisation over European integration by country
14
Replicating previous research
In order to demonstrate the effect that choice of measurement has on the outcome of statistical
analysis and the utility of the new measures, three pieces of previously published research that have
used one of the existing public support measures will be retested using all three of the previous
measures and the new median and polarisation measures. The three pieces of research tested use
different statistical techniques and different subsets of the public opinion data. The first two use
public support as an independent variable to explain turnout at European elections, and European
level policy output respectively. The third uses public support as a dependent variable and examines
the effect of economic performance on changes in support for integration.
In Citizens’ Support for the European Union and Participation in European Parliament Elections
Stockemer uses the net support measure for each country at the time of a European election to test
the impact that country level support for European integration has on turnout at European
Parliament elections.19 Stockemer finds that turnout is higher when there is more public support for
integration. Table 2 shows the results of the replication of Stockemer’s analysis. The first notable
result is that if the gross support ‘good thing’ measure had been used than the main finding of the
study would not be statistically significant. Using the other measures the finding is still significant,
and the results are reasonably similar between the different models. In terms of model fit (measured
by R2 and Bayesian information criterion (BIC) statistics, the new median measure offers a modest
improvement to the existing approaches, providing the first piece of evidence in support of the new
measures.
19
Stockemer, “Citizens’ Support for the European Union and Participation in European Parliament Elections.”
15
Gross support model
Net support model
Total net support
Median EU support
EU Polarisation
(original)
model
model
model
Public opinion measure
0.198
0.147**
0.106*
0.445**
-1.723**
(0.117)
(0.059)
(0.572)
(.178)
(0.791)
Compulsory voting
24.649***
24.31***
24.507***
24.01***
23.540***
(5.337)
(4.44)
(5.315)
(5.04)
(5.368)
Electoral system type
1.553
0.63
0.774
0.447
0.614
(2.173)
(3.97)
(3.983)
(3.855)
(4.051)
Simultaneous elections
5.032**
4.99***
4.970**
5.05**
4.980**
(2.173)
(2.15)
(2.186)
(2.16)
(2.194)
GDP per capita
-0.0003**
-0.0003**
-0.0003**
-0.0003**
-0.0002*
(0.0001)
(0.0001)
(0.0001)
(0.0001)
(0.0001)
Small state
9.973**
9.77*
9.962**
10.07**
9.808**
(4.485)
(5.05)
(4.384)
(4.20)
(4.300)
Closeness of the electoral race
-0.054
-0.055
-0.057
-0.065
-0.072
(0.137)
(0.125)
(0.134)
(0.132)
(0.132)
National-level turnout
0.355**
0.344**
0.356**
0.362**
0.379**
(0.144)
(0.150)
(0.143)
(0.143)
(0.138)
Eastern Europe
-16.144***
-17.02***
-15.625***
-15.71***
-17.123***
(5.318)
(5.09)
(5.378)
(5.29)
(5.227)
Constant
20.161
26.38*
29.507**
2.947
48.7389***
(16.610)
(15.17)
(12.834)
(19.99)
11.747
N
118
118
118
118
118
2
R
0.7298
0.7343
0.7312
0.7387
0.7346
Bayesian information criterion
870.6601
868.5817
869.5665
866.5015
869.8584
Table 2. Results of Prais-Winsten AR(1) regressions examining the link between public support for European integration on turnout at European Parliament
elections. For full details of the data other than the Median EU support measure see Stockemer (2012).
16
In Public Opinion and Policy Output in the European Toshkov demonstrates that there is a link
between public support for European integration (measured by the EU average gross support ‘good
thing’ measure for each half-year) and the volume of policy output generated by the European
Commission.20 Toshkov finds that when public support for integration is high there is a high volume
of policy produced, which falls as support decreases. He also finds that the reciprocal relationship
between policy production and public support is much weaker.
The results of the replication analysis, shown in table 3 below do not change any of the substantive
findings of the link between public support for integration and policy output. Again however the
new measures outperform the existing approaches in terms of model fit, with a substantial decrease
in the BIC statistic for the models run with the new measures. The substantial difference between
the polarisation and median measures also suggests a possible different explanation to that offered
by Toshkov: it is possible that the link between public opinion and policy output is better explained
by polarisation over European integration rather than absolute levels of support.
In Post-Maastricht Blues Eichenberg and Dalton examine the impact of macroeconomic performance
on public opinion towards European integration (measured as net support in half years for eight
countries: Belgium, Denmark, France, Germany, Ireland, Italy, the Netherlands, and the UK).21
Eichenberg and Dalton’s main finding is that factors that had previously been found to be important
– economic growth, inflation, unemployment, and trade concentration – had decreased in
importance following the Treaty of Maastricht: all except inflation were no longer statistically
significant, and the substantive effect of inflation had decreased. Table 4 shows the results of the
replication with one exception, in both the median and polarisation models (and the total net
support model) trade concentration (Intra-EU export %) is now statistically significant.
20
Toshkov, “Public Opinion and Policy Output in the European Union: A Lost Relationship.”
Eichenberg and Dalton, “Post-Maastricht Blues: The Transformation of Citizen Support for European
Integration, 1973-2004.”
21
17
Public support
Public support t-1
Public support t-2
Legislative output t-1
Legislative output t-2
Constant
Gross support model
(original)
Net support model
Total net support model
Median EU support model
EU Polarisation model
0.627***
(0.118)
0.164
(0.116)
0.104**
(0.042)
0.032
(0.044)
7.892**
(3.754)
0.677***
(0.120)
0.074
(0.119)
0.137**
(0.061)
0.045
(0.062)
5.769*
(3.319)
0.696***
(0.120)
0.082
(0.119)
0.196**
(0.077)
0.058
(0.080)
-2.932
(2.770)
0.709***
(0.119)
0.048
(0.118)
0.063**
(0.023)
0.021
(0.024)
13.445***
(4.641)
0.677***
(0.120)
0.031
(0.121)
-0.008
(0.006)
-0.002
(0.006)
3.727***
(1.260)
Legislative output
Public support t-1
0.024
0.114
0.050
0.150
-2.657
(0.316)
(0.225)
(0.177)
(0.587)
(2.417)
Public support t-2
0.785**
0.533**
0.396**
1.229**
-5.191**
(0.312)
(0.225)
(0.175)
(0.579)
(2.438)
Legislative output t-1
-0.095
-0.099
-0.090
-0.067
-0.935
(0.113)
(0.114)
(0.114)
(0.115)
(0.115)
Legislative output t-2
-0.094
-0.107
-0.094
-0.073
-0.118
(0.118)
(0.117)
(0.118)
(0.119)
(0.116)
Constant
-12.737
4.891
23.976
-58.552
126.413
(10.09)
(6.223)
(4.096)
(22.751)
(25.422)
Number of Observations
69
69
69
69
69
R2 Public Support
0.7262
0.6727
0.7205
0.7051
0.5727
R2 Legislative output
0.2132
0.2168
0.2066
0.1832
0.2006
Bayesian information criterion
885.1988
934.4112
968.75
807.4372
609.6484
Table 3. Results of Vector Autoregressive models (VAR) comparing public support for European integration and policy output. For full details see Toshkov (2011).
18
Gross support model
Net support model
(original)
Total net support model
GDP
Median EU support model
EU Polarisation model
-2.417
0.643
-8.92322
-1.94538
0.381363
(5.425)
(7.867)
(10.739)
(2.941)
(0.622)
Inflation
-0.996***
-1.217***
-1.38597***
-0.44824***
0.06445*
(0.266)
(0.377)
(0.486)
(0.149)
(0.037)
Unemployment
-0.315
-0.300
-0.77553
-0.23065
0.022616
(0.334)
(0.474)
(0.619)
(0.177)
(0.031)
Intra-EU export %
0.103
0.137
0.331998*
0.107037**
-0.02252*
(0.100)
(0.154)
(0.194)
(0.055)
(0.012)
UK membership referendum
13.743***
place":"Ca28.39851***
28.39851***
11.71735***
-0.73498**
(3.682)
(5.657)
(6.875)
(2.8)
(0.333)
Danish SEA referendum
16.119***
20.547***
28.32927***
9.721005***
-0.16634
(3.902)
(5.45)
(7.206)
(2.173)
(0.45)
UK
-18.897***
-37.898***
-35.7629***
-11.9466***
2.685206***
(2.893)
(4.942)
(5.354)
(1.777)
(0.272)
Denmark
-10.847***
-26.130***
-22.7122***
-7.28495***
2.80089***
(3.452)
(4.801)
(5.933)
(1.932)
(0.236)
Ireland
8.446*
5.176
15.24333
3.167969
0.258332
(4.404)
(6.979)
(9.707)
(2.568)
(0.79)
Italy
13.917***
17.199***
27.32992***
7.085301***
-1.65066***
(2.739)
(4.478)
(5.445)
(1.515)
(0.403)
Netherlands
16.286***
19.285***
27.68886***
5.777824***
-1.47564***
(2.455)
(4.028)
(4.816)
(1.411)
(0.413)
German unification
3.645
4.827*
6.245372
1.470166
-0.58756***
(2.248)
(2.933)
(4.052)
(1.107)
(0.301)
Constant
56.858***
43.352***
18.09958
63.44801***
11.4596*
(8.268)
(12.003)
(15.236)
(4.419)
(0.643)
N
504
504
504
504
504
R2
0.5569
0.4075
0.3037
0.8019
0.9395
Table 4. Linear regression with panel-corrected standard errors showing the effect of macroeconomic performance on public support for European Integration, for details see
Eichenberg and Dalton (2007).
19
This indicates that Eichenberg and Dalton may have been premature in arguing that the importance
of trade concentration no longer played an important role in influencing opinion towards
integration. Additionally once again the model fit is substantially improved by the use of the median
and polarisation measures.22
Conclusion
That the replication of previous research does not result in the dramatic overturning of previous
research should not be confused with an endorsement of the previous measures. As was clearly
demonstrated in each of the replications the new measures proposed here substantially improve
model fit, suggesting that the new measures are a much better estimate of public opinion than
previous methods and result in a reduction of error in statistical analysis. The results here suggest
that the main danger of using the previous methods is committing a type II error and incorrectly
rejecting a hypothesis. This is best demonstrated by the findings that the gross support model of
Stockemer’s study was not statistically significant and the results suggesting Eichenberg and Dalton
may have incorrectly rejected the influence of trade concentration on public opinion.
The median and polarisation measures proposed here offer theoretically meaningful and
demonstrably superior approaches to previous measures of public opinion on European integration.
The theoretical paradigm behind the approach also suggests possible routes for further research into
public opinion on European integration, particularly the determinants and role of public polarisation
over European integration. Scholars of European integration are fortunate in quantity of data
available to research. This paper hopes to play a small part in ensuring that this data is used in the
most effective way possible.
22
Panel Corrected Standard Errors regression does not allow for the calculation of a BIC statistic. Here only R
is used to evaluate model fit.
20
2
Acknowledgements
I would like to thank Daniel Stockemer, Dimiter Toshkov, and Richard C. Eichenberg for providing
their data and assisting me with the replication of their work.
21
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